From 8f86c6f4eac64a6055a3a77f5c15dcf4cbffe307 Mon Sep 17 00:00:00 2001 From: MikeLippincott <1michaell2017@gmail.com> Date: Mon, 8 Jun 2026 14:50:45 -0600 Subject: [PATCH 01/25] progress capture --- .gitignore | 2 + .pre-commit-config.yaml | 64 + 0.data-download/1.data_downloader.ipynb | 31 +- .../2.construct_gene_dictionary.ipynb | 114 +- 0.data-download/download_data.sh | 18 + .../results/all_corum_results.parquet | Bin 0 -> 1739705 bytes .../results/all_drug_results.parquet | Bin 0 -> 4275240 bytes .../results/all_reactome_results.parquet | Bin 0 -> 7107699 bytes 9.webapp/.streamlit/config.toml | 2 + 9.webapp/0.single-dependency-umaps(1).ipynb | 30279 ++++++ 9.webapp/1.latent-umaps(1).ipynb | 86709 +++++++++++++++ 9.webapp/8.spider_plots.ipynb | 266 + 9.webapp/Justfile | 18 + 9.webapp/app.py | 305 + 9.webapp/app_utils.py | 432 + 9.webapp/pyproject.toml | 24 + 9.webapp/test_notebook.ipynb | 87386 ++++++++++++++++ 9.webapp/uv.lock | 1972 + README.md | 27 +- 19 files changed, 207569 insertions(+), 80 deletions(-) create mode 100644 .pre-commit-config.yaml create mode 100644 0.data-download/download_data.sh create mode 100644 5.drug-dependency/results/all_corum_results.parquet create mode 100644 5.drug-dependency/results/all_drug_results.parquet create mode 100644 5.drug-dependency/results/all_reactome_results.parquet create mode 100644 9.webapp/.streamlit/config.toml create mode 100644 9.webapp/0.single-dependency-umaps(1).ipynb create mode 100644 9.webapp/1.latent-umaps(1).ipynb create mode 100644 9.webapp/8.spider_plots.ipynb create mode 100644 9.webapp/Justfile create mode 100644 9.webapp/app.py create mode 100644 9.webapp/app_utils.py create mode 100644 9.webapp/pyproject.toml create mode 100644 9.webapp/test_notebook.ipynb create mode 100644 9.webapp/uv.lock diff --git a/.gitignore b/.gitignore index 78c2fae..9c6700f 100644 --- a/.gitignore +++ b/.gitignore @@ -4,3 +4,5 @@ __pycache__ 2.train-VAE/parameter_sweep .DS_Store +9.webapp/gene_dependency_webapp.egg-info +*.pyc diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml new file mode 100644 index 0000000..b6f56df --- /dev/null +++ b/.pre-commit-config.yaml @@ -0,0 +1,64 @@ +repos: + - repo: https://gitlab.com/vojko.pribudic.foss/pre-commit-update + rev: v0.9.0 # Insert the latest tag here + + hooks: + - id: pre-commit-update + args: [--exclude, black, --keep, isort] + # Formats import order + - repo: https://github.com/pycqa/isort + rev: 5.12.0 + hooks: + - id: isort + name: isort (python) + args: ["--profile", "black", "--filter-files"] + + #Code formatter for both python files and jupyter notebooks + - repo: https://github.com/astral-sh/ruff-pre-commit + # Ruff version. + rev: v0.15.16 + hooks: + # Run the formatter. + - id: ruff-format + + - repo: https://github.com/nbQA-dev/nbQA + rev: 1.9.1 + hooks: + - id: nbqa-isort + additional_dependencies: [isort==5.6.4] + args: [--profile=black] + + - repo: https://github.com/pre-commit/mirrors-prettier + rev: "v3.1.0" + hooks: + - id: prettier + types_or: [markdown, yaml, json, html, css, python, r] + + - repo: https://github.com/hadialqattan/pycln + rev: v2.6.0 + hooks: + - id: pycln + args: [--config=pyproject.toml] + exclude: | + (?x)^( + 2\.segment_images/scripts/.*\.py$| + 3\.cellprofiling/scripts/.*\.py$ + )$ + # additional hooks found with in the pre-commit lib + - repo: https://github.com/pre-commit/pre-commit-hooks + rev: v6.0.0 + hooks: + - id: trailing-whitespace # removes trailing white spaces + - id: mixed-line-ending # removes mixed end of line + args: + - --fix=lf + + - repo: local + hooks: + - id: shellcheck + name: shellcheck + description: Test shell scripts with shellcheck + entry: shellcheck + language: python + types: [shell] + require_serial: true # shellcheck can detect sourcing this way diff --git a/0.data-download/1.data_downloader.ipynb b/0.data-download/1.data_downloader.ipynb index a30f5f3..6928843 100644 --- a/0.data-download/1.data_downloader.ipynb +++ b/0.data-download/1.data_downloader.ipynb @@ -25,8 +25,9 @@ "source": [ "import pathlib\n", "import urllib.request\n", - "import pandas as pd\n", "from pathlib import Path\n", + "\n", + "import pandas as pd\n", "import pyarrow as pa" ] }, @@ -57,8 +58,8 @@ " \"46489732\": \"Model.csv\",\n", " \"46489063\": \"CRISPRGeneEffect_Uncorrected.csv\",\n", " \"46489021\": \"CRISPRGeneDependency.csv\",\n", - " \"29094531\": \"depmap_gene_meta.tsv\"\n", - " # DepMap, Broad (2024). DepMap 24Q2 Public. Figshare+. Dataset. https://doi.org/10.25452/figshare.plus.25880521.v1\n", + " \"29094531\": \"depmap_gene_meta.tsv\",\n", + " # DepMap, Broad (2024). DepMap 24Q2 Public. Figshare+. Dataset. https://doi.org/10.25452/figshare.plus.25880521.v1\n", "}" ] }, @@ -107,22 +108,22 @@ "metadata": {}, "outputs": [], "source": [ - "#Column name correction for CRISPRGeneEffect\n", + "# Column name correction for CRISPRGeneEffect\n", "df = pd.read_csv(\"../0.data-download/data/CRISPRGeneEffect_Uncorrected.csv\")\n", - "df = df.rename(columns={df.columns[0]:'ModelID'})\n", - "filepath = Path('../0.data-download/data/CRISPRGeneEffect.csv')\n", - "filepath.parent.mkdir(parents=True, exist_ok=True) \n", + "df = df.rename(columns={df.columns[0]: \"ModelID\"})\n", + "filepath = Path(\"../0.data-download/data/CRISPRGeneEffect.csv\")\n", + "filepath.parent.mkdir(parents=True, exist_ok=True)\n", "\n", "df.to_csv(filepath, index=False)" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ - "#Convert to parquet\n", + "# Convert to parquet\n", "# List of CSV files\n", "\n", "data_directory = \"../0.data-download/data/\"\n", @@ -137,22 +138,22 @@ "for csv_file in csv_files:\n", " # Read the CSV file\n", " df = pd.read_csv(csv_file)\n", - " \n", + "\n", " # Define the output Parquet file name\n", - " parquet_file = csv_file.with_suffix('.parquet')\n", - " \n", + " parquet_file = csv_file.with_suffix(\".parquet\")\n", + "\n", " # Save the DataFrame as a Parquet file\n", " df.to_parquet(parquet_file, index=False)\n", "\n", "meta_df = pd.read_csv(metadata_file, sep=\"\\t\")\n", - "meta_parquet = metadata_file.with_suffix('.parquet')\n", + "meta_parquet = metadata_file.with_suffix(\".parquet\")\n", "meta_df.to_parquet(meta_parquet, index=False)" ] } ], "metadata": { "kernelspec": { - "display_name": "base", + "display_name": "abstract_embedding", "language": "python", "name": "python3" }, @@ -166,7 +167,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.5" + "version": "3.11.14" } }, "nbformat": 4, diff --git a/0.data-download/2.construct_gene_dictionary.ipynb b/0.data-download/2.construct_gene_dictionary.ipynb index 972825a..a1795e7 100644 --- a/0.data-download/2.construct_gene_dictionary.ipynb +++ b/0.data-download/2.construct_gene_dictionary.ipynb @@ -35,18 +35,19 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 1, "id": "44a48da1-2987-4778-b38d-75ad13ed4f82", "metadata": {}, "outputs": [], "source": [ "import pathlib\n", + "\n", "import pandas as pd" ] }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 2, "id": "a4994c02-29ed-4c75-b4eb-9f1f67f33bc8", "metadata": {}, "outputs": [], @@ -61,7 +62,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 3, "id": "665885c5-cbfa-445e-a08c-cc00e1f5051f", "metadata": {}, "outputs": [ @@ -281,7 +282,7 @@ "[5 rows x 18444 columns]" ] }, - "execution_count": 31, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -296,7 +297,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 4, "id": "3203bcb5-bfe2-4d7e-8171-b0f94034b47d", "metadata": {}, "outputs": [ @@ -457,7 +458,7 @@ "2 https://www.ncbi.nlm.nih.gov/gene/?term=16 80.0 False " ] }, - "execution_count": 32, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -484,7 +485,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 5, "id": "fd813eb6-a3cd-4d60-84de-b552655c3344", "metadata": {}, "outputs": [ @@ -524,67 +525,66 @@ " \n", " \n", " 0\n", - " 51126\n", - " NAA20 (51126)\n", - " NAA20\n", + " 55957\n", + " LIN37 (55957)\n", + " LIN37\n", " \n", " \n", " 1\n", - " 51550\n", - " CINP (51550)\n", - " CINP\n", + " 79980\n", + " DSN1 (79980)\n", + " DSN1\n", " \n", " \n", " 2\n", - " 56984\n", - " PSMG2 (56984)\n", - " PSMG2\n", + " 5922\n", + " RASA2 (5922)\n", + " RASA2\n", " \n", " \n", " 3\n", - " 9550\n", - " ATP6V1G1 (9550)\n", - " ATP6V1G1\n", + " 4221\n", + " MEN1 (4221)\n", + " MEN1\n", " \n", " \n", " 4\n", - " 79084\n", - " WDR77 (79084)\n", - " WDR77\n", + " 3364\n", + " HUS1 (3364)\n", + " HUS1\n", " \n", " \n", "\n", "" ], "text/plain": [ - " entrezgene Name symbol\n", - "0 51126 NAA20 (51126) NAA20\n", - "1 51550 CINP (51550) CINP\n", - "2 56984 PSMG2 (56984) PSMG2\n", - "3 9550 ATP6V1G1 (9550) ATP6V1G1\n", - "4 79084 WDR77 (79084) WDR77" + " entrezgene Name symbol\n", + "0 55957 LIN37 (55957) LIN37\n", + "1 79980 DSN1 (79980) DSN1\n", + "2 5922 RASA2 (5922) RASA2\n", + "3 4221 MEN1 (4221) MEN1\n", + "4 3364 HUS1 (3364) HUS1" ] }, - "execution_count": 33, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Recode column names to entrez ids from dependency file\n", - "entrez_genes = [x[1].strip(\")\").strip() for x in dependency_df.iloc[:, 1:].columns.str.split(\"(\")]\n", + "entrez_genes = [\n", + " x[1].strip(\")\").strip() for x in dependency_df.iloc[:, 1:].columns.str.split(\"(\")\n", + "]\n", "\n", "# Obtain intersection of entrez gene ids\n", - "entrez_intersection = list(\n", - " set(gene_meta_df.entrezgene).intersection(set(entrez_genes))\n", - ")\n", + "entrez_intersection = list(set(gene_meta_df.entrezgene).intersection(set(entrez_genes)))\n", "\n", "print(f\"The number of overlapping entrez gene ids: {len(entrez_intersection)}\")\n", "\n", "# Subset the gene metadata file to only those in common, which are ones that passed qc\n", "gene_passed_qc_df = (\n", - " gene_meta_df\n", - " .query(\"entrezgene in @entrez_intersection\")\n", + " gene_meta_df.query(\"entrezgene in @entrez_intersection\")\n", " .set_index(\"entrezgene\")\n", " .reindex(entrez_intersection)\n", " .reset_index()\n", @@ -609,7 +609,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 6, "id": "c5eff9ef-a686-4c28-9968-19dffcc7f9f3", "metadata": {}, "outputs": [ @@ -690,21 +690,19 @@ "4 127550 A3GALT2 A3GALT2 (127550)" ] }, - "execution_count": 34, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "entrez_genes = [x[1].strip(\")\").strip() for x in dependency_df.iloc[:, 1:].columns.str.split(\"(\")]\n", - "symbol_genes = [x[0].strip() for x in dependency_df.iloc[:,1:].columns.str.split(\"(\")]\n", + "entrez_genes = [\n", + " x[1].strip(\")\").strip() for x in dependency_df.iloc[:, 1:].columns.str.split(\"(\")\n", + "]\n", + "symbol_genes = [x[0].strip() for x in dependency_df.iloc[:, 1:].columns.str.split(\"(\")]\n", "\n", "gene_dictionary_df = pd.DataFrame(\n", - " [\n", - " entrez_genes,\n", - " symbol_genes,\n", - " dependency_df.iloc[:,1:].columns.tolist()\n", - " ]\n", + " [entrez_genes, symbol_genes, dependency_df.iloc[:, 1:].columns.tolist()]\n", ").transpose()\n", "\n", "gene_dictionary_df.columns = [\"entrez_id\", \"symbol_id\", \"dependency_column\"]\n", @@ -724,7 +722,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 7, "id": "88749f9d-99b9-461a-9998-5f17fd55ab71", "metadata": {}, "outputs": [], @@ -735,7 +733,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 8, "id": "171b6309-9d4e-4f54-a4e6-0c85cdc83b12", "metadata": {}, "outputs": [ @@ -818,7 +816,7 @@ "2 2 A2M A2M (2) False True False" ] }, - "execution_count": 36, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -830,7 +828,7 @@ " gene_passed_qc_df,\n", " left_on=\"entrez_id\",\n", " right_on=\"entrezgene\",\n", - " how=\"left\" # Note the left merge, to retain all genes from gene_dictionary_df\n", + " how=\"left\", # Note the left merge, to retain all genes from gene_dictionary_df\n", " )\n", " # Select only certain columns\n", " .loc[:, [\"entrez_id\", \"symbol_id\", \"dependency_column\", \"entrezgene\"]]\n", @@ -841,20 +839,18 @@ ")\n", "\n", "# Convert genes with entrez entries to those that indicate QC pass\n", - "gene_dictionary_qc_df.loc[gene_dictionary_qc_df.qc_pass_pan != False, \"qc_pass_pan\"] = True\n", + "gene_dictionary_qc_df.loc[gene_dictionary_qc_df.qc_pass_pan != False, \"qc_pass_pan\"] = (\n", + " True\n", + ")\n", "\n", "# Create the qc_pass_other column\n", - "gene_dictionary_qc_df = (\n", - " gene_dictionary_qc_df.assign(\n", - " qc_pass_other=~gene_dictionary_qc_df.symbol_id.str.contains(qc_fail_other_genes)\n", - " )\n", + "gene_dictionary_qc_df = gene_dictionary_qc_df.assign(\n", + " qc_pass_other=~gene_dictionary_qc_df.symbol_id.str.contains(qc_fail_other_genes)\n", ")\n", "\n", "# Create qc_pass summary column\n", - "gene_dictionary_qc_df = (\n", - " gene_dictionary_qc_df.assign(\n", - " qc_pass=(gene_dictionary_qc_df.qc_pass_pan & gene_dictionary_qc_df.qc_pass_other)\n", - " )\n", + "gene_dictionary_qc_df = gene_dictionary_qc_df.assign(\n", + " qc_pass=(gene_dictionary_qc_df.qc_pass_pan & gene_dictionary_qc_df.qc_pass_other)\n", ")\n", "\n", "# Output file\n", @@ -869,7 +865,7 @@ ], "metadata": { "kernelspec": { - "display_name": "gene_dependency_representations", + "display_name": "abstract_embedding", "language": "python", "name": "python3" }, @@ -883,7 +879,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.4" + "version": "3.11.14" } }, "nbformat": 4, diff --git a/0.data-download/download_data.sh b/0.data-download/download_data.sh new file mode 100644 index 0000000..b20f058 --- /dev/null +++ b/0.data-download/download_data.sh @@ -0,0 +1,18 @@ +#!/bin/bash + +# shellcheck disable=SC2035 +jupyter nbconvert --to=script --FilesWriter.build_directory=scripts/ *.ipynb + +# check if the data are present +# if not then run the download scripts +# if data are present then skip the download scripts +if [ ! -f "data/metadata_df.parquet" ] || [ ! -f "data/Model.parquet" ]; then + echo "Data files not found. Running data download scripts..." + + uv run python scripts/1.data_downloader.py + uv run python scripts/2.construct_gene_dictionary.py + + echo "Data download and processing complete." +else + echo "Data files already exist. 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load_train_test_data" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(1150, 18444)\n" + ] + } + ], + "source": [ + "# Load dependency data\n", + "data_directory = pathlib.Path(\"../0.data-download/data\").resolve()\n", + "dependency_file = pathlib.Path(f\"{data_directory}/CRISPRGeneEffect.parquet\").resolve()\n", + "gene_dict_file = pathlib.Path(\n", + " f\"{data_directory}/CRISPR_gene_dictionary.parquet\"\n", + ").resolve()\n", + "dependency_df, gene_dict_df = load_model_data(dependency_file, gene_dict_file)\n", + "dependency_df = dependency_df.set_index(\"ModelID\")" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "cancer_type_input_file = pathlib.Path(\"../0.data-download/data/Model.parquet\")\n", + "cancer_type_df = pd.read_parquet(cancer_type_input_file)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "combined_df = dependency_df.merge(\n", + " cancer_type_df[[\"ModelID\", \"OncotreePrimaryDisease\"]], on=\"ModelID\", how=\"left\"\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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    1ACH-0000040.228512-0.397136-1.409154-0.397439-0.123994-1.725931-0.618666-0.9321080.082256...-0.704149-0.478794-0.145720-1.303979-0.278718-0.679133-2.612545-0.043210-0.365718Acute Myeloid Leukemia
    2ACH-0000050.070309-0.208097-0.782796-0.263901-0.050738-1.951187-0.093201-1.1870580.007900...-0.175668-0.986281-0.020722-1.336103-0.031358-0.560265-2.4344070.212494-0.278459Acute Myeloid Leukemia
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    4ACH-000009-0.153007-0.310527-1.297714-0.100032-0.394965-1.853329-0.362086-1.465030-0.098795...-0.396564-0.585670-0.085462-2.150424-0.038581-0.495035-1.4499620.092776-0.161901Colorectal Adenocarcinoma
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colorsys\n", + "import random\n", + "\n", + "\n", + "def generate_random_palette(num_colors, seed=12):\n", + " # Generate random colors with varied lightness and saturation\n", + " random.seed(seed)\n", + "\n", + " colors = []\n", + "\n", + " for _ in range(num_colors):\n", + " h = random.random() # Random hue between 0 and 1\n", + " l = random.uniform(0.2, 0.8) # Lightness between 0.3 and 0.9 for contrast\n", + " s = random.uniform(0.5, 1.0) # Saturation between 0.6 and 1.0 for vivid colors\n", + " color = colorsys.hls_to_rgb(h, l, s) # Convert HLS to RGB color\n", + " colors.append(color)\n", + "\n", + " return colors" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.plotly.v1+json": { + "config": { + "plotlyServerURL": "https://plot.ly" + }, + "data": [ + { + "hoverinfo": "text", + "marker": { + "color": "#636EFA", + "size": 7 + }, + "mode": "markers", + "name": "Ovarian Epithelial Tumor", + "text": [ + "Ovarian Epithelial Tumor | ACH-000001", + "Ovarian Epithelial Tumor | ACH-000013", + "Ovarian Epithelial Tumor | ACH-000048", + "Ovarian Epithelial Tumor | ACH-000103", + "Ovarian Epithelial Tumor | ACH-000116", + "Ovarian Epithelial Tumor | ACH-000123", + "Ovarian Epithelial Tumor | ACH-000132", + "Ovarian Epithelial Tumor | ACH-000237", + "Ovarian Epithelial Tumor | ACH-000256", + "Ovarian Epithelial Tumor | ACH-000278", + "Ovarian Epithelial Tumor | ACH-000280", + "Ovarian Epithelial Tumor | ACH-000291", + "Ovarian Epithelial Tumor | ACH-000308", + "Ovarian Epithelial Tumor | ACH-000324", + "Ovarian Epithelial Tumor | ACH-000430", + "Ovarian Epithelial Tumor | ACH-000460", + "Ovarian Epithelial Tumor | ACH-000520", + "Ovarian Epithelial Tumor | ACH-000524", + "Ovarian Epithelial Tumor | ACH-000527", + "Ovarian Epithelial Tumor | ACH-000542", + "Ovarian Epithelial Tumor | ACH-000584", + "Ovarian Epithelial Tumor | ACH-000608", + "Ovarian Epithelial Tumor | ACH-000646", + "Ovarian Epithelial Tumor | ACH-000657", + "Ovarian Epithelial Tumor | ACH-000663", + "Ovarian Epithelial Tumor | ACH-000688", + "Ovarian Epithelial Tumor | ACH-000696", + "Ovarian Epithelial Tumor | ACH-000701", + "Ovarian Epithelial Tumor | ACH-000704", + "Ovarian Epithelial Tumor | ACH-000713", + "Ovarian Epithelial Tumor | ACH-000719", + "Ovarian Epithelial Tumor | ACH-000796", + "Ovarian Epithelial Tumor | ACH-000811", + "Ovarian Epithelial Tumor | ACH-000885", + "Ovarian Epithelial Tumor | ACH-000906", + "Ovarian Epithelial Tumor | ACH-000936", + "Ovarian Epithelial Tumor | ACH-000947", + "Ovarian Epithelial Tumor | ACH-000962", + "Ovarian Epithelial Tumor | ACH-000966", + "Ovarian Epithelial Tumor | ACH-001048", + "Ovarian Epithelial Tumor | ACH-001063", + "Ovarian Epithelial Tumor | ACH-001145", + "Ovarian Epithelial Tumor | ACH-001151", + "Ovarian Epithelial Tumor | ACH-001278", + "Ovarian Epithelial Tumor | ACH-001279", + "Ovarian Epithelial Tumor | ACH-001340", + "Ovarian Epithelial Tumor | ACH-001370", + "Ovarian Epithelial Tumor | ACH-001403", + "Ovarian Epithelial Tumor | ACH-001418", + "Ovarian Epithelial Tumor | ACH-001628", + "Ovarian Epithelial Tumor | ACH-001630", + "Ovarian Epithelial Tumor | ACH-001632", + "Ovarian Epithelial Tumor | ACH-001719", + "Ovarian Epithelial Tumor | ACH-001991", + "Ovarian Epithelial Tumor | ACH-002140", + "Ovarian Epithelial Tumor | ACH-002181", + "Ovarian Epithelial Tumor | ACH-002183", + "Ovarian Epithelial Tumor | ACH-002486", + "Ovarian Epithelial Tumor | ACH-002524" + ], + "type": "scatter", + "x": [ + 3.0309908218654065, + -0.6451330075414331, + -5.083336194271603, + 3.5501342155382747, + 1.2761951845240291, + -4.2168917744847105, + 1.2208674505264685, + 4.743704058920847, + 3.645265085276565, + 5.3927939548802355, + -0.17458554447799873, + 1.109578612850182, + 5.19861859404294, + -0.9380287199461492, + -4.317228187345513, + -1.9085663724207853, + 1.8912339629311985, + 6.421946990041236, + -0.41849604585415023, + 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Carcinoma | ACH-000547", + "Bladder Urothelial Carcinoma | ACH-000593", + "Bladder Urothelial Carcinoma | ACH-000720", + "Bladder Urothelial Carcinoma | ACH-000724", + "Bladder Urothelial Carcinoma | ACH-000741", + "Bladder Urothelial Carcinoma | ACH-000753", + "Bladder Urothelial Carcinoma | ACH-000802", + "Bladder Urothelial Carcinoma | ACH-000834", + "Bladder Urothelial Carcinoma | ACH-000862", + "Bladder Urothelial Carcinoma | ACH-000896", + "Bladder Urothelial Carcinoma | ACH-000905", + "Bladder Urothelial Carcinoma | ACH-001183", + "Bladder Urothelial Carcinoma | ACH-001407", + "Bladder Urothelial Carcinoma | ACH-001409", + "Bladder Urothelial Carcinoma | ACH-001412", + "Bladder Urothelial Carcinoma | ACH-001413", + "Bladder Urothelial Carcinoma | ACH-001414", + "Bladder Urothelial Carcinoma | ACH-001415", + "Bladder Urothelial Carcinoma | ACH-001416" + ], + "type": "scatter", + "x": [ + 0.31495373306606067, + 0.711451453353316, + -0.007188566788073693, + -4.653102243282732, + 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ACH-000311", + "Non-Small Cell Lung Cancer | ACH-000337", + "Non-Small Cell Lung Cancer | ACH-000339", + "Non-Small Cell Lung Cancer | ACH-000343", + "Non-Small Cell Lung Cancer | ACH-000378", + "Non-Small Cell Lung Cancer | ACH-000390", + "Non-Small Cell Lung Cancer | ACH-000395", + "Non-Small Cell Lung Cancer | ACH-000414", + "Non-Small Cell Lung Cancer | ACH-000416", + "Non-Small Cell Lung Cancer | ACH-000434", + "Non-Small Cell Lung Cancer | ACH-000438", + "Non-Small Cell Lung Cancer | ACH-000442", + "Non-Small Cell Lung Cancer | ACH-000444", + "Non-Small Cell Lung Cancer | ACH-000448", + "Non-Small Cell Lung Cancer | ACH-000454", + "Non-Small Cell Lung Cancer | ACH-000463", + "Non-Small Cell Lung Cancer | ACH-000481", + "Non-Small Cell Lung Cancer | ACH-000496", + "Non-Small Cell Lung Cancer | ACH-000510", + "Non-Small Cell Lung Cancer | ACH-000511", + "Non-Small Cell Lung Cancer | ACH-000521", + "Non-Small Cell Lung Cancer | ACH-000528", + "Non-Small Cell Lung Cancer | ACH-000562", + "Non-Small Cell Lung Cancer | ACH-000563", + "Non-Small Cell Lung Cancer | ACH-000585", + "Non-Small Cell Lung Cancer | ACH-000587", + "Non-Small Cell Lung Cancer | ACH-000589", + "Non-Small Cell Lung Cancer | ACH-000596", + "Non-Small Cell Lung Cancer | ACH-000627", + "Non-Small Cell Lung Cancer | ACH-000638", + "Non-Small Cell Lung Cancer | ACH-000662", + "Non-Small Cell Lung Cancer | ACH-000665", + "Non-Small Cell Lung Cancer | ACH-000666", + "Non-Small Cell Lung Cancer | ACH-000667", + "Non-Small Cell Lung Cancer | ACH-000672", + "Non-Small Cell Lung Cancer | ACH-000677", + "Non-Small Cell Lung Cancer | ACH-000681", + "Non-Small Cell Lung Cancer | ACH-000700", + "Non-Small Cell Lung Cancer | ACH-000706", + "Non-Small Cell Lung Cancer | ACH-000718", + "Non-Small Cell Lung Cancer | ACH-000747", + "Non-Small Cell Lung Cancer | ACH-000757", + "Non-Small Cell Lung Cancer | ACH-000766", + "Non-Small Cell Lung Cancer | ACH-000769", + "Non-Small Cell Lung Cancer | ACH-000774", + "Non-Small Cell Lung Cancer | ACH-000781", + "Non-Small Cell Lung Cancer | ACH-000785", + "Non-Small Cell Lung Cancer | ACH-000787", + "Non-Small Cell Lung Cancer | ACH-000791", + "Non-Small Cell Lung Cancer | ACH-000826", + "Non-Small Cell Lung Cancer | ACH-000837", + "Non-Small Cell Lung Cancer | ACH-000840", + "Non-Small Cell Lung Cancer | ACH-000841", + "Non-Small Cell Lung Cancer | ACH-000843", + "Non-Small Cell Lung Cancer | ACH-000845", + "Non-Small Cell Lung Cancer | ACH-000851", + "Non-Small Cell Lung Cancer | ACH-000853", + "Non-Small Cell Lung Cancer | ACH-000858", + "Non-Small Cell Lung Cancer | ACH-000860", + "Non-Small Cell Lung Cancer | ACH-000861", + "Non-Small Cell Lung Cancer | ACH-000867", + "Non-Small Cell Lung Cancer | ACH-000869", + "Non-Small Cell Lung Cancer | ACH-000872", + "Non-Small Cell Lung Cancer | ACH-000878", + "Non-Small Cell Lung Cancer | ACH-000886", + "Non-Small Cell Lung Cancer | ACH-000888", + "Non-Small Cell Lung Cancer | 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Neoplasms | ACH-000653", + "Mature B-Cell Neoplasms | ACH-000654", + "Mature B-Cell Neoplasms | ACH-000656", + "Mature B-Cell Neoplasms | ACH-000660", + "Mature B-Cell Neoplasms | ACH-000697", + "Mature B-Cell Neoplasms | ACH-000714", + "Mature B-Cell Neoplasms | ACH-000763", + "Mature B-Cell Neoplasms | ACH-000817", + "Mature B-Cell Neoplasms | ACH-000821", + "Mature B-Cell Neoplasms | ACH-000829", + "Mature B-Cell Neoplasms | ACH-000838", + "Mature B-Cell Neoplasms | ACH-000889", + "Mature B-Cell Neoplasms | ACH-000914", + "Mature B-Cell Neoplasms | ACH-000944", + "Mature B-Cell Neoplasms | ACH-001450", + "Mature B-Cell Neoplasms | ACH-001498", + "Mature B-Cell Neoplasms | ACH-001533", + "Mature B-Cell Neoplasms | ACH-001539", + "Mature B-Cell Neoplasms | ACH-001616", + "Mature B-Cell Neoplasms | ACH-001634", + "Mature B-Cell Neoplasms | ACH-001639", + "Mature B-Cell Neoplasms | ACH-001677", + "Mature B-Cell Neoplasms | ACH-001707", + "Mature B-Cell Neoplasms | ACH-001709", + "Mature B-Cell Neoplasms | ACH-002055", + "Mature B-Cell Neoplasms | ACH-002062", + "Mature B-Cell Neoplasms | ACH-002214", + "Mature B-Cell Neoplasms | ACH-002215", + "Mature B-Cell Neoplasms | ACH-002478", + "Mature B-Cell Neoplasms | ACH-002485", + "Mature B-Cell Neoplasms | ACH-002500", + "Mature B-Cell Neoplasms | ACH-002677", + "Mature B-Cell Neoplasms | ACH-002678" + ], + "type": "scatter", + "x": [ + -4.230036041497958, + -0.9599514789862148, + -9.960450870559855, + -2.137675082320434, + -7.099694653702987, + -5.781743133236115, + -12.28254712641251, + -2.197767908201214, + 3.4836440400691147, + -4.865258956688968, + 1.7132806653617692, + -7.236550672818914, + -4.005304079113779, + -3.0919391988380127, + -2.055718416576532, + -6.009279677564389, + 0.6588113809970629, + -0.9473905053938274, + -3.13679002708559, + -0.7465826121156746, + -5.8279681320291745, + -0.10377771158024245, + -6.210951581011847, + -2.659048683129515, + -2.711957056646598, + -11.616373203942327, + 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ACH-000244", + "Diffuse Glioma | ACH-000269", + "Diffuse Glioma | ACH-000273", + "Diffuse Glioma | ACH-000323", + "Diffuse Glioma | ACH-000329", + "Diffuse Glioma | ACH-000368", + "Diffuse Glioma | ACH-000370", + "Diffuse Glioma | ACH-000376", + "Diffuse Glioma | ACH-000389", + "Diffuse Glioma | ACH-000437", + "Diffuse Glioma | ACH-000445", + "Diffuse Glioma | ACH-000455", + "Diffuse Glioma | ACH-000464", + "Diffuse Glioma | ACH-000469", + "Diffuse Glioma | ACH-000479", + "Diffuse Glioma | ACH-000504", + "Diffuse Glioma | ACH-000558", + "Diffuse Glioma | ACH-000570", + "Diffuse Glioma | ACH-000571", + "Diffuse Glioma | ACH-000591", + "Diffuse Glioma | ACH-000592", + "Diffuse Glioma | ACH-000595", + "Diffuse Glioma | ACH-000609", + "Diffuse Glioma | ACH-000622", + "Diffuse Glioma | ACH-000623", + "Diffuse Glioma | ACH-000631", + "Diffuse Glioma | ACH-000634", + "Diffuse Glioma | ACH-000655", + "Diffuse Glioma | ACH-000673", + "Diffuse Glioma | ACH-000676", + "Diffuse Glioma | 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ACH-002106", + "Ewing Sarcoma | ACH-002109", + "Ewing Sarcoma | ACH-002110", + "Ewing Sarcoma | ACH-002114", + "Ewing Sarcoma | ACH-002116", + "Ewing Sarcoma | ACH-002119", + "Ewing Sarcoma | ACH-002160" + ], + "type": "scatter", + "x": [ + 2.805551538089792, + 1.6077887363737997, + 1.6054610001472154, + -2.099417191776415, + 0.5887355902928044, + -4.1197545603396, + -4.424777942235254, + -6.6382016656072205, + -2.341289744352628, + -4.891226127631078, + -2.2671837503300214, + -0.7379506146575147, + 0.3095626933930831, + -0.23972492953299265, + -1.1956662327219354, + 0.44303945328310235, + -1.513434553586227, + 0.4746926656543402, + -5.4087107528798795, + -1.0184925046161886, + -7.61920687468574, + -2.112269040906147, + 0.7768589726235391, + -5.612466491500805, + -5.690207085516707 + ], + "y": [ + 0.14074071985207204, + -0.627048170762642, + 2.654817236851029, + 0.03932386119461592, + -0.8445088828314018, + -0.13586128167103734, + 5.195075901821137, + 5.163382780696362, + 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Adenocarcinoma | ACH-000356", + "Esophagogastric Adenocarcinoma | ACH-000383", + "Esophagogastric Adenocarcinoma | ACH-000427", + "Esophagogastric Adenocarcinoma | ACH-000466", + "Esophagogastric Adenocarcinoma | ACH-000485", + "Esophagogastric Adenocarcinoma | ACH-000507", + "Esophagogastric Adenocarcinoma | ACH-000581", + "Esophagogastric Adenocarcinoma | ACH-000616", + "Esophagogastric Adenocarcinoma | ACH-000633", + "Esophagogastric Adenocarcinoma | ACH-000736", + "Esophagogastric Adenocarcinoma | ACH-000746", + "Esophagogastric Adenocarcinoma | ACH-000758", + "Esophagogastric Adenocarcinoma | ACH-000764", + "Esophagogastric Adenocarcinoma | ACH-000793", + "Esophagogastric Adenocarcinoma | ACH-000847", + "Esophagogastric Adenocarcinoma | ACH-000880", + "Esophagogastric Adenocarcinoma | ACH-000898", + "Esophagogastric Adenocarcinoma | ACH-000911", + "Esophagogastric Adenocarcinoma | ACH-000919", + "Esophagogastric Adenocarcinoma | ACH-000932", + "Esophagogastric Adenocarcinoma | ACH-000948", + "Esophagogastric Adenocarcinoma | ACH-001368", + "Esophagogastric Adenocarcinoma | ACH-001496", + "Esophagogastric Adenocarcinoma | ACH-001497", + "Esophagogastric Adenocarcinoma | ACH-001500", + "Esophagogastric Adenocarcinoma | ACH-001544", + "Esophagogastric Adenocarcinoma | ACH-001653", + "Esophagogastric Adenocarcinoma | ACH-001654", + "Esophagogastric Adenocarcinoma | ACH-001664", + "Esophagogastric Adenocarcinoma | ACH-002141", + "Esophagogastric Adenocarcinoma | ACH-002161", + "Esophagogastric Adenocarcinoma | ACH-002202", + "Esophagogastric Adenocarcinoma | ACH-002446", + "Esophagogastric Adenocarcinoma | ACH-002705", + "Esophagogastric Adenocarcinoma | ACH-002706" + ], + "type": "scatter", + "x": [ + -4.162764787605665, + 8.797004721880963, + -0.8355828331646905, + 1.6733375074106704, + -2.6269941085749107, + 0.324125484967366, + -1.0386285488971287, + -3.167319375828302, + 0.8293499524287758, + -0.05959084354024104, + 1.2226371479776177, + 3.460471563584129, + 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"Mature T and NK Neoplasms | ACH-000233", + "Mature T and NK Neoplasms | ACH-000338", + "Mature T and NK Neoplasms | ACH-000664", + "Mature T and NK Neoplasms | ACH-000773", + "Mature T and NK Neoplasms | ACH-001111", + "Mature T and NK Neoplasms | ACH-001119", + "Mature T and NK Neoplasms | ACH-001737" + ], + "type": "scatter", + "x": [ + -1.365273495298985, + -6.680184014408566, + -4.137199405379333, + -3.3502161094892533, + 0.1694901486019222, + -8.81683843923116, + -2.1667082207155905, + -1.067589288386224, + 3.728737340608749, + -1.1560587308933248 + ], + "y": [ + -4.470268730419931, + -3.2854862045859745, + -2.7318245093914992, + -2.1506923170802468, + -0.8452303937890703, + -3.1490553648582025, + -2.632643659704652, + -1.8773570845052092, + -2.809249396623952, + 0.4729065309946081 + ] + }, + { + "hoverinfo": "text", + "marker": { + "color": "#0DF9FF", + "size": 7 + }, + "mode": "markers", + "name": "Fibrosarcoma", + "text": [ + "Fibrosarcoma | ACH-000054" + ], + "type": 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"B-Lymphoblastic Leukemia/Lymphoma | ACH-001520", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001669", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001735", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001736", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001993", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-002059" + ], + "type": "scatter", + "x": [ + -4.931532844451203, + -1.5261081901450173, + -4.044715422301275, + -7.189805443963426, + -6.1879418047347885, + -5.532456647320777, + -3.513456846380123, + -5.265135006820562, + -7.389462888136302, + -3.987913437079184, + -7.806641379165343, + -2.025036101132089, + -4.113893913070926 + ], + "y": [ + -3.6033673727354807, + -4.492603101716206, + -4.148930925796432, + -4.233592238363938, + -5.330928627967554, + -3.9254086131938215, + -3.043699511707792, + -2.969548398734912, + -3.868882129378096, + -4.859483532259131, + -4.431291613321818, + -3.8378473558032544, + -2.4082557700792018 + ] + }, + { + "hoverinfo": "text", + "marker": { + "color": 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ACH-000260", + "Neuroblastoma | ACH-000310", + "Neuroblastoma | ACH-000312", + "Neuroblastoma | ACH-000341", + "Neuroblastoma | ACH-000366", + "Neuroblastoma | ACH-000804", + "Neuroblastoma | ACH-001188", + "Neuroblastoma | ACH-001300", + "Neuroblastoma | ACH-001301", + "Neuroblastoma | ACH-001302", + "Neuroblastoma | ACH-001303", + "Neuroblastoma | ACH-001338", + "Neuroblastoma | ACH-001344", + "Neuroblastoma | ACH-001354", + "Neuroblastoma | ACH-001366", + "Neuroblastoma | ACH-001367", + "Neuroblastoma | ACH-001481", + "Neuroblastoma | ACH-001548", + "Neuroblastoma | ACH-001603", + "Neuroblastoma | ACH-001674", + "Neuroblastoma | ACH-002080", + "Neuroblastoma | ACH-002083", + "Neuroblastoma | ACH-002261", + "Neuroblastoma | ACH-002278", + "Neuroblastoma | ACH-002280", + "Neuroblastoma | ACH-002282", + "Neuroblastoma | ACH-002283", + "Neuroblastoma | ACH-002284", + "Neuroblastoma | ACH-002285", + "Neuroblastoma | ACH-002922" + ], + "type": "scatter", + "x": [ + 0.4082600987518737, + 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ACH-001526", + "Osteosarcoma | ACH-001715", + "Osteosarcoma | ACH-001814", + "Osteosarcoma | ACH-002067", + "Osteosarcoma | ACH-002069", + "Osteosarcoma | ACH-002471", + "Osteosarcoma | ACH-002834" + ], + "type": "scatter", + "x": [ + 8.014923561203458, + 6.284509701537909, + -0.43454096760301586, + 0.8119298677187917, + -1.0615631808335872, + -4.675659223815148, + 4.404676264315412, + 5.30096276057464, + 5.577338889951733, + 0.2865527944622839, + 2.12701398967933, + 2.118003628425808, + 4.058798894934358 + ], + "y": [ + 0.7800213503892617, + 0.7780897386847487, + 4.289024944209753, + 2.2733848547628264, + 7.609428468998928, + 0.39451930971655513, + 1.012108758224338, + 1.0921025936647153, + 2.530615631210353, + 0.781181084507878, + 4.344335557262799, + 1.964264681012564, + 4.650823873605171 + ] + }, + { + "hoverinfo": "text", + "marker": { + "color": "#6E899C", + "size": 7 + }, + "mode": "markers", + "name": "Pleural Mesothelioma", + "text": [ + "Pleural Mesothelioma | ACH-000086", + 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ACH-000537", + "Hepatocellular Carcinoma | ACH-000577", + "Hepatocellular Carcinoma | ACH-000620", + "Hepatocellular Carcinoma | ACH-000734", + "Hepatocellular Carcinoma | ACH-000848", + "Hepatocellular Carcinoma | ACH-001318", + "Hepatocellular Carcinoma | ACH-002523" + ], + "type": "scatter", + "x": [ + -0.6685294794990254, + -4.237655728033159, + 1.1803030417493352, + 0.7250847923953324, + 7.021664633004289, + 4.801358842905883, + -0.2529436079129108, + 1.152013724613071, + -1.5123394595522917, + 4.171117819389476, + 3.618223896178974, + -2.1737537546761136, + 5.810151326500753, + 1.916473336546264, + 0.48462414667644105, + 7.938762576200405, + -0.13625740270133807, + -3.426459658498924, + -3.278805608794943, + -0.6412529046710205, + 0.15586570671873198 + ], + "y": [ + -0.4301994334964398, + 0.23598193333607964, + 5.472126015348956, + 1.701514567840574, + 2.1613950974185454, + 1.918919918874581, + 5.822352688347071, + 3.2319227729584004, + 0.5571342056851746, + -1.1488029770453685, 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"label": "Salivary Carcinoma", + "method": "update" + } + ], + "direction": "down", + "showactive": true, + "x": 1.15, + "xanchor": "left", + "y": 1.15, + "yanchor": "top" + } + ], + "width": 1500, + "xaxis": { + "title": { + "text": "PCA1" + } + }, + "yaxis": { + "title": { + "text": "PCA2" + } + } + } + } + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import plotly.express as px\n", + "import plotly.graph_objects as go\n", + "from sklearn.decomposition import PCA\n", + "from sklearn.preprocessing import StandardScaler\n", + "\n", + "# Prepare PCA input (excluding non-numeric columns)\n", + "pca_input = combined_df[gene_cols].apply(pd.to_numeric, errors=\"coerce\")\n", + "pca = PCA(n_components=2, random_state=0)\n", + "pca_embedding = pca.fit_transform(pca_input)\n", + "\n", + "# Add PCA components to the dataframe\n", + "combined_df[\"PCA1\"] = pca_embedding[:, 0]\n", + "combined_df[\"PCA2\"] = pca_embedding[:, 1]\n", + "\n", + "# Prepare color map for each cancer type\n", + "cancer_types = combined_df[\"OncotreePrimaryDisease\"].unique()\n", + "color_map = (\n", + " px.colors.qualitative.Plotly\n", + " + px.colors.qualitative.Light24\n", + " + px.colors.qualitative.Dark24\n", + ")\n", + "highlight_color_map = {\n", + " cancer: color_map[i % len(color_map)] for i, cancer in enumerate(cancer_types)\n", + "}\n", + "\n", + "# Create one trace per cancer type\n", + "traces = []\n", + "for cancer in cancer_types:\n", + " df_subset = combined_df[combined_df[\"OncotreePrimaryDisease\"] == cancer]\n", + " trace = go.Scatter(\n", + " x=df_subset[\"PCA1\"],\n", + " y=df_subset[\"PCA2\"],\n", + " mode=\"markers\",\n", + " name=cancer,\n", + " marker=dict(size=7),\n", + " text=[f\"{cancer} | {model_id}\" for model_id in df_subset[\"ModelID\"]],\n", + " hoverinfo=\"text\",\n", + " )\n", + " traces.append(trace)\n", + "\n", + "# Create dropdown buttons\n", + "dropdown_buttons = []\n", + "\n", + "for i, cancer in enumerate(cancer_types):\n", + " # Make all grey except the selected one\n", + " visibility = [True] * len(cancer_types)\n", + " colors = [\"lightgrey\"] * len(cancer_types)\n", + " colors[i] = highlight_color_map[cancer]\n", + "\n", + " button = dict(\n", + " method=\"update\",\n", + " label=cancer,\n", + " args=[\n", + " {\n", + " \"visible\": visibility,\n", + " \"marker\": [{\"color\": colors[j]} for j in range(len(cancer_types))],\n", + " },\n", + " {\"title\": f\"PCA Highlighted: {cancer}\"},\n", + " ],\n", + " )\n", + " dropdown_buttons.append(button)\n", + "\n", + "# Add a button to show all with normal colors\n", + "default_colors = [highlight_color_map[cancer] for cancer in cancer_types]\n", + "dropdown_buttons.insert(\n", + " 0,\n", + " dict(\n", + " method=\"update\",\n", + " label=\"Show All\",\n", + " args=[\n", + " {\n", + " \"visible\": [True] * len(cancer_types),\n", + " \"marker\": [\n", + " {\"color\": default_colors[j]} for j in range(len(cancer_types))\n", + " ],\n", + " },\n", + " {\"title\": \"PCA of DepMap Single Gene Data\"},\n", + " ],\n", + " ),\n", + ")\n", + "\n", + "# Create the figure\n", + "fig = go.Figure(data=traces)\n", + "\n", + "# Set default colors\n", + "for i, trace in enumerate(fig.data):\n", + " trace.marker.color = default_colors[i]\n", + "\n", + "fig.update_layout(\n", + " title=\"PCA of DepMap Single Gene Data\",\n", + " xaxis_title=\"PCA1\",\n", + " yaxis_title=\"PCA2\",\n", + " updatemenus=[\n", + " {\n", + " \"buttons\": dropdown_buttons,\n", + " \"direction\": \"down\",\n", + " \"showactive\": True,\n", + " \"x\": 1.15,\n", + " \"xanchor\": \"left\",\n", + " \"y\": 1.15,\n", + " \"yanchor\": \"top\",\n", + " }\n", + " ],\n", + " width=1500,\n", + " height=800,\n", + ")\n", + "\n", + "fig.show()\n", + "fig.write_html(\"achilles_pca.html\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "gene_dependency_representations_real", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.8" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/9.webapp/1.latent-umaps(1).ipynb b/9.webapp/1.latent-umaps(1).ipynb new file mode 100644 index 0000000..c21af55 --- /dev/null +++ b/9.webapp/1.latent-umaps(1).ipynb @@ -0,0 +1,86709 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import colorsys\n", + "import pathlib\n", + "import random\n", + "\n", + "import ipywidgets as widgets\n", + "import pandas as pd\n", + "import plotly.express as px\n", + "import plotly.graph_objs as go\n", + "from sklearn.decomposition import PCA" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "cancer_type_input_file = pathlib.Path(\"../0.data-download/data/Model.parquet\")\n", + "cancer_type_df = pd.read_parquet(cancer_type_input_file)\n", + "\n", + "reactome_dims = pathlib.Path(\n", + " \"../5.drug-dependency/results/all_reactome_results.parquet\"\n", + ")\n", + "reactome_df = pd.read_parquet(reactome_dims)\n", + "\n", + "corum_dims = pathlib.Path(\"../5.drug-dependency/results/all_corum_results.parquet\")\n", + "corum_df = pd.read_parquet(corum_dims)\n", + "\n", + "drug_dims = pathlib.Path(\"../5.drug-dependency/results/all_drug_results.parquet\")\n", + "drug_df = pd.read_parquet(drug_dims)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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    ModelIDmodellatent_dim_totalinitseedOncotreePrimaryDiseasezlatent_scorereactome_pathwaynes_scorepathway_score
    0ACH-000001betatcvae1641154917792Ovarian Epithelial Tumor10.306144Formation Of Incision Complex In GG-NER R-HSA-...3.2473450.306144
    1ACH-000001betatcvae250501796030Ovarian Epithelial Tumor10.657242Citric Acid (TCA) Cycle And Respiratory Electr...inf0.657242
    2ACH-000001betatcvae9001590696690Ovarian Epithelial Tumor10.455570Polymerase Switching On C-strand Of Telomere R...2.9176800.455570
    3ACH-000001betavae534066919116Ovarian Epithelial Tumor10.000000RHOC GTPase Cycle R-HSA-90131063.1494550.000000
    4ACH-000001betavae1021507182516Ovarian Epithelial Tumor10.159076Nephrin Family Interactions R-HSA-3737532.5826870.159076
    \n", + "
    " + ], + "text/plain": [ + " ModelID model latent_dim_total init seed \\\n", + "0 ACH-000001 betatcvae 16 4 1154917792 \n", + "1 ACH-000001 betatcvae 25 0 501796030 \n", + "2 ACH-000001 betatcvae 90 0 1590696690 \n", + "3 ACH-000001 betavae 5 3 4066919116 \n", + "4 ACH-000001 betavae 10 2 1507182516 \n", + "\n", + " OncotreePrimaryDisease z latent_score \\\n", + "0 Ovarian Epithelial Tumor 1 0.306144 \n", + "1 Ovarian Epithelial Tumor 1 0.657242 \n", + "2 Ovarian Epithelial Tumor 1 0.455570 \n", + "3 Ovarian Epithelial Tumor 1 0.000000 \n", + "4 Ovarian Epithelial Tumor 1 0.159076 \n", + "\n", + " reactome_pathway nes_score pathway_score \n", + "0 Formation Of Incision Complex In GG-NER R-HSA-... 3.247345 0.306144 \n", + "1 Citric Acid (TCA) Cycle And Respiratory Electr... inf 0.657242 \n", + "2 Polymerase Switching On C-strand Of Telomere R... 2.917680 0.455570 \n", + "3 RHOC GTPase Cycle R-HSA-9013106 3.149455 0.000000 \n", + "4 Nephrin Family Interactions R-HSA-373753 2.582687 0.159076 " + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "reactome_df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "# Step 2: Subset based on matching keys\n", + "subset_keys = [\"model\", \"latent_dim_total\", \"init\", \"z\"]\n", + "\n", + "# Replace latent identifiers with pathway\n", + "reactome_df[\"feature\"] = reactome_df[\"reactome_pathway\"]\n", + "reactome_df = reactome_df.drop(\n", + " columns=[\"model\", \"latent_dim_total\", \"init\", \"seed\", \"z\", \"reactome_pathway\"]\n", + ")\n", + "\n", + "corum_df[\"feature\"] = corum_df[\"reactome_pathway\"]\n", + "corum_df = corum_df.drop(\n", + " columns=[\"model\", \"latent_dim_total\", \"init\", \"seed\", \"z\", \"reactome_pathway\"]\n", + ")\n", + "\n", + "drug_df[\"feature\"] = drug_df[\"name\"]\n", + "drug_df = drug_df.drop(\n", + " columns=[\"model\", \"latent_dim_total\", \"init\", \"seed\", \"z\", \"name\"]\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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    ModelIDOncotreePrimaryDiseaselatent_scorepearson_correlationpathway_scorefeature
    597ACH-000004Acute Myeloid Leukemia0.543216-0.2639620.54321610-deacetylbaccatin
    716ACH-000004Acute Myeloid Leukemia0.740212-0.2529450.7402122,3-DCPE
    457ACH-000004Acute Myeloid Leukemia0.832806-0.2753880.8328063-deazaneplanocin-A
    678ACH-000004Acute Myeloid Leukemia0.641957-0.3206670.6419579-aminoacridine
    444ACH-000004Acute Myeloid Leukemia0.546763-0.2626310.546763ACY-1215
    \n", + "
    " + ], + "text/plain": [ + " ModelID OncotreePrimaryDisease latent_score pearson_correlation \\\n", + "597 ACH-000004 Acute Myeloid Leukemia 0.543216 -0.263962 \n", + "716 ACH-000004 Acute Myeloid Leukemia 0.740212 -0.252945 \n", + "457 ACH-000004 Acute Myeloid Leukemia 0.832806 -0.275388 \n", + "678 ACH-000004 Acute Myeloid Leukemia 0.641957 -0.320667 \n", + "444 ACH-000004 Acute Myeloid Leukemia 0.546763 -0.262631 \n", + "\n", + " pathway_score feature \n", + "597 0.543216 10-deacetylbaccatin \n", + "716 0.740212 2,3-DCPE \n", + "457 0.832806 3-deazaneplanocin-A \n", + "678 0.641957 9-aminoacridine \n", + "444 0.546763 ACY-1215 " + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "drug_df_sorted = drug_df.sort_values(\n", + " by=[\"OncotreePrimaryDisease\", \"ModelID\", \"feature\"], ascending=True\n", + ")\n", + "drug_df_sorted.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "# Create a unique column name by combining feature and source\n", + "meta_cols = [\"ModelID\", \"OncotreePrimaryDisease\"]\n", + "reactome_meta = reactome_df[meta_cols].drop_duplicates()\n", + "corum_meta = corum_df[meta_cols].drop_duplicates()\n", + "drug_meta = drug_df[meta_cols].drop_duplicates()\n", + "\n", + "# Pivot to wide format\n", + "reactome_matrix = reactome_df.pivot(\n", + " index=\"ModelID\", columns=\"feature\", values=\"latent_score\"\n", + ")\n", + "corum_matrix = corum_df.pivot(index=\"ModelID\", columns=\"feature\", values=\"latent_score\")\n", + "drug_matrix = drug_df.pivot(index=\"ModelID\", columns=\"feature\", values=\"latent_score\")\n", + "\n", + "# Join metadata back to each matrix\n", + "reactome_matrix = reactome_matrix.merge(reactome_meta, on=\"ModelID\", how=\"left\")\n", + "corum_matrix = corum_matrix.merge(corum_meta, on=\"ModelID\", how=\"left\")\n", + "drug_matrix = drug_matrix.merge(drug_meta, on=\"ModelID\", how=\"left\")" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "def generate_random_palette(num_colors, seed=12):\n", + " # Generate random colors with varied lightness and saturation\n", + " random.seed(seed)\n", + "\n", + " colors = []\n", + "\n", + " for _ in range(num_colors):\n", + " h = random.random() # Random hue between 0 and 1\n", + " l = random.uniform(0.2, 0.8) # Lightness between 0.3 and 0.9 for contrast\n", + " s = random.uniform(0.5, 1.0) # Saturation between 0.6 and 1.0 for vivid colors\n", + " color = colorsys.hls_to_rgb(h, l, s) # Convert HLS to RGB color\n", + " colors.append(color)\n", + "\n", + " return colors" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "def make_dropdown_pca_with_selection(df, title=\"PCA Interactive Plot\"):\n", + " out = widgets.Output() # Create a fresh output for this plot!\n", + "\n", + " # Prepare PCA input\n", + " pca_input = df.drop(\n", + " columns=[\"OncotreePrimaryDisease\", \"source\", \"ModelID\"], errors=\"ignore\"\n", + " ).fillna(0)\n", + " pca = PCA(n_components=2, random_state=0)\n", + " embedding = pca.fit_transform(pca_input)\n", + "\n", + " # Add PCA coordinates to the dataframe\n", + " df[\"PCA1\"] = embedding[:, 0]\n", + " df[\"PCA2\"] = embedding[:, 1]\n", + "\n", + " # Prepare color map for each cancer type\n", + " cancer_types = df[\"OncotreePrimaryDisease\"].unique()\n", + " color_map = (\n", + " px.colors.qualitative.Plotly\n", + " + px.colors.qualitative.Light24\n", + " + px.colors.qualitative.Dark24\n", + " )\n", + " highlight_color_map = {\n", + " cancer: color_map[i % len(color_map)] for i, cancer in enumerate(cancer_types)\n", + " }\n", + "\n", + " # Create one trace per cancer type\n", + " traces = []\n", + " for cancer in cancer_types:\n", + " df_subset = df[df[\"OncotreePrimaryDisease\"] == cancer]\n", + " trace = go.Scattergl(\n", + " x=df_subset[\"PCA1\"],\n", + " y=df_subset[\"PCA2\"],\n", + " mode=\"markers\",\n", + " name=cancer,\n", + " marker=dict(size=7, color=highlight_color_map[cancer]),\n", + " text=[f\"{cancer} | {model_id}\" for model_id in df_subset[\"ModelID\"]],\n", + " customdata=df_subset[\"ModelID\"], # Attach ModelID to customdata\n", + " hoverinfo=\"text\",\n", + " )\n", + " traces.append(trace)\n", + "\n", + " # Dropdown buttons to highlight cancer types\n", + " dropdown_buttons = []\n", + " for i, cancer in enumerate(cancer_types):\n", + " visibility = [True] * len(cancer_types)\n", + " colors = [\"lightgrey\"] * len(cancer_types)\n", + " colors[i] = highlight_color_map[cancer]\n", + "\n", + " button = dict(\n", + " method=\"update\",\n", + " label=cancer,\n", + " args=[\n", + " {\n", + " \"visible\": visibility,\n", + " \"marker\": [{\"color\": colors[j]} for j in range(len(cancer_types))],\n", + " },\n", + " {\"title\": f\"PCA Highlighted: {cancer}\"},\n", + " ],\n", + " )\n", + " dropdown_buttons.append(button)\n", + "\n", + " # Default color button\n", + " default_colors = [highlight_color_map[cancer] for cancer in cancer_types]\n", + " dropdown_buttons.insert(\n", + " 0,\n", + " dict(\n", + " method=\"update\",\n", + " label=\"Show All\",\n", + " args=[\n", + " {\n", + " \"visible\": [True] * len(cancer_types),\n", + " \"marker\": [\n", + " {\"color\": default_colors[j]} for j in range(len(cancer_types))\n", + " ],\n", + " },\n", + " {\"title\": title},\n", + " ],\n", + " ),\n", + " )\n", + "\n", + " fig = go.Figure(data=traces)\n", + "\n", + " for i, trace in enumerate(fig.data):\n", + " trace.marker.color = default_colors[i]\n", + "\n", + " fig.update_layout(\n", + " title=title,\n", + " xaxis_title=\"PCA1\",\n", + " yaxis_title=\"PCA2\",\n", + " updatemenus=[\n", + " {\n", + " \"buttons\": dropdown_buttons,\n", + " \"direction\": \"down\",\n", + " \"showactive\": True,\n", + " \"x\": 1.15,\n", + " \"xanchor\": \"left\",\n", + " \"y\": 1.15,\n", + " \"yanchor\": \"top\",\n", + " }\n", + " ],\n", + " dragmode=\"lasso\", # Ensure Lasso is enabled\n", + " width=1500,\n", + " height=800,\n", + " )\n", + "\n", + " return fig, out # Return both the figure and the output widget for selection" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.plotly.v1+json": { + "config": { + "plotlyServerURL": "https://plot.ly" + }, + "data": [ + { + "customdata": [ + "ACH-000001", + "ACH-000013", + "ACH-000048", + "ACH-000103", + "ACH-000116", + "ACH-000123", + "ACH-000132", + "ACH-000237", + "ACH-000256", + "ACH-000278", + "ACH-000280", + "ACH-000291", + "ACH-000308", + "ACH-000324", + "ACH-000430", + "ACH-000460", + "ACH-000520", + "ACH-000524", + "ACH-000527", + "ACH-000542", + "ACH-000584", + "ACH-000608", + "ACH-000646", + "ACH-000657", + "ACH-000663", + "ACH-000688", + "ACH-000696", + "ACH-000701", + "ACH-000704", + "ACH-000713", + "ACH-000719", + "ACH-000796", + "ACH-000811", + "ACH-000885", + "ACH-000906", 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ACH-000280", + "Ovarian Epithelial Tumor | ACH-000291", + "Ovarian Epithelial Tumor | ACH-000308", + "Ovarian Epithelial Tumor | ACH-000324", + "Ovarian Epithelial Tumor | ACH-000430", + "Ovarian Epithelial Tumor | ACH-000460", + "Ovarian Epithelial Tumor | ACH-000520", + "Ovarian Epithelial Tumor | ACH-000524", + "Ovarian Epithelial Tumor | ACH-000527", + "Ovarian Epithelial Tumor | ACH-000542", + "Ovarian Epithelial Tumor | ACH-000584", + "Ovarian Epithelial Tumor | ACH-000608", + "Ovarian Epithelial Tumor | ACH-000646", + "Ovarian Epithelial Tumor | ACH-000657", + "Ovarian Epithelial Tumor | ACH-000663", + "Ovarian Epithelial Tumor | ACH-000688", + "Ovarian Epithelial Tumor | ACH-000696", + "Ovarian Epithelial Tumor | ACH-000701", + "Ovarian Epithelial Tumor | ACH-000704", + "Ovarian Epithelial Tumor | ACH-000713", + "Ovarian Epithelial Tumor | ACH-000719", + "Ovarian Epithelial Tumor | ACH-000796", + "Ovarian Epithelial Tumor | ACH-000811", + "Ovarian Epithelial Tumor | ACH-000885", + "Ovarian Epithelial Tumor | ACH-000906", + "Ovarian Epithelial Tumor | ACH-000936", + "Ovarian Epithelial Tumor | ACH-000947", + "Ovarian Epithelial Tumor | ACH-000962", + "Ovarian Epithelial Tumor | ACH-000966", + "Ovarian Epithelial Tumor | ACH-001048", + "Ovarian Epithelial Tumor | ACH-001063", + "Ovarian Epithelial Tumor | ACH-001145", + "Ovarian Epithelial Tumor | ACH-001151", + "Ovarian Epithelial Tumor | ACH-001278", + "Ovarian Epithelial Tumor | ACH-001279", + "Ovarian Epithelial Tumor | ACH-001340", + "Ovarian Epithelial Tumor | ACH-001370", + "Ovarian Epithelial Tumor | ACH-001403", + "Ovarian Epithelial Tumor | ACH-001418", + "Ovarian Epithelial Tumor | ACH-001628", + "Ovarian Epithelial Tumor | ACH-001630", + "Ovarian Epithelial Tumor | ACH-001632", + "Ovarian Epithelial Tumor | ACH-001719", + "Ovarian Epithelial Tumor | ACH-001991", + "Ovarian Epithelial Tumor | ACH-002140", + "Ovarian Epithelial Tumor | ACH-002181", + "Ovarian Epithelial Tumor | ACH-002183", + "Ovarian Epithelial Tumor | ACH-002486", + "Ovarian Epithelial Tumor | ACH-002524" + ], + "type": "scattergl", + "x": { + "bdata": "e4r5vXb+GEB3ZKhALgRQvzJvbj+zPJhAjuwfPx0F7r/s1PLAO+TywArKyD9QREE/sscBwMD76j9xNJdAA/IrQO14272HxvLAujMCQKPC8sDw4wNAr9TywI2/H8AMsvLAswDFPnB1pMAiym5AzegdwIiS0D8zZOU+ic/QvkXWZL9RyVPAhGu0QB/Tk0Beduw/74jkQNR3MUCgV+Y/osfywEW/8sDWK0VAzNcXP0e68sDsgZRA/7fywCK+8sAozPLAgK+iP1y98sDew/LAgtrywAni8sDkMKpAqLnywO/O8sAm6PLATQBxQMayjj8=", + "dtype": "f4" + }, + "y": { + "bdata": "up2uvu/orT/bEiK+/2xov8Jb2T8iOVm/OmQPQMi4l0D42aq/Mcuqv5bRO0BrxbA/dRoevryEBEDZ6Rg/b/3WvrOXCUAEdau/7DXjP/k+q7+V/Ba/wHSrv3Pdlj1Qfau/PiokQF6QM0Aafg9AafNoP09yCD+ACR++jcqlP4wGkr6AcEBA0kouP5xabD/5aj+/Y+rsvwkpMz+tetU+H/Sqvz0Jq78g3nw//1PCPxmDq7/vg308a0Krv0Bnq7/5Aau/IhtOv/tfq78i0qq/yraqv6Z5qr/wRQvAUZ2rv4Djqr9FmKq/kqGwP3VBeD4=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000004", + "ACH-000005", + "ACH-000045", + "ACH-000113", + "ACH-000146", + "ACH-000168", + "ACH-000190", + 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Leukemia | ACH-000406", + "Acute Myeloid Leukemia | ACH-000498", + "Acute Myeloid Leukemia | ACH-000557", + "Acute Myeloid Leukemia | ACH-000602", + "Acute Myeloid Leukemia | ACH-000770", + "Acute Myeloid Leukemia | ACH-001036", + "Acute Myeloid Leukemia | ACH-001129", + "Acute Myeloid Leukemia | ACH-001574", + "Acute Myeloid Leukemia | ACH-001577", + "Acute Myeloid Leukemia | ACH-001613", + "Acute Myeloid Leukemia | ACH-001618", + "Acute Myeloid Leukemia | ACH-001647", + "Acute Myeloid Leukemia | ACH-001656" + ], + "type": "scattergl", + "x": { + "bdata": "CJ/fP16jlT6TIrpAinkNQfzmdD6qGBi+C4skQLKkgT+lXzK/dFkmQJUt60Dc5rlAK434P0vczUCLIpk+4IwBwECUFEDt+pNAGDlGQOkUvb37sMRAtpkHQIODlUC0oEJAVFKOQL2JhEA=", + "dtype": "f4" + }, + "y": { + "bdata": "PxwGwL8xqL9U0oXAV4GbwBxNPMDLXgrAdhBnPvxjjb/64PG/C68qwACzkMBSwYXA0JwNwOuhesCgd/Y84oBMwOLsN8B/ZHLAV731vwxmR7/VaHfAJSQDwDgYGsA/xQjAlARnwAezc8A=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000007", + "ACH-000009", + "ACH-000202", + 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+ }, + "mode": "markers", + "name": "Colorectal Adenocarcinoma", + "text": [ + "Colorectal Adenocarcinoma | ACH-000007", + "Colorectal Adenocarcinoma | ACH-000009", + "Colorectal Adenocarcinoma | ACH-000202", + "Colorectal Adenocarcinoma | ACH-000249", + "Colorectal Adenocarcinoma | ACH-000252", + "Colorectal Adenocarcinoma | ACH-000253", + "Colorectal Adenocarcinoma | ACH-000286", + "Colorectal Adenocarcinoma | ACH-000296", + "Colorectal Adenocarcinoma | ACH-000350", + "Colorectal Adenocarcinoma | ACH-000381", + "Colorectal Adenocarcinoma | ACH-000403", + "Colorectal Adenocarcinoma | ACH-000421", + "Colorectal Adenocarcinoma | ACH-000467", + "Colorectal Adenocarcinoma | ACH-000470", + "Colorectal Adenocarcinoma | ACH-000489", + "Colorectal Adenocarcinoma | ACH-000491", + "Colorectal Adenocarcinoma | ACH-000501", + "Colorectal Adenocarcinoma | ACH-000532", + "Colorectal Adenocarcinoma | ACH-000552", + "Colorectal Adenocarcinoma | ACH-000565", + "Colorectal Adenocarcinoma | ACH-000651", + "Colorectal Adenocarcinoma | ACH-000683", + "Colorectal Adenocarcinoma | ACH-000722", + "Colorectal Adenocarcinoma | ACH-000798", + "Colorectal Adenocarcinoma | ACH-000820", + "Colorectal Adenocarcinoma | ACH-000926", + "Colorectal Adenocarcinoma | ACH-000935", + "Colorectal Adenocarcinoma | ACH-000943", + "Colorectal Adenocarcinoma | ACH-000950", + "Colorectal Adenocarcinoma | ACH-000957", + "Colorectal Adenocarcinoma | ACH-000958", + "Colorectal Adenocarcinoma | ACH-000959", + "Colorectal Adenocarcinoma | ACH-000963", + "Colorectal Adenocarcinoma | ACH-000969", + "Colorectal Adenocarcinoma | ACH-000970", + "Colorectal Adenocarcinoma | ACH-000971", + "Colorectal Adenocarcinoma | ACH-000985", + "Colorectal Adenocarcinoma | ACH-000986", + "Colorectal Adenocarcinoma | ACH-000991", + "Colorectal Adenocarcinoma | ACH-000997", + "Colorectal Adenocarcinoma | ACH-001039", + "Colorectal Adenocarcinoma | ACH-001061", + "Colorectal Adenocarcinoma | ACH-001081", + "Colorectal Adenocarcinoma | ACH-001345", + "Colorectal Adenocarcinoma | ACH-001399", + "Colorectal Adenocarcinoma | ACH-001454", + "Colorectal Adenocarcinoma | ACH-001458", + "Colorectal Adenocarcinoma | ACH-001459", + "Colorectal Adenocarcinoma | ACH-001460", + "Colorectal Adenocarcinoma | ACH-001461", + "Colorectal Adenocarcinoma | ACH-001786", + "Colorectal Adenocarcinoma | ACH-002024", + "Colorectal Adenocarcinoma | ACH-002025", + "Colorectal Adenocarcinoma | ACH-002233", + "Colorectal Adenocarcinoma | ACH-002535", + "Colorectal Adenocarcinoma | ACH-002654", + "Colorectal Adenocarcinoma | ACH-002659", + "Colorectal Adenocarcinoma | ACH-002660", + "Colorectal Adenocarcinoma | ACH-002662", + "Colorectal Adenocarcinoma | ACH-002664", + "Colorectal Adenocarcinoma | ACH-002669" + ], + "type": "scattergl", + "x": { + "bdata": 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ACH-000593", + "Bladder Urothelial Carcinoma | ACH-000720", + "Bladder Urothelial Carcinoma | ACH-000724", + "Bladder Urothelial Carcinoma | ACH-000741", + "Bladder Urothelial Carcinoma | ACH-000753", + "Bladder Urothelial Carcinoma | ACH-000802", + "Bladder Urothelial Carcinoma | ACH-000834", + "Bladder Urothelial Carcinoma | ACH-000862", + "Bladder Urothelial Carcinoma | ACH-000896", + "Bladder Urothelial Carcinoma | ACH-000905", + "Bladder Urothelial Carcinoma | ACH-001183", + "Bladder Urothelial Carcinoma | ACH-001407", + "Bladder Urothelial Carcinoma | ACH-001409", + "Bladder Urothelial Carcinoma | ACH-001412", + "Bladder Urothelial Carcinoma | ACH-001413", + "Bladder Urothelial Carcinoma | ACH-001414", + "Bladder Urothelial Carcinoma | ACH-001415", + "Bladder Urothelial Carcinoma | ACH-001416" + ], + "type": "scattergl", + "x": { + "bdata": 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"hoverinfo": "text", + "marker": { + "color": "#FFA15A", + "size": 7 + }, + "mode": "markers", + "name": "Non-Small Cell Lung Cancer", + "text": [ + "Non-Small Cell Lung Cancer | ACH-000012", + "Non-Small Cell Lung Cancer | ACH-000015", + "Non-Small Cell Lung Cancer | ACH-000021", + "Non-Small Cell Lung Cancer | ACH-000029", + "Non-Small Cell Lung Cancer | ACH-000030", + "Non-Small Cell Lung Cancer | ACH-000035", + "Non-Small Cell Lung Cancer | ACH-000143", + "Non-Small Cell Lung Cancer | ACH-000161", + "Non-Small Cell Lung Cancer | ACH-000176", + "Non-Small Cell Lung Cancer | ACH-000251", + "Non-Small Cell Lung Cancer | ACH-000261", + "Non-Small Cell Lung Cancer | ACH-000264", + "Non-Small Cell Lung Cancer | ACH-000311", + "Non-Small Cell Lung Cancer | ACH-000337", + "Non-Small Cell Lung Cancer | ACH-000339", + "Non-Small Cell Lung Cancer | ACH-000343", + "Non-Small Cell Lung Cancer | ACH-000378", + "Non-Small Cell Lung Cancer | ACH-000390", + "Non-Small Cell Lung Cancer | ACH-000395", + "Non-Small Cell Lung Cancer | ACH-000414", + "Non-Small Cell Lung Cancer | ACH-000416", + "Non-Small Cell Lung Cancer | ACH-000434", + "Non-Small Cell Lung Cancer | ACH-000438", + "Non-Small Cell Lung Cancer | ACH-000442", + "Non-Small Cell Lung Cancer | ACH-000444", + "Non-Small Cell Lung Cancer | ACH-000448", + "Non-Small Cell Lung Cancer | ACH-000454", + "Non-Small Cell Lung Cancer | ACH-000463", + "Non-Small Cell Lung Cancer | ACH-000481", + "Non-Small Cell Lung Cancer | ACH-000496", + "Non-Small Cell Lung Cancer | ACH-000510", + "Non-Small Cell Lung Cancer | ACH-000511", + "Non-Small Cell Lung Cancer | ACH-000521", + "Non-Small Cell Lung Cancer | ACH-000528", + "Non-Small Cell Lung Cancer | ACH-000562", + "Non-Small Cell Lung Cancer | ACH-000563", + "Non-Small Cell Lung Cancer | ACH-000585", + "Non-Small Cell Lung Cancer | ACH-000587", + "Non-Small Cell Lung Cancer | ACH-000589", + "Non-Small Cell Lung Cancer | ACH-000596", + "Non-Small Cell Lung Cancer | ACH-000627", + "Non-Small Cell Lung Cancer | ACH-000638", + "Non-Small Cell Lung Cancer | ACH-000662", + "Non-Small Cell Lung Cancer | ACH-000665", + "Non-Small Cell Lung Cancer | ACH-000666", + "Non-Small Cell Lung Cancer | ACH-000667", + "Non-Small Cell Lung Cancer | ACH-000672", + "Non-Small Cell Lung Cancer | ACH-000677", + "Non-Small Cell Lung Cancer | ACH-000681", + "Non-Small Cell Lung Cancer | ACH-000700", + "Non-Small Cell Lung Cancer | ACH-000706", + "Non-Small Cell Lung Cancer | ACH-000718", + "Non-Small Cell Lung Cancer | ACH-000747", + "Non-Small Cell Lung Cancer | ACH-000757", + "Non-Small Cell Lung Cancer | ACH-000766", + "Non-Small Cell Lung Cancer | ACH-000769", + "Non-Small Cell Lung Cancer | ACH-000774", + "Non-Small Cell Lung Cancer | ACH-000781", + "Non-Small Cell Lung Cancer | ACH-000785", + "Non-Small Cell Lung Cancer | ACH-000787", + "Non-Small Cell Lung Cancer | ACH-000791", + "Non-Small Cell Lung Cancer | ACH-000826", + "Non-Small Cell Lung Cancer | ACH-000837", + "Non-Small Cell Lung Cancer | ACH-000840", + "Non-Small Cell Lung Cancer | ACH-000841", + "Non-Small Cell Lung Cancer | ACH-000843", + "Non-Small Cell Lung Cancer | ACH-000845", + "Non-Small Cell Lung Cancer | ACH-000851", + "Non-Small Cell Lung Cancer | ACH-000853", + "Non-Small Cell Lung Cancer | ACH-000858", + "Non-Small Cell Lung Cancer | ACH-000860", + "Non-Small Cell Lung Cancer | ACH-000861", + "Non-Small Cell Lung Cancer | ACH-000867", + "Non-Small Cell Lung Cancer | ACH-000869", + "Non-Small Cell Lung Cancer | ACH-000872", + "Non-Small Cell Lung Cancer | ACH-000878", + "Non-Small Cell Lung Cancer | ACH-000886", + "Non-Small Cell Lung Cancer | ACH-000888", + "Non-Small Cell Lung Cancer | ACH-000894", + "Non-Small Cell Lung Cancer | ACH-000900", + "Non-Small Cell Lung Cancer | ACH-000901", + "Non-Small Cell Lung Cancer | ACH-000916", + "Non-Small Cell Lung Cancer | ACH-000921", + "Non-Small Cell Lung Cancer | ACH-000924", + "Non-Small Cell Lung Cancer | ACH-000929", + "Non-Small Cell Lung Cancer | ACH-000945", + "Non-Small Cell Lung Cancer | ACH-000975", + "Non-Small Cell Lung Cancer | ACH-000980", + "Non-Small Cell Lung Cancer | ACH-001075", + "Non-Small Cell Lung Cancer | ACH-001137", + "Non-Small Cell Lung Cancer | ACH-001233", + "Non-Small Cell Lung Cancer | ACH-002035", + "Non-Small Cell Lung Cancer | ACH-002156", + "Non-Small Cell Lung Cancer | ACH-002522", + "Non-Small Cell Lung Cancer | ACH-002526", + "Non-Small Cell Lung Cancer | ACH-002531", + "Non-Small Cell Lung Cancer | ACH-002650", + "Non-Small Cell Lung Cancer | ACH-003012" + ], + "type": "scattergl", + "x": { + "bdata": 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"ACH-000827", + "ACH-000881", + "ACH-000882", + "ACH-000884", + "ACH-000899", + "ACH-000915", + "ACH-000968", + "ACH-001041", + "ACH-001190", + "ACH-001239", + "ACH-001522", + "ACH-001563", + "ACH-001566", + "ACH-001567", + "ACH-001568", + "ACH-001570", + "ACH-001645", + "ACH-001970", + "ACH-001972", + "ACH-001973", + "ACH-001975", + "ACH-001982", + "ACH-001986", + "ACH-001990", + "ACH-002001", + "ACH-002002", + "ACH-002003", + "ACH-002004", + "ACH-002005", + "ACH-002084", + "ACH-002143", + "ACH-002458", + "ACH-002460", + "ACH-002461", + "ACH-002508", + "ACH-002510", + "ACH-002511", + "ACH-002512", + "ACH-002847", + "ACH-002928" + ], + "hoverinfo": "text", + "marker": { + "color": "#19D3F3", + "size": 7 + }, + "mode": "markers", + "name": "Melanoma", + "text": [ + "Melanoma | ACH-000014", + "Melanoma | ACH-000219", + "Melanoma | ACH-000274", + "Melanoma | ACH-000304", + "Melanoma | ACH-000322", + "Melanoma | ACH-000348", + "Melanoma | ACH-000401", + "Melanoma | ACH-000404", + "Melanoma | ACH-000425", + "Melanoma | ACH-000441", + "Melanoma | ACH-000450", + "Melanoma | ACH-000458", + "Melanoma | ACH-000477", + "Melanoma | ACH-000550", + "Melanoma | ACH-000579", + "Melanoma | ACH-000580", + "Melanoma | ACH-000614", + "Melanoma | ACH-000632", + "Melanoma | ACH-000661", + "Melanoma | ACH-000765", + "Melanoma | ACH-000788", + "Melanoma | ACH-000799", + "Melanoma | ACH-000801", + "Melanoma | ACH-000805", + "Melanoma | ACH-000810", + "Melanoma | ACH-000822", + "Melanoma | ACH-000827", + "Melanoma | ACH-000881", + "Melanoma | ACH-000882", + "Melanoma | ACH-000884", + "Melanoma | ACH-000899", + "Melanoma | ACH-000915", + "Melanoma | ACH-000968", + "Melanoma | ACH-001041", + "Melanoma | ACH-001190", + "Melanoma | ACH-001239", + "Melanoma | ACH-001522", + "Melanoma | ACH-001563", + "Melanoma | ACH-001566", + "Melanoma | ACH-001567", + "Melanoma | ACH-001568", + "Melanoma | ACH-001570", + "Melanoma | ACH-001645", + "Melanoma | ACH-001970", + "Melanoma | ACH-001972", + "Melanoma | ACH-001973", + "Melanoma | ACH-001975", + "Melanoma | ACH-001982", + "Melanoma | ACH-001986", + "Melanoma | ACH-001990", + "Melanoma | ACH-002001", + "Melanoma | ACH-002002", + "Melanoma | ACH-002003", + "Melanoma | ACH-002004", + "Melanoma | ACH-002005", + "Melanoma | ACH-002084", + "Melanoma | ACH-002143", + "Melanoma | ACH-002458", + "Melanoma | ACH-002460", + "Melanoma | ACH-002461", + "Melanoma | ACH-002508", + "Melanoma | ACH-002510", + "Melanoma | ACH-002511", + "Melanoma | ACH-002512", + "Melanoma | ACH-002847", + "Melanoma | ACH-002928" + ], + "type": "scattergl", + "x": { + "bdata": "7FguQHmL30A+qSDA8ygIPyhld0CrGKS/lgovQOSw8sDf0vLA5OaQQDLM8sDNs/LA9c2LPb0bEsC82/LAty3WvUNfc0BUbh1ANrPywAKysD8wpNE/1uCfvCPZ8sAykL4/dFanPvkxJ8D4G6I/1idpQLe8lkAYiltA1dDywOh/k0CW3YFAJnsiQG6/nL/vi35AYyK1P8/Y8sDq3fLA2OHywEPW8sB4w/LAAW70vX24CEDqtPLA/LvywPfA8sCaEGJALhuHQFgLrEDeeZFAz9DVQG8nC0DmyvLAma1oQP3jDr9cfDnAqgojQNYVFkB+fTU++15nvyDZdEAK217Auim3PktPfb0rfhvA", + "dtype": "f4" + }, + "y": { + "bdata": 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"ACH-001393", + "ACH-001394", + "ACH-001396", + "ACH-001419", + "ACH-001662", + "ACH-001683", + "ACH-001819", + "ACH-002179", + "ACH-002399", + "ACH-002401" + ], + "hoverinfo": "text", + "marker": { + "color": "#FF6692", + "size": 7 + }, + "mode": "markers", + "name": "Invasive Breast Carcinoma", + "text": [ + "Invasive Breast Carcinoma | ACH-000017", + "Invasive Breast Carcinoma | ACH-000019", + "Invasive Breast Carcinoma | ACH-000028", + "Invasive Breast Carcinoma | ACH-000097", + "Invasive Breast Carcinoma | ACH-000111", + "Invasive Breast Carcinoma | ACH-000147", + "Invasive Breast Carcinoma | ACH-000148", + "Invasive Breast Carcinoma | ACH-000212", + "Invasive Breast Carcinoma | ACH-000223", + "Invasive Breast Carcinoma | ACH-000248", + "Invasive Breast Carcinoma | ACH-000258", + "Invasive Breast Carcinoma | ACH-000276", + "Invasive Breast Carcinoma | ACH-000277", + "Invasive Breast Carcinoma | ACH-000288", + "Invasive Breast Carcinoma | ACH-000330", + "Invasive Breast Carcinoma | ACH-000352", + "Invasive Breast Carcinoma | ACH-000374", + "Invasive Breast Carcinoma | ACH-000554", + "Invasive Breast Carcinoma | ACH-000573", + "Invasive Breast Carcinoma | ACH-000621", + "Invasive Breast Carcinoma | ACH-000668", + "Invasive Breast Carcinoma | ACH-000699", + "Invasive Breast Carcinoma | ACH-000711", + "Invasive Breast Carcinoma | ACH-000721", + "Invasive Breast Carcinoma | ACH-000768", + "Invasive Breast Carcinoma | ACH-000783", + "Invasive Breast Carcinoma | ACH-000849", + "Invasive Breast Carcinoma | ACH-000856", + "Invasive Breast Carcinoma | ACH-000876", + "Invasive Breast Carcinoma | ACH-000910", + "Invasive Breast Carcinoma | ACH-000934", + "Invasive Breast Carcinoma | ACH-001065", + "Invasive Breast Carcinoma | ACH-001388", + "Invasive Breast Carcinoma | ACH-001389", + "Invasive Breast Carcinoma | ACH-001390", + "Invasive Breast Carcinoma | ACH-001391", + "Invasive Breast Carcinoma | ACH-001392", + "Invasive Breast Carcinoma | ACH-001393", + "Invasive Breast Carcinoma | ACH-001394", + "Invasive Breast Carcinoma | ACH-001396", + "Invasive Breast Carcinoma | ACH-001419", + "Invasive Breast Carcinoma | ACH-001662", + "Invasive Breast Carcinoma | ACH-001683", + "Invasive Breast Carcinoma | ACH-001819", + "Invasive Breast Carcinoma | ACH-002179", + "Invasive Breast Carcinoma | ACH-002399", + "Invasive Breast Carcinoma | ACH-002401" + ], + "type": "scattergl", + "x": { + "bdata": "rkW1vVsoAEC1uoxAFfaQPyCmQ0DKLFpAbvxLPyOzmz+cVMO/HdnmP3/4gr+78l2/4kURPS1q7z87dn0/WEV5P8gN6z/dOwzAAqDbPxi3YMB1QIq/UP/2v/OVE0B8c05ABCWeP5jKOsAQ9GZA6EPrQCD1eb9wwn1AgExdwCFbr0BMPAvAzsvywIwbxz+MbTPArtLywFrW8sCez/LAeu3ywG3mAz+T0LS+WhW8PonUvb9DUUdA7QmoPxqJEkA=", + "dtype": "f4" + }, + "y": { + "bdata": "2bE+v8uRlr/uW82/IfMhv8F8AcB+tZi/C1nlP9Abtz7lxHy9p5q1v5IsjT5cP4Y/GMIpv20cMkDw29G+SpiMvwIcrb6yKO2/piLDPkJOoj/6oYy/zqSpP1OKkr+gFWi/qcpCvgkCPL9qFEa/gxMJPEUssr/+thPAkVHSv+bVCsAyckg/nJ2qv1hXXT8Xl0k/Ewurv+Oyqr/OFKu/Z7+qv9uNGD7hwHY8PX7uvh4BAL9aYB7AyrsqvkJNu70=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000022", + "ACH-000023", + "ACH-000042", + "ACH-000060", + "ACH-000085", + "ACH-000093", + "ACH-000094", + "ACH-000114", + "ACH-000118", + "ACH-000138", + "ACH-000139", + "ACH-000155", + "ACH-000164", + "ACH-000178", + "ACH-000213", + "ACH-000222", + "ACH-000235", + "ACH-000243", + "ACH-000265", + "ACH-000266", + "ACH-000281", + "ACH-000307", + "ACH-000320", + "ACH-000332", + "ACH-000354", + "ACH-000417", + "ACH-000468", + "ACH-000502", + "ACH-000517", + "ACH-000535", + "ACH-000599", + "ACH-000601", + "ACH-000652", + "ACH-001098", + "ACH-001107", + "ACH-001353", + "ACH-001375", + "ACH-001377", + "ACH-001379", + "ACH-001380", + "ACH-001382", + "ACH-001999", + "ACH-002039", + "ACH-002186", + "ACH-002672" + ], + "hoverinfo": "text", + "marker": { + "color": "#B6E880", + "size": 7 + }, + "mode": "markers", + "name": "Pancreatic Adenocarcinoma", + "text": [ + "Pancreatic Adenocarcinoma | ACH-000022", + "Pancreatic Adenocarcinoma | ACH-000023", + "Pancreatic Adenocarcinoma | ACH-000042", + "Pancreatic Adenocarcinoma | ACH-000060", + "Pancreatic Adenocarcinoma | ACH-000085", + "Pancreatic Adenocarcinoma | ACH-000093", + "Pancreatic Adenocarcinoma | ACH-000094", + "Pancreatic Adenocarcinoma | ACH-000114", + "Pancreatic Adenocarcinoma | ACH-000118", + "Pancreatic Adenocarcinoma | ACH-000138", + "Pancreatic Adenocarcinoma | ACH-000139", + "Pancreatic Adenocarcinoma | ACH-000155", + "Pancreatic Adenocarcinoma | ACH-000164", + "Pancreatic Adenocarcinoma | ACH-000178", + "Pancreatic Adenocarcinoma | ACH-000213", + "Pancreatic Adenocarcinoma | ACH-000222", + "Pancreatic Adenocarcinoma | ACH-000235", + "Pancreatic Adenocarcinoma | ACH-000243", + "Pancreatic Adenocarcinoma | ACH-000265", + "Pancreatic Adenocarcinoma | ACH-000266", + "Pancreatic Adenocarcinoma | ACH-000281", + "Pancreatic Adenocarcinoma | ACH-000307", + "Pancreatic Adenocarcinoma | ACH-000320", + "Pancreatic Adenocarcinoma | ACH-000332", + "Pancreatic Adenocarcinoma | ACH-000354", + "Pancreatic Adenocarcinoma | ACH-000417", + "Pancreatic Adenocarcinoma | ACH-000468", + "Pancreatic Adenocarcinoma | ACH-000502", + "Pancreatic Adenocarcinoma | ACH-000517", + "Pancreatic Adenocarcinoma | ACH-000535", + "Pancreatic Adenocarcinoma | ACH-000599", + "Pancreatic Adenocarcinoma | ACH-000601", + "Pancreatic Adenocarcinoma | ACH-000652", + "Pancreatic Adenocarcinoma | ACH-001098", + "Pancreatic Adenocarcinoma | ACH-001107", + "Pancreatic Adenocarcinoma | ACH-001353", + "Pancreatic Adenocarcinoma | ACH-001375", + "Pancreatic Adenocarcinoma | ACH-001377", + "Pancreatic Adenocarcinoma | ACH-001379", + "Pancreatic Adenocarcinoma | ACH-001380", + "Pancreatic Adenocarcinoma | ACH-001382", + "Pancreatic Adenocarcinoma | ACH-001999", + "Pancreatic Adenocarcinoma | ACH-002039", + "Pancreatic Adenocarcinoma | ACH-002186", + "Pancreatic Adenocarcinoma | ACH-002672" + ], + "type": "scattergl", + "x": { + "bdata": 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"ACH-000660", + "ACH-000697", + "ACH-000714", + "ACH-000763", + "ACH-000817", + "ACH-000821", + "ACH-000829", + "ACH-000838", + "ACH-000889", + "ACH-000914", + "ACH-000944", + "ACH-001450", + "ACH-001498", + "ACH-001533", + "ACH-001539", + "ACH-001616", + "ACH-001634", + "ACH-001639", + "ACH-001677", + "ACH-001707", + "ACH-001709", + "ACH-002055", + "ACH-002062", + "ACH-002214", + "ACH-002215", + "ACH-002478", + "ACH-002485", + "ACH-002500", + "ACH-002677", + "ACH-002678" + ], + "hoverinfo": "text", + "marker": { + "color": "#FF97FF", + "size": 7 + }, + "mode": "markers", + "name": "Mature B-Cell Neoplasms", + "text": [ + "Mature B-Cell Neoplasms | ACH-000024", + "Mature B-Cell Neoplasms | ACH-000106", + "Mature B-Cell Neoplasms | ACH-000124", + "Mature B-Cell Neoplasms | ACH-000167", + "Mature B-Cell Neoplasms | ACH-000183", + "Mature B-Cell Neoplasms | ACH-000204", + "Mature B-Cell Neoplasms | ACH-000271", + "Mature B-Cell Neoplasms | ACH-000315", + "Mature B-Cell Neoplasms | ACH-000334", + "Mature B-Cell Neoplasms | ACH-000346", + "Mature B-Cell Neoplasms | ACH-000363", + "Mature B-Cell Neoplasms | ACH-000365", + "Mature B-Cell Neoplasms | ACH-000371", + "Mature B-Cell Neoplasms | ACH-000398", + "Mature B-Cell Neoplasms | ACH-000402", + "Mature B-Cell Neoplasms | ACH-000405", + "Mature B-Cell Neoplasms | ACH-000426", + "Mature B-Cell Neoplasms | ACH-000436", + "Mature B-Cell Neoplasms | ACH-000512", + "Mature B-Cell Neoplasms | ACH-000541", + "Mature B-Cell Neoplasms | ACH-000567", + "Mature B-Cell Neoplasms | ACH-000576", + "Mature B-Cell Neoplasms | ACH-000588", + "Mature B-Cell Neoplasms | ACH-000653", + "Mature B-Cell Neoplasms | ACH-000654", + "Mature B-Cell Neoplasms | ACH-000656", + "Mature B-Cell Neoplasms | ACH-000660", + "Mature B-Cell Neoplasms | ACH-000697", + "Mature B-Cell Neoplasms | ACH-000714", + "Mature B-Cell Neoplasms | ACH-000763", + "Mature B-Cell Neoplasms | ACH-000817", + "Mature B-Cell Neoplasms | ACH-000821", + "Mature B-Cell Neoplasms | ACH-000829", + "Mature B-Cell Neoplasms | ACH-000838", + "Mature B-Cell Neoplasms | ACH-000889", + "Mature B-Cell Neoplasms | ACH-000914", + "Mature B-Cell Neoplasms | ACH-000944", + "Mature B-Cell Neoplasms | ACH-001450", + "Mature B-Cell Neoplasms | ACH-001498", + "Mature B-Cell Neoplasms | ACH-001533", + "Mature B-Cell Neoplasms | ACH-001539", + "Mature B-Cell Neoplasms | ACH-001616", + "Mature B-Cell Neoplasms | ACH-001634", + "Mature B-Cell Neoplasms | ACH-001639", + "Mature B-Cell Neoplasms | ACH-001677", + "Mature B-Cell Neoplasms | ACH-001707", + "Mature B-Cell Neoplasms | ACH-001709", + "Mature B-Cell Neoplasms | ACH-002055", + "Mature B-Cell Neoplasms | ACH-002062", + "Mature B-Cell Neoplasms | ACH-002214", + "Mature B-Cell Neoplasms | ACH-002215", + "Mature B-Cell Neoplasms | ACH-002478", + "Mature B-Cell Neoplasms | ACH-002485", + "Mature B-Cell Neoplasms | ACH-002500", + "Mature B-Cell Neoplasms | ACH-002677", + "Mature B-Cell Neoplasms | ACH-002678" + ], + "type": "scattergl", + "x": { + "bdata": "t7c4QLlv6z/HxuxAxpkSQLDVsUDIH59AtUsPQeZaD0D/9Zu/peWLQEmVKT6ps7xA9oyGQMmJWEA5xw1APPubQC/Krz3T4/LAeCpTQB254z+1tfLAmnn9PkI7okAJczNAkT0lQP+fBEF5/AVBQ7qEQNSVEkAMDMQ/qvlkQKZ88j/hrPLAxnbGP4d6yEDrAOBA+C6XQIWsg0A9WaFAGtPywD5rzT8HPspARrPywFo4+z+M3PA/JsPywLsb8EB39kxA1UYRQABdz0C/939AwwBAQM31LUDEy7lAeIW8QIZZKkA=", + "dtype": "f4" + }, + "y": { + "bdata": "66ZlwO87kr9NKYLAyH8mwEBRi8DqQJnAT1a/wANvNMCmyj/AQ2hVwBbIZ8DvjJTA3bFvwMSbU8D6BSnAlDhUwCZ4LMCQLqu/bCk1wOQqOcBxeau/UqpCwFT8csDWkGnAO11wwF4loMDNqXfA7VAjwPvWb8CqPj7An25ywPGBNcA1Z6u/dAFVwCWQeMAmNZXAP2dkwJEGicA0/WrAkxurv7NHHMADXq7AIYWrvzooiMClkeW/oeOqv5M/nsBc/1DA8DcVwEF7jsASMzjABUNKwPE2+b86uWbAs2WcwDUbWMA=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000025", + "ACH-001067", + "ACH-002070" + ], + "hoverinfo": "text", + "marker": { + "color": "#FECB52", + "size": 7 + }, + "mode": "markers", + "name": "Meningothelial Tumor", + "text": [ + "Meningothelial Tumor | ACH-000025", + "Meningothelial Tumor | ACH-001067", + "Meningothelial Tumor | ACH-002070" + ], + "type": "scattergl", + "x": { + "bdata": "28RMQHnG8sDmH4I/", + "dtype": "f4" + }, + "y": { + "bdata": "nxIiQJ+aqr9v4ds/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000036", + "ACH-000040", + "ACH-000067", + "ACH-000075", + "ACH-000098", + "ACH-000128", + "ACH-000137", + "ACH-000152", + "ACH-000200", + "ACH-000208", + "ACH-000215", + "ACH-000231", + "ACH-000232", + "ACH-000244", + "ACH-000269", + "ACH-000273", + "ACH-000323", + "ACH-000329", + "ACH-000368", + "ACH-000370", + "ACH-000376", + "ACH-000389", + "ACH-000437", + "ACH-000445", + "ACH-000455", + "ACH-000464", + "ACH-000469", + "ACH-000479", + "ACH-000504", + "ACH-000558", + "ACH-000570", + "ACH-000571", + "ACH-000591", + "ACH-000592", + "ACH-000595", + "ACH-000609", + "ACH-000622", + "ACH-000623", + "ACH-000631", + "ACH-000634", + "ACH-000655", + "ACH-000673", + "ACH-000676", + "ACH-000738", + "ACH-000756", + "ACH-000760", + "ACH-000807", + "ACH-000819", + "ACH-000863", + "ACH-000887", + "ACH-001016", + "ACH-001126", + "ACH-001172", + "ACH-001329", + "ACH-001605", + "ACH-001606", + "ACH-001608", + "ACH-001609", + "ACH-001610", + "ACH-001611", + "ACH-001622", + "ACH-001623", + "ACH-001624", + "ACH-002228", + "ACH-002229", + "ACH-002230", + "ACH-002257", + "ACH-002269", + "ACH-002304", + "ACH-002680" + ], + "hoverinfo": "text", + "marker": { + "color": "#FD3216", + "size": 7 + }, + "mode": "markers", + "name": "Diffuse Glioma", + "text": [ + "Diffuse Glioma | ACH-000036", + "Diffuse Glioma | ACH-000040", + "Diffuse Glioma | ACH-000067", + "Diffuse Glioma | ACH-000075", + "Diffuse Glioma | ACH-000098", + "Diffuse Glioma | ACH-000128", + "Diffuse Glioma | ACH-000137", + "Diffuse Glioma | ACH-000152", + "Diffuse Glioma | ACH-000200", + "Diffuse Glioma | ACH-000208", + "Diffuse Glioma | ACH-000215", + "Diffuse Glioma | ACH-000231", + "Diffuse Glioma | ACH-000232", + "Diffuse Glioma | ACH-000244", + "Diffuse Glioma | ACH-000269", + "Diffuse Glioma | ACH-000273", + "Diffuse Glioma | ACH-000323", + "Diffuse Glioma | ACH-000329", + "Diffuse Glioma | ACH-000368", + "Diffuse Glioma | ACH-000370", + "Diffuse Glioma | ACH-000376", + "Diffuse Glioma | ACH-000389", + "Diffuse Glioma | ACH-000437", + "Diffuse Glioma | ACH-000445", + "Diffuse Glioma | ACH-000455", + "Diffuse Glioma | ACH-000464", + "Diffuse Glioma | ACH-000469", + "Diffuse Glioma | ACH-000479", + "Diffuse Glioma | ACH-000504", + "Diffuse Glioma | ACH-000558", + "Diffuse Glioma | ACH-000570", + "Diffuse Glioma | ACH-000571", + "Diffuse Glioma | ACH-000591", + "Diffuse Glioma | ACH-000592", + "Diffuse Glioma | ACH-000595", + "Diffuse Glioma | ACH-000609", + "Diffuse Glioma | ACH-000622", + "Diffuse Glioma | ACH-000623", + "Diffuse Glioma | ACH-000631", + "Diffuse Glioma | ACH-000634", + "Diffuse Glioma | ACH-000655", + "Diffuse Glioma | ACH-000673", + "Diffuse Glioma | ACH-000676", + "Diffuse Glioma | ACH-000738", + "Diffuse Glioma | ACH-000756", + "Diffuse Glioma | ACH-000760", + "Diffuse Glioma | ACH-000807", + "Diffuse Glioma | ACH-000819", + "Diffuse Glioma | ACH-000863", + "Diffuse Glioma | ACH-000887", + "Diffuse Glioma | ACH-001016", + "Diffuse Glioma | ACH-001126", + "Diffuse Glioma | ACH-001172", + "Diffuse Glioma | ACH-001329", + "Diffuse Glioma | ACH-001605", + "Diffuse Glioma | ACH-001606", + "Diffuse Glioma | ACH-001608", + "Diffuse Glioma | ACH-001609", + "Diffuse Glioma | ACH-001610", + "Diffuse Glioma | ACH-001611", + "Diffuse Glioma | ACH-001622", + "Diffuse Glioma | ACH-001623", + "Diffuse Glioma | ACH-001624", + "Diffuse Glioma | ACH-002228", + "Diffuse Glioma | ACH-002229", + "Diffuse Glioma | ACH-002230", + "Diffuse Glioma | ACH-002257", + "Diffuse Glioma | ACH-002269", + "Diffuse Glioma | ACH-002304", + "Diffuse Glioma | ACH-002680" + ], + "type": "scattergl", + "x": { + "bdata": "mh/hPVQB678x6tS/KOW3v/dpHT8lrPE/mnBjP14Hzb8X1PLASxKsvqTiD0CPJ+Y+wFaLQMRhVMA15j2+W1oSQN3XjD4pmb696Ux9vxwwrb+8bK5Ak16WvrwJTD9vE12/iNCAQBk8N8CVJqc/ykCZPtr/UMAvm8s/rKj4Pw0KJsBXzSs+pyIDwOfulD8KwX69m7I0wKcv17+u7X6/wujBP85Qgj7W0vLAj2OCQL0vhkAApx5AN1NhPxh4uT+L8Dg/l2YiQDfh2z81yARAfLjywGiXmkDAzgDAJaMwvmKG978AIA1ArVWKP8kgOj4SdIw/orEtvwdNHsBZeCG/767ywDrL8sCfwvLA+1m6velSX0CDyfLAASCkPQ==", + "dtype": "f4" + }, + "y": { + "bdata": "dVSBQJ5QkkCBQHhA32Z2QHhKnEBHHlI/EaJaQERHU0CHtaq/YZHkP5dKJEC+4kxAGIGRP1E2mkAg6nM/BXwiQLspF0BZ1bo/MTumQArZhz9JDMQ/LdJSQDadOkDw2mJAlt8vP6CKiECdrU1AM5QXQHcUcEBPAkZAoUttQE/oGkCEOZFAkcBZQDjAOUAl21xAuK7kP6XFfkD2cwlA6TYNQI79xD9ET6u/bqt1vweQoz+BnG1AhVhUP/tYuz70tBZAx7tCQO/Nnj/UBrc/HWSrv29tDT/d0YJAtCkuQNs8HEAaLwRAKf8FQHGeB0Be8hJABWOPQO2ni0Dy3J8/QMGrv1xIq78e8Kq/M7SjQER6uj9Q36q/DzOEQA==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000037" + ], + "hoverinfo": "text", + "marker": { + "color": "#00FE35", + "size": 7 + }, + "mode": "markers", + "name": "Sarcoma, NOS", + "text": [ + "Sarcoma, NOS | ACH-000037" + ], + "type": "scattergl", + "x": { + "bdata": "P0j4vw==", + "dtype": "f4" + }, + "y": { + "bdata": "yalAQA==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000039", + "ACH-000041", + "ACH-000052", + "ACH-000087", + "ACH-000210", + "ACH-000279", + "ACH-000391", + "ACH-000424", + "ACH-000499", + "ACH-001029", + "ACH-001038", + "ACH-001192", + "ACH-001193", + "ACH-001205", + "ACH-001283", + "ACH-001430", + "ACH-001431", + "ACH-002105", + "ACH-002106", + "ACH-002109", + "ACH-002110", + "ACH-002114", + "ACH-002116", + "ACH-002119", + "ACH-002160" + ], + "hoverinfo": "text", + "marker": { + "color": "#6A76FC", + "size": 7 + }, + "mode": "markers", + "name": "Ewing Sarcoma", + "text": [ + "Ewing Sarcoma | ACH-000039", + "Ewing Sarcoma | ACH-000041", + "Ewing Sarcoma | ACH-000052", + "Ewing Sarcoma | ACH-000087", + "Ewing Sarcoma | ACH-000210", + "Ewing Sarcoma | ACH-000279", + "Ewing Sarcoma | ACH-000391", + "Ewing Sarcoma | ACH-000424", + "Ewing Sarcoma | ACH-000499", + "Ewing Sarcoma | ACH-001029", + "Ewing Sarcoma | ACH-001038", + "Ewing Sarcoma | ACH-001192", + "Ewing Sarcoma | ACH-001193", + "Ewing Sarcoma | ACH-001205", + "Ewing Sarcoma | ACH-001283", + "Ewing Sarcoma | ACH-001430", + "Ewing Sarcoma | ACH-001431", + "Ewing Sarcoma | ACH-002105", + "Ewing Sarcoma | ACH-002106", + "Ewing Sarcoma | ACH-002109", + "Ewing Sarcoma | ACH-002110", + "Ewing Sarcoma | ACH-002114", + "Ewing Sarcoma | ACH-002116", + "Ewing Sarcoma | ACH-002119", + "Ewing Sarcoma | ACH-002160" + ], + "type": "scattergl", + "x": { + "bdata": "/wQSv7AlDb3bRMc+yCtKQOPfhT986IZAAj6OQCvLu0AnEVdADYStQHagTUDuKeo/G0GIP47ntz/g1CFAAqWKP1SgBkCcbHU/J7CIQOQ79z8jCM1ALs/ywJ3w8sBIC7FAhNuoQA==", + "dtype": "f4" + }, + "y": { + "bdata": "IXZBP4dmHb4FDwpA7+bKvkKtt75+OHm/UULXPw9Wiz/OXy8/OH50P0YH7b9y5B4/IKjGP47Tpb2pkLI+6oPIPvlNur5i51pA5uLuvzqBhz8Jrtm9eJ+qv/hpqr8LSEc/4wmlvg==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000047", + "ACH-000144", + "ACH-000216", + "ACH-000239", + "ACH-000247", + "ACH-000255", + "ACH-000303", + "ACH-000325", + "ACH-000344", + "ACH-000356", + "ACH-000383", + "ACH-000427", + "ACH-000466", + "ACH-000485", + "ACH-000507", + "ACH-000581", + "ACH-000616", + "ACH-000633", + "ACH-000736", + "ACH-000746", + "ACH-000758", + "ACH-000764", + "ACH-000793", + "ACH-000847", + "ACH-000880", + "ACH-000898", + "ACH-000911", + "ACH-000919", + "ACH-000932", + "ACH-000948", + "ACH-001368", + "ACH-001496", + "ACH-001497", + "ACH-001500", + "ACH-001544", + "ACH-001653", + "ACH-001654", + "ACH-001664", + "ACH-002141", + "ACH-002161", + "ACH-002202", + "ACH-002446", + "ACH-002705", + "ACH-002706" + ], + "hoverinfo": "text", + "marker": { + "color": "#FED4C4", + "size": 7 + }, + "mode": "markers", + "name": "Esophagogastric Adenocarcinoma", + "text": [ + "Esophagogastric Adenocarcinoma | ACH-000047", + "Esophagogastric Adenocarcinoma | ACH-000144", + "Esophagogastric Adenocarcinoma | ACH-000216", + "Esophagogastric Adenocarcinoma | ACH-000239", + "Esophagogastric Adenocarcinoma | ACH-000247", + "Esophagogastric Adenocarcinoma | ACH-000255", + "Esophagogastric Adenocarcinoma | ACH-000303", + "Esophagogastric Adenocarcinoma | ACH-000325", + "Esophagogastric Adenocarcinoma | ACH-000344", + "Esophagogastric Adenocarcinoma | ACH-000356", + "Esophagogastric Adenocarcinoma | ACH-000383", + "Esophagogastric Adenocarcinoma | ACH-000427", + "Esophagogastric Adenocarcinoma | ACH-000466", + "Esophagogastric Adenocarcinoma | ACH-000485", + "Esophagogastric Adenocarcinoma | ACH-000507", + "Esophagogastric Adenocarcinoma | ACH-000581", + "Esophagogastric Adenocarcinoma | ACH-000616", + "Esophagogastric Adenocarcinoma | ACH-000633", + "Esophagogastric Adenocarcinoma | ACH-000736", + "Esophagogastric Adenocarcinoma | ACH-000746", + "Esophagogastric Adenocarcinoma | ACH-000758", + "Esophagogastric Adenocarcinoma | ACH-000764", + "Esophagogastric Adenocarcinoma | ACH-000793", + "Esophagogastric Adenocarcinoma | ACH-000847", + "Esophagogastric Adenocarcinoma | ACH-000880", + "Esophagogastric Adenocarcinoma | ACH-000898", + "Esophagogastric Adenocarcinoma | ACH-000911", + "Esophagogastric Adenocarcinoma | ACH-000919", + "Esophagogastric Adenocarcinoma | ACH-000932", + "Esophagogastric Adenocarcinoma | ACH-000948", + "Esophagogastric Adenocarcinoma | ACH-001368", + "Esophagogastric Adenocarcinoma | ACH-001496", + "Esophagogastric Adenocarcinoma | ACH-001497", + "Esophagogastric Adenocarcinoma | ACH-001500", + "Esophagogastric Adenocarcinoma | ACH-001544", + "Esophagogastric Adenocarcinoma | ACH-001653", + "Esophagogastric Adenocarcinoma | ACH-001654", + "Esophagogastric Adenocarcinoma | ACH-001664", + "Esophagogastric Adenocarcinoma | ACH-002141", + "Esophagogastric Adenocarcinoma | ACH-002161", + "Esophagogastric Adenocarcinoma | ACH-002202", + "Esophagogastric Adenocarcinoma | ACH-002446", + "Esophagogastric Adenocarcinoma | ACH-002705", + "Esophagogastric Adenocarcinoma | ACH-002706" + ], + "type": "scattergl", + "x": { + "bdata": "KoaZQC9qNMBw1tA/jXZwvdRGM0CQRqg/qqQNQHFKaEA+XU0/QySWP2aYA70+vPLA0QapvpPCBEBPEINAa5HKP3I5Bb8/nlNAS45eQJ5Dqj9d00tAUsTywLk9V0ALwvLAwCWMQNPURT/CqHhAbIHPP9eYf0CSKWRAZMUnQGiUdj+6a38/0I5OQJx+8b6tEPs/BXkBQNnFo0C1QKZAcmweQLj4GEC/AEBAIDotQFyygEA=", + "dtype": "f4" + }, + "y": { + "bdata": "AGfAv1HNsT7J2oA/1BMQPfTowL+UAxZA/U0avyNRPsAAwJA/3xu/vqk24r+rcau/4AgrQOu9nb+kqtW/OfgTwMB4B0AdwZW/ZH3+v514H8AyYZK/t6+qv+/uJ8Dj5qq/wtBDvro4/L9y65m/0dqmvq/wCcCEp22/P3IJwCJc6b8WUdy/3156PwCYyr9u+J2/6QsaQJqvSsBhSBHAhFpRv34Rhr407t++hIfGvoyKM78=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000053", + "ACH-000101", + "ACH-000226", + "ACH-000233", + "ACH-000338", + "ACH-000664", + "ACH-000773", + "ACH-001111", + "ACH-001119", + "ACH-001737" + ], + "hoverinfo": "text", + "marker": { + "color": "#FE00CE", + "size": 7 + }, + "mode": "markers", + "name": "Mature T and NK Neoplasms", + "text": [ + "Mature T and NK Neoplasms | ACH-000053", + "Mature T and NK Neoplasms | ACH-000101", + "Mature T and NK Neoplasms | ACH-000226", + "Mature T and NK Neoplasms | ACH-000233", + "Mature T and NK Neoplasms | ACH-000338", + "Mature T and NK Neoplasms | ACH-000664", + "Mature T and NK Neoplasms | ACH-000773", + "Mature T and NK Neoplasms | ACH-001111", + "Mature T and NK Neoplasms | ACH-001119", + "Mature T and NK Neoplasms | ACH-001737" + ], + "type": "scattergl", + "x": { + "bdata": "kZnlP2+nqEBMknFAuvBdQGr/jj9RsuJAmrENQOb/+z++WrK/hmjrPw==", + "dtype": "f4" + }, + "y": { + "bdata": "tmFQwKdKgMAN1j3AB/4hwLk+Or8kLIHAvropwMsj378zGhe/0hKxvg==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000054" + ], + "hoverinfo": "text", + "marker": { + "color": "#0DF9FF", + "size": 7 + }, + "mode": "markers", + "name": "Fibrosarcoma", + "text": [ + "Fibrosarcoma | ACH-000054" + ], + "type": "scattergl", + "x": { + "bdata": "PNxYPw==", + "dtype": "f4" + }, + "y": { + "bdata": "DSHFPw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000055", + "ACH-000095", + "ACH-000160", + "ACH-000211", + "ACH-000776", + "ACH-001020", + "ACH-001028", + "ACH-001031", + "ACH-001033", + "ACH-001053", + "ACH-001054", + "ACH-001232", + "ACH-001289", + "ACH-001670", + "ACH-001711" + ], + "hoverinfo": "text", + "marker": { + "color": "#F6F926", + "size": 7 + }, + "mode": "markers", + "name": "Embryonal Tumor", + "text": [ + "Embryonal Tumor | ACH-000055", + "Embryonal Tumor | ACH-000095", + "Embryonal Tumor | ACH-000160", + "Embryonal Tumor | ACH-000211", + "Embryonal Tumor | ACH-000776", + "Embryonal Tumor | ACH-001020", + "Embryonal Tumor | ACH-001028", + "Embryonal Tumor | ACH-001031", + "Embryonal Tumor | ACH-001033", + "Embryonal Tumor | ACH-001053", + "Embryonal Tumor | ACH-001054", + "Embryonal Tumor | ACH-001232", + "Embryonal Tumor | ACH-001289", + "Embryonal Tumor | ACH-001670", + "Embryonal Tumor | ACH-001711" + ], + "type": "scattergl", + "x": { + "bdata": "ibw6QBroEkA4irRAfyyLPZb46D+ejrw/0uaPQJ17kEBURLY/J0DBP77nl0CjfDe9KxjUP/8xOkCFPRVA", + "dtype": "f4" + }, + "y": { + "bdata": "0WiPvyMvKb8AIUM/ENcrQI1QfT/FTaI/7yUfv9/oYz/PRRE/uqc+vmJit79VYYVAs9OKviGNGT+/kg0/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000070", + "ACH-000151", + "ACH-000782", + "ACH-000922", + "ACH-000938", + "ACH-000960", + "ACH-001484", + "ACH-001520", + "ACH-001669", + "ACH-001735", + "ACH-001736", + "ACH-001993", + "ACH-002059" + ], + "hoverinfo": "text", + "marker": { + "color": "#FF9616", + "size": 7 + }, + "mode": "markers", + "name": "B-Lymphoblastic Leukemia/Lymphoma", + "text": [ + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000070", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000151", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000782", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000922", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000938", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000960", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001484", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001520", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001669", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001735", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001736", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001993", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-002059" + ], + "type": "scattergl", + "x": { + "bdata": "eseKQDzO9j+rn3lALfbDQH0Ko0A+wYpAkSFnQMFolkChZ7tA2M9NQDSNy0Cd//w/hnqAQA==", + "dtype": "f4" + }, + "y": { + "bdata": "so+AwHF9b8AWLHnATSSYwLuiocAAvYrA1lhHwKBpWsBjKIvANv+JwFY3nsDjc0fAuUFAwA==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000074", + "ACH-000076", + "ACH-000198", + "ACH-000295", + "ACH-000326", + "ACH-000551", + "ACH-000604", + "ACH-000920", + "ACH-000983", + "ACH-002061" + ], + "hoverinfo": "text", + "marker": { + "color": "#479B55", + "size": 7 + }, + "mode": "markers", + "name": "Myeloproliferative Neoplasms", + "text": [ + "Myeloproliferative Neoplasms | ACH-000074", + "Myeloproliferative Neoplasms | ACH-000076", + "Myeloproliferative Neoplasms | ACH-000198", + "Myeloproliferative Neoplasms | ACH-000295", + "Myeloproliferative Neoplasms | ACH-000326", + "Myeloproliferative Neoplasms | ACH-000551", + "Myeloproliferative Neoplasms | ACH-000604", + "Myeloproliferative Neoplasms | ACH-000920", + "Myeloproliferative Neoplasms | ACH-000983", + "Myeloproliferative Neoplasms | ACH-002061" + ], + "type": "scattergl", + "x": { + "bdata": "y4VSQKHkfkCcTfFACYRtP2RbjUA2u25AEyctQKPzlD9a4qlAwRBtQA==", + "dtype": "f4" + }, + "y": { + "bdata": "2f9GwOTuL8AlO5zAdLUgwKg8XMC82UjAr2sKwEFHmL/URoXAujoxwA==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000077", + "ACH-000583", + "ACH-001197", + "ACH-001642" + ], + "hoverinfo": "text", + "marker": { + "color": "#EEA6FB", + "size": 7 + }, + "mode": "markers", + "name": "Non-Hodgkin Lymphoma", + "text": [ + "Non-Hodgkin Lymphoma | ACH-000077", + "Non-Hodgkin Lymphoma | ACH-000583", + "Non-Hodgkin Lymphoma | ACH-001197", + "Non-Hodgkin Lymphoma | ACH-001642" + ], + "type": "scattergl", + "x": { + "bdata": "RAV+QLuy8sBfUS1AmUrJPw==", + "dtype": "f4" + }, + "y": { + "bdata": "nuzZv5vMq7/8YULAFh0GwA==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000078", + "ACH-000099", + "ACH-000120", + "ACH-000149", + "ACH-000203", + "ACH-000227", + "ACH-000259", + "ACH-000260", + "ACH-000310", + "ACH-000312", + "ACH-000341", + "ACH-000366", + "ACH-000804", + "ACH-001188", + "ACH-001300", + "ACH-001301", + "ACH-001302", + "ACH-001303", + "ACH-001338", + "ACH-001344", + "ACH-001354", + "ACH-001366", + "ACH-001367", + "ACH-001481", + "ACH-001548", + "ACH-001603", + "ACH-001674", + "ACH-002080", + "ACH-002083", + "ACH-002261", + "ACH-002278", + "ACH-002280", + "ACH-002282", + "ACH-002283", + "ACH-002284", + "ACH-002285", + "ACH-002922" + ], + "hoverinfo": "text", + "marker": { + "color": "#DC587D", + "size": 7 + }, + "mode": "markers", + "name": "Neuroblastoma", + "text": [ + "Neuroblastoma | ACH-000078", + "Neuroblastoma | ACH-000099", + "Neuroblastoma | ACH-000120", + "Neuroblastoma | ACH-000149", + "Neuroblastoma | ACH-000203", + "Neuroblastoma | ACH-000227", + "Neuroblastoma | ACH-000259", + "Neuroblastoma | ACH-000260", + "Neuroblastoma | ACH-000310", + "Neuroblastoma | ACH-000312", + "Neuroblastoma | ACH-000341", + "Neuroblastoma | ACH-000366", + "Neuroblastoma | ACH-000804", + "Neuroblastoma | ACH-001188", + "Neuroblastoma | ACH-001300", + "Neuroblastoma | ACH-001301", + "Neuroblastoma | ACH-001302", + "Neuroblastoma | ACH-001303", + "Neuroblastoma | ACH-001338", + "Neuroblastoma | ACH-001344", + "Neuroblastoma | ACH-001354", + "Neuroblastoma | ACH-001366", + "Neuroblastoma | ACH-001367", + "Neuroblastoma | ACH-001481", + "Neuroblastoma | ACH-001548", + "Neuroblastoma | ACH-001603", + "Neuroblastoma | ACH-001674", + "Neuroblastoma | ACH-002080", + "Neuroblastoma | ACH-002083", + "Neuroblastoma | ACH-002261", + "Neuroblastoma | ACH-002278", + "Neuroblastoma | ACH-002280", + "Neuroblastoma | ACH-002282", + "Neuroblastoma | ACH-002283", + "Neuroblastoma | ACH-002284", + "Neuroblastoma | ACH-002285", + "Neuroblastoma | ACH-002922" + ], + "type": "scattergl", + "x": { + "bdata": "UFyKP4JEekBzgac/o8FAQPj7Kb77VQzAUhuzQJnPHUC9svW/1R/IPx4gbTs0E/o/gnmLQIEiL0B3vHdAjkHHvjGtbj9/mB0+5haEQLW5BD+KJ8U/APQwQG/1VECjwjc9n6V4PiH+JEAEaUpAl8jywFYHpUC0cpxAUqGKQOQFiECHcV1A/XIjQPTd8sAnQQlBSiFVQA==", + "dtype": "f4" + }, + "y": { + "bdata": "hVWhvtdvWr8hXNE/WGtiPyQrFT8T/Ri/tm2fv7sP3z9pcyc+2AmPv0ZyfT/xAyi+6YkPv5cqiT/9Vnq+VaizP1X1Xr6pb0c+yob4v2iexj8lOA29fNvCvouDfL9Saw1AFR4pP8loBD4gwNK/UGirv8a0F0D0g5y/rK+5vv39Zb9aLn++Ldu1P5LOqr/ph/M+WT6Wvw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000082", + "ACH-000359", + "ACH-000364", + "ACH-000410", + "ACH-000748", + "ACH-001001", + "ACH-001526", + "ACH-001715", + "ACH-001814", + "ACH-002067", + "ACH-002069", + "ACH-002471", + "ACH-002834" + ], + "hoverinfo": "text", + "marker": { + "color": "#D626FF", + "size": 7 + }, + "mode": "markers", + "name": "Osteosarcoma", + "text": [ + "Osteosarcoma | ACH-000082", + "Osteosarcoma | ACH-000359", + "Osteosarcoma | ACH-000364", + "Osteosarcoma | ACH-000410", + "Osteosarcoma | ACH-000748", + "Osteosarcoma | ACH-001001", + "Osteosarcoma | ACH-001526", + "Osteosarcoma | ACH-001715", + "Osteosarcoma | ACH-001814", + "Osteosarcoma | ACH-002067", + "Osteosarcoma | ACH-002069", + "Osteosarcoma | ACH-002471", + "Osteosarcoma | ACH-002834" + ], + "type": "scattergl", + "x": { + "bdata": "EnVawMOUMcDiTxpADp+MP5wg7z+jKbNAbqTPvwOL5r9wLgvALquoP1StSr6meHK+RtzywA==", + "dtype": "f4" + }, + "y": { + "bdata": "QxswQIzgH0DaOTlAKN31P82cl0AWuxu/S8kEQNwSFEDOGFtA84k5P90HaEDuvf8/dQ+qvw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000086", + "ACH-000092", + "ACH-000153", + "ACH-000319", + "ACH-000331", + "ACH-000335", + "ACH-000367", + "ACH-000569", + "ACH-000645", + "ACH-000648", + "ACH-001547", + "ACH-001555", + "ACH-001556", + "ACH-001557", + "ACH-001558", + "ACH-001559", + "ACH-001560", + "ACH-001562", + "ACH-001977", + "ACH-001992", + "ACH-002033" + ], + "hoverinfo": "text", + "marker": { + "color": "#6E899C", + "size": 7 + }, + "mode": "markers", + "name": "Pleural Mesothelioma", + "text": [ + "Pleural Mesothelioma | ACH-000086", + "Pleural Mesothelioma | ACH-000092", + "Pleural Mesothelioma | ACH-000153", + "Pleural Mesothelioma | ACH-000319", + "Pleural Mesothelioma | ACH-000331", + "Pleural Mesothelioma | ACH-000335", + "Pleural Mesothelioma | ACH-000367", + "Pleural Mesothelioma | ACH-000569", + "Pleural Mesothelioma | ACH-000645", + "Pleural Mesothelioma | ACH-000648", + "Pleural Mesothelioma | ACH-001547", + "Pleural Mesothelioma | ACH-001555", + "Pleural Mesothelioma | ACH-001556", + "Pleural Mesothelioma | ACH-001557", + "Pleural Mesothelioma | ACH-001558", + "Pleural Mesothelioma | ACH-001559", + "Pleural Mesothelioma | ACH-001560", + "Pleural Mesothelioma | ACH-001562", + "Pleural Mesothelioma | ACH-001977", + "Pleural Mesothelioma | ACH-001992", + "Pleural Mesothelioma | ACH-002033" + ], + "type": "scattergl", + "x": { + "bdata": "ImwZQIuoAcBTe7K/QTeqv+c9OD+dNw5AOMfywPV0TD91Ce2/yq6OP5m5Kr8eA6U97IXOP8afVD+J2fLAgsLywHra8sBIxfLAF79+QAAuQkAv6zbA", + "dtype": "f4" + }, + "y": { + "bdata": "5XcEQIBPJEDI01ZAspNiQOJKGkDeEPs+VP+rv165bz8TVD9AFGYNQG1BfkDfRzVA49qIP+baNEDeyqq/H46qv3ilqr8dnaq/dlcHv35Zej+R9oc/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000090", + "ACH-000115", + "ACH-000956", + "ACH-000977", + "ACH-000979", + "ACH-001422", + "ACH-001627", + "ACH-001648", + "ACH-001649" + ], + "hoverinfo": "text", + "marker": { + "color": "#00B5F7", + "size": 7 + }, + "mode": "markers", + "name": "Prostate Adenocarcinoma", + "text": [ + "Prostate Adenocarcinoma | ACH-000090", + "Prostate Adenocarcinoma | ACH-000115", + "Prostate Adenocarcinoma | ACH-000956", + "Prostate Adenocarcinoma | ACH-000977", + "Prostate Adenocarcinoma | ACH-000979", + "Prostate Adenocarcinoma | ACH-001422", + "Prostate Adenocarcinoma | ACH-001627", + "Prostate Adenocarcinoma | ACH-001648", + "Prostate Adenocarcinoma | ACH-001649" + ], + "type": "scattergl", + "x": { + "bdata": "Qx5RPLnXUsAjDwBAGFSZQBp4mz+jInPAhLrywHHG8sC75fLA", + "dtype": "f4" + }, + "y": { + "bdata": "CzfJP0aODz4te76/ZnG/vxHlbj8DVC+/hC6rv6wSq7/FGau/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000096", + "ACH-000172", + "ACH-000533", + "ACH-000597", + "ACH-001099", + "ACH-001128", + "ACH-001211", + "ACH-001212", + "ACH-001532" + ], + "hoverinfo": "text", + "marker": { + "color": "#B68E00", + "size": 7 + }, + "mode": "markers", + "name": "Rhabdoid Cancer", + "text": [ + "Rhabdoid Cancer | ACH-000096", + "Rhabdoid Cancer | ACH-000172", + "Rhabdoid Cancer | ACH-000533", + "Rhabdoid Cancer | ACH-000597", + "Rhabdoid Cancer | ACH-001099", + "Rhabdoid Cancer | ACH-001128", + "Rhabdoid Cancer | ACH-001211", + "Rhabdoid Cancer | ACH-001212", + "Rhabdoid Cancer | ACH-001532" + ], + "type": "scattergl", + "x": { + "bdata": "KC8dQOZq5T92lqdAPdU+QBx0s0AjmglAIPAaQM3byz+GFZ9A", + "dtype": "f4" + }, + "y": { + "bdata": 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"qXQqQFUJJkC3nuo/NOU5QIYyA7/KMpdAOpZ7QNwtOECMSsU/giAaQOOIFECPO25A37yjQA==", + "dtype": "f4" + }, + "y": { + "bdata": "bPFCvwcwqT1p1Gs/EpI+vhoIfkDJjea+1rBhv2kaMT9o7AY++0vrvp/xsz8YnZS/nOiovg==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000108", + "ACH-000685" + ], + "hoverinfo": "text", + "marker": { + "color": "#FF0092", + "size": 7 + }, + "mode": "markers", + "name": "Adenosquamous Carcinoma of the Pancreas", + "text": [ + "Adenosquamous Carcinoma of the Pancreas | ACH-000108", + "Adenosquamous Carcinoma of the Pancreas | ACH-000685" + ], + "type": "scattergl", + "x": { + "bdata": "lUUdwEgzN0A=", + "dtype": "f4" + }, + "y": { + "bdata": "nnF5P1tXFUA=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000133", + "ACH-001310", + "ACH-001453", + "ACH-002210", + "ACH-002247", + "ACH-002462", + "ACH-002463", + "ACH-002464", + "ACH-002465", + "ACH-002467" + ], + "hoverinfo": "text", + "marker": { + "color": "#22FFA7", + "size": 7 + }, + "mode": "markers", + "name": "Non-Cancerous", + "text": [ + "Non-Cancerous | ACH-000133", + "Non-Cancerous | ACH-001310", + "Non-Cancerous | ACH-001453", + "Non-Cancerous | ACH-002210", + "Non-Cancerous | ACH-002247", + "Non-Cancerous | ACH-002462", + "Non-Cancerous | ACH-002463", + "Non-Cancerous | ACH-002464", + "Non-Cancerous | ACH-002465", + "Non-Cancerous | ACH-002467" + ], + "type": "scattergl", + "x": { + "bdata": "xpyUPBm98sAHz1w/koekQLDJ8sDb3vLA+NnywMPV8sCF1PLAB9/ywA==", + "dtype": "f4" + }, + "y": { + "bdata": "DslqQBMhq7+sQA1A/LdgwGbCqr8mIqu/sUyrv90brL+yi6u/ylOrvw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000141", + "ACH-001607", + "ACH-001619", + "ACH-001850", + "ACH-001861", + "ACH-001961" + ], + "hoverinfo": "text", + "marker": { + "color": "#E3EE9E", + "size": 7 + }, + "mode": "markers", + "name": "Intracholecystic Papillary Neoplasm", + "text": [ + "Intracholecystic Papillary Neoplasm | ACH-000141", + "Intracholecystic Papillary Neoplasm | ACH-001607", + "Intracholecystic Papillary Neoplasm | ACH-001619", + "Intracholecystic Papillary Neoplasm | ACH-001850", + "Intracholecystic Papillary Neoplasm | ACH-001861", + "Intracholecystic Papillary Neoplasm | ACH-001961" + ], + "type": "scattergl", + "x": { + "bdata": "xNbywAldL0DOXdq/eU8xQJ6x8sBfE/s/", + "dtype": "f4" + }, + "y": { + "bdata": "kQmrvzzujL+Vag1AmPI2vuvxqr8/nh6/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000145", + "ACH-000505", + "ACH-002785" + ], + "hoverinfo": "text", + "marker": { + "color": "#86CE00", + "size": 7 + }, + "mode": "markers", + "name": "Leiomyosarcoma", + "text": [ + "Leiomyosarcoma | ACH-000145", + "Leiomyosarcoma | ACH-000505", + "Leiomyosarcoma | ACH-002785" + ], + "type": "scattergl", + "x": { + "bdata": "AiMRwNwxQ8C4Iey/", + "dtype": "f4" + }, + "y": { + "bdata": "GXs6QN11QkAodWw/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000159", + "ACH-000189", + "ACH-000234", + "ACH-000246", + "ACH-000250", + "ACH-000262", + "ACH-000272", + "ACH-000313", + "ACH-000317", + "ACH-000375", + "ACH-000385", + "ACH-000411", + "ACH-000433", + "ACH-000459", + "ACH-000484", + "ACH-000495", + "ACH-000649", + "ACH-000684", + "ACH-000709", + "ACH-000792", + "ACH-000907", + "ACH-001163", + "ACH-001194", + "ACH-001398", + "ACH-001687", + "ACH-001688", + "ACH-002150", + "ACH-002189", + "ACH-002533" + ], + "hoverinfo": "text", + "marker": { + "color": "#BC7196", + "size": 7 + }, + "mode": "markers", + "name": "Renal Cell Carcinoma", + "text": [ + "Renal Cell Carcinoma | ACH-000159", + "Renal Cell Carcinoma | ACH-000189", + "Renal Cell Carcinoma | ACH-000234", + "Renal Cell Carcinoma | ACH-000246", + "Renal Cell Carcinoma | ACH-000250", + "Renal Cell Carcinoma | ACH-000262", + "Renal Cell Carcinoma | ACH-000272", + "Renal Cell Carcinoma | ACH-000313", + "Renal Cell Carcinoma | ACH-000317", + "Renal Cell Carcinoma | ACH-000375", + "Renal Cell Carcinoma | ACH-000385", + "Renal Cell Carcinoma | ACH-000411", + "Renal Cell Carcinoma | ACH-000433", + "Renal Cell Carcinoma | ACH-000459", + "Renal Cell Carcinoma | ACH-000484", + "Renal Cell Carcinoma | ACH-000495", + "Renal Cell Carcinoma | ACH-000649", + "Renal Cell Carcinoma | ACH-000684", + "Renal Cell Carcinoma | ACH-000709", + "Renal Cell Carcinoma | ACH-000792", + "Renal Cell Carcinoma | ACH-000907", + "Renal Cell Carcinoma | ACH-001163", + "Renal Cell Carcinoma | ACH-001194", + "Renal Cell Carcinoma | ACH-001398", + "Renal Cell Carcinoma | ACH-001687", + "Renal Cell Carcinoma | ACH-001688", + "Renal Cell Carcinoma | ACH-002150", + "Renal Cell Carcinoma | ACH-002189", + "Renal Cell Carcinoma | ACH-002533" + ], + "type": "scattergl", + "x": { + "bdata": "iFm1v3ff8sAKpB7Aq8DywNyv8sDQt/LAuc7ywHSHOcC5u/LA1OV1QGs+Sz4ieps/xIBtv98pvMDy3fLAQgjFv3ZD8T+uFQu/i+YkwNTE9T5Kv1XAiGOqPxC88sDIc1e+osTywHTC8sD2wfLAQBpXwKOMQkA=", + "dtype": "f4" + }, + "y": { + "bdata": "OxmZPwgTq7/qY0pAPJCrvwpCq78hFqu/W+mqv9ODC0AUj6u/bEubPN+NCkAVYhNAqhhKQEdNJj/ayaq/Ro4xQGIKEkDuC1NAoYcUQMJHj0BzcXFAY2Wuvzz4qr91Vm8/9E6rv7Owq79U8aq/EakbQH3cXb4=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000163", + "ACH-000181", + "ACH-000188", + "ACH-000207", + "ACH-000228", + "ACH-000238", + "ACH-000415", + "ACH-000472", + "ACH-000500", + "ACH-000503", + "ACH-000518", + "ACH-000546", + "ACH-000548", + "ACH-000549", + "ACH-000606", + "ACH-000618", + "ACH-000619", + "ACH-000630", + "ACH-000682", + "ACH-000732", + "ACH-000735", + "ACH-000740", + "ACH-000762", + "ACH-000771", + "ACH-000778", + "ACH-000794", + "ACH-000832", + "ACH-000836", + "ACH-000846", + "ACH-001228", + "ACH-001229", + "ACH-001331", + "ACH-001332", + "ACH-001346", + "ACH-001347", + "ACH-001385", + "ACH-001509", + "ACH-001510", + "ACH-001511", + "ACH-001542", + "ACH-001543", + "ACH-001625", + "ACH-001626", + "ACH-001641", + "ACH-001675", + "ACH-001690", + "ACH-001691", + "ACH-001692", + "ACH-001694", + "ACH-001695", + "ACH-001696", + "ACH-001698", + "ACH-001699", + "ACH-001701", + "ACH-002029", + "ACH-002030", + "ACH-002042", + "ACH-002043", + "ACH-002044", + "ACH-002045", + "ACH-002212", + "ACH-002249", + "ACH-002250", + "ACH-002251", + "ACH-002265", + "ACH-002294", + "ACH-002295", + "ACH-002296", + "ACH-002297", + "ACH-002298", + "ACH-002305" + ], + "hoverinfo": "text", + "marker": { + "color": "#7E7DCD", + "size": 7 + }, + "mode": "markers", + "name": "Head and Neck Squamous Cell Carcinoma", + "text": [ + "Head and Neck Squamous Cell Carcinoma | ACH-000163", + "Head and Neck Squamous Cell Carcinoma | ACH-000181", + "Head and Neck Squamous Cell Carcinoma | ACH-000188", + "Head and Neck Squamous Cell Carcinoma | ACH-000207", + "Head and Neck Squamous Cell Carcinoma | ACH-000228", + "Head and Neck Squamous Cell Carcinoma | ACH-000238", + "Head and Neck Squamous Cell Carcinoma | ACH-000415", + "Head and Neck Squamous Cell Carcinoma | ACH-000472", + "Head and Neck Squamous Cell Carcinoma | ACH-000500", + "Head and Neck Squamous Cell Carcinoma | ACH-000503", + "Head and Neck Squamous Cell Carcinoma | ACH-000518", + "Head and Neck Squamous Cell Carcinoma | ACH-000546", + "Head and Neck Squamous Cell Carcinoma | ACH-000548", + "Head and Neck Squamous Cell Carcinoma | ACH-000549", + "Head and Neck Squamous Cell Carcinoma | ACH-000606", + "Head and Neck Squamous Cell Carcinoma | ACH-000618", + "Head and Neck Squamous Cell Carcinoma | ACH-000619", + "Head and Neck Squamous Cell Carcinoma | ACH-000630", + "Head and Neck Squamous Cell Carcinoma | ACH-000682", + "Head and Neck Squamous Cell Carcinoma | ACH-000732", + "Head and Neck Squamous Cell Carcinoma | ACH-000735", + "Head and Neck Squamous Cell Carcinoma | ACH-000740", + "Head and Neck Squamous Cell Carcinoma | ACH-000762", + "Head and Neck Squamous Cell Carcinoma | ACH-000771", + "Head and Neck Squamous Cell Carcinoma | ACH-000778", + "Head and Neck Squamous Cell Carcinoma | ACH-000794", + "Head and Neck Squamous Cell Carcinoma | ACH-000832", + "Head and Neck Squamous Cell Carcinoma | ACH-000836", + "Head and Neck Squamous Cell Carcinoma | ACH-000846", + "Head and Neck Squamous Cell Carcinoma | ACH-001228", + "Head and Neck Squamous Cell Carcinoma | ACH-001229", + "Head and Neck Squamous Cell Carcinoma | ACH-001331", + "Head and Neck Squamous Cell Carcinoma | ACH-001332", + "Head and Neck Squamous Cell Carcinoma | ACH-001346", + "Head and Neck Squamous Cell Carcinoma | ACH-001347", + "Head and Neck Squamous Cell Carcinoma | ACH-001385", + "Head and Neck Squamous Cell Carcinoma | ACH-001509", + "Head and Neck Squamous Cell Carcinoma | ACH-001510", + "Head and Neck Squamous Cell Carcinoma | ACH-001511", + "Head and Neck Squamous Cell Carcinoma | ACH-001542", + "Head and Neck Squamous Cell Carcinoma | ACH-001543", + "Head and Neck Squamous Cell Carcinoma | ACH-001625", + "Head and Neck Squamous Cell Carcinoma | ACH-001626", + "Head and Neck Squamous Cell Carcinoma | ACH-001641", + "Head and Neck Squamous Cell Carcinoma | ACH-001675", + "Head and Neck Squamous Cell Carcinoma | ACH-001690", + "Head and Neck Squamous Cell Carcinoma | ACH-001691", + "Head and Neck Squamous Cell Carcinoma | ACH-001692", + "Head and Neck Squamous Cell Carcinoma | ACH-001694", + "Head and Neck Squamous Cell Carcinoma | ACH-001695", + "Head and Neck Squamous Cell Carcinoma | ACH-001696", + "Head and Neck Squamous Cell Carcinoma | ACH-001698", + "Head and Neck Squamous Cell Carcinoma | ACH-001699", + "Head and Neck Squamous Cell Carcinoma | ACH-001701", + "Head and Neck Squamous Cell Carcinoma | ACH-002029", + "Head and Neck Squamous Cell Carcinoma | ACH-002030", + "Head and Neck Squamous Cell Carcinoma | ACH-002042", + "Head and Neck Squamous Cell Carcinoma | ACH-002043", + "Head and Neck Squamous Cell Carcinoma | ACH-002044", + "Head and Neck Squamous Cell Carcinoma | ACH-002045", + "Head and Neck Squamous Cell Carcinoma | ACH-002212", + "Head and Neck Squamous Cell Carcinoma | ACH-002249", + "Head and Neck Squamous Cell Carcinoma | ACH-002250", + "Head and Neck Squamous Cell Carcinoma | ACH-002251", + "Head and Neck Squamous Cell Carcinoma | ACH-002265", + "Head and Neck Squamous Cell Carcinoma | ACH-002294", + "Head and Neck Squamous Cell Carcinoma | ACH-002295", + "Head and Neck Squamous Cell Carcinoma | ACH-002296", + "Head and Neck Squamous Cell Carcinoma | ACH-002297", + "Head and Neck Squamous Cell Carcinoma | ACH-002298", + "Head and Neck Squamous Cell Carcinoma | ACH-002305" + ], + "type": "scattergl", + "x": { + "bdata": "IlGvvfQ1rj/+Wb4/CczywC3o8sDUZmg/Fc/ywNEWkL8miAq/gLzywGasUEBEnixAWAGtv2w/8j+UJCZA63GiQIxzOEBWUhFAuCM8QB6qiD8oYVA/biaNP3cUQD8GvfLAjmXHv2QIBEATP6lAaVzUP4N3dEB7Kay/Ir0FQHDX8sBG1PLAd6DTP/Zj4T/pHsFAiDIYv4mo0T89dJi/E8WIQOim4D9Z8h7AReAgwDTR8sCmq8M/wLBMQP6TZL6D24ZA7bUoQNzz3T/Olt0/WO3fP1LDr0DlxilAERaaQFm9WkDcLt6/dAYmQAUmw0AugRdA0crywJVHQUAtz5Y/7nsMQKnM8sAlGvA/7RfwvQ99o0A2/UBAYQNrQOfe8sA=", + "dtype": "f4" + }, + "y": { + "bdata": "GJd0QLfCtD7qTL8/ACGrvy7Sqr9HojZAoHiqvwnABUAbFLA/7Pqqvy7S0T+fPd0+DkzhPynzJD8zb5c/TeGVvoNAjT+L2JRA36UuP5P0lT9lVuc/TBaAPxcmvj/iSqu/NnMBQOGDnj+4bZY/Dg9NP6JfTz6fpJQ/zLOUPr9zqr+8Kau//ckQQEI2sj9gq6O/3xUjQL5GOkB2HSNAZWhsP+oy6j8p8dc/j5yOP+oRq7+2LTNACjiIP5RGnUCCpl0/QSWjP4T1Pz8BSxBA5hEDQKQ+BL/aqEI/1JE6PyzLaD/65Pw/KT7qPeWiGMDxEb8+WAGrv8Kq2D+dLn49Ay4FQGeDq7/skk0/GjTzP7PQJz/S91k/0Gp5PXLQqr8=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000174", + "ACH-000191", + "ACH-001306", + "ACH-001307", + "ACH-001356", + "ACH-001443", + "ACH-002041" + ], + "hoverinfo": "text", + "marker": { + "color": "#FC6955", + "size": 7 + }, + "mode": "markers", + "name": "Anaplastic Thyroid Cancer", + "text": [ + "Anaplastic Thyroid Cancer | ACH-000174", + "Anaplastic Thyroid Cancer | ACH-000191", + "Anaplastic Thyroid Cancer | ACH-001306", + "Anaplastic Thyroid Cancer | ACH-001307", + "Anaplastic Thyroid Cancer | ACH-001356", + "Anaplastic Thyroid Cancer | ACH-001443", + "Anaplastic Thyroid Cancer | ACH-002041" + ], + "type": "scattergl", + "x": { + "bdata": "Jcs/P0u0kz+XX2K/r5sPwM9wZsACtIc9nYvUvg==", + "dtype": "f4" + }, + "y": { + "bdata": "HsMGQOEBA0BZpnZA/JHSP1cDWj8AVPA/VXRpQA==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000182", + "ACH-000377", + "ACH-001862", + "ACH-002023" + ], + "hoverinfo": "text", + "marker": { + "color": "#E48F72", + "size": 7 + }, + "mode": "markers", + "name": "Ampullary Carcinoma", + "text": [ + "Ampullary Carcinoma | ACH-000182", + "Ampullary Carcinoma | ACH-000377", + "Ampullary Carcinoma | ACH-001862", + "Ampullary Carcinoma | ACH-002023" + ], + "type": "scattergl", + "x": { + "bdata": "4szywHC08sArakG/uNjiPw==", + "dtype": "f4" + }, + "y": { + "bdata": "Ceuqv1E3q7+AyuM+Zu6Dvw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000187", + "ACH-000257", + "ACH-000290", + "ACH-000292", + "ACH-000355", + "ACH-000431", + "ACH-000514", + "ACH-000515", + "ACH-000525", + "ACH-000559", + "ACH-000639", + "ACH-000695", + "ACH-000698", + "ACH-000749", + "ACH-000767", + "ACH-000775", + "ACH-000790", + "ACH-000800", + "ACH-000866", + "ACH-000871", + "ACH-000890", + "ACH-000912", + "ACH-001386", + "ACH-001549", + "ACH-002051", + "ACH-002052", + "ACH-002077" + ], + "hoverinfo": "text", + "marker": { + "color": "#2E91E5", + "size": 7 + }, + "mode": "markers", + "name": "Lung Neuroendocrine Tumor", + "text": [ + "Lung Neuroendocrine Tumor | ACH-000187", + "Lung Neuroendocrine Tumor | ACH-000257", + "Lung Neuroendocrine Tumor | ACH-000290", + "Lung Neuroendocrine Tumor | ACH-000292", + "Lung Neuroendocrine Tumor | ACH-000355", + "Lung Neuroendocrine Tumor | ACH-000431", + "Lung Neuroendocrine Tumor | ACH-000514", + "Lung Neuroendocrine Tumor | ACH-000515", + "Lung Neuroendocrine Tumor | ACH-000525", + "Lung Neuroendocrine Tumor | ACH-000559", + "Lung Neuroendocrine Tumor | ACH-000639", + "Lung Neuroendocrine Tumor | ACH-000695", + "Lung Neuroendocrine Tumor | ACH-000698", + "Lung Neuroendocrine Tumor | ACH-000749", + "Lung Neuroendocrine Tumor | ACH-000767", + "Lung Neuroendocrine Tumor | ACH-000775", + "Lung Neuroendocrine Tumor | ACH-000790", + "Lung Neuroendocrine Tumor | ACH-000800", + "Lung Neuroendocrine Tumor | ACH-000866", + "Lung Neuroendocrine Tumor | ACH-000871", + "Lung Neuroendocrine Tumor | ACH-000890", + "Lung Neuroendocrine Tumor | ACH-000912", + "Lung Neuroendocrine Tumor | ACH-001386", + "Lung Neuroendocrine Tumor | ACH-001549", + "Lung Neuroendocrine Tumor | ACH-002051", + "Lung Neuroendocrine Tumor | ACH-002052", + "Lung Neuroendocrine Tumor | ACH-002077" + ], + "type": "scattergl", + "x": { + "bdata": "uHgBQAA+jr25G9s/tuWaQBpOk0BCgcM+JtRXv3mmDECGrrc/IOyMvxmujEDMhaO/eYg2QEhLLEDDtoS/S00RQOwqP0D1SdI/T2iUQGJriUCh/FK/rjcYQMKIzj6R3zE/vd0ewNk42L50XLe/", + "dtype": "f4" + }, + "y": { + "bdata": "2GMzwLV+lr8WegjA9hkIP+jXQb9Q0ia/0HCvvx2Utr8ybai/ljV2v/K0Q8CgKEm/OjIswHEVb77S1dm/n1qwvnGvzb+q0pc/qrHdvw+Bo7/PY0JASD81PwcNr7/nd6S/lxyhv3Xs0L/LuB2/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000192", + "ACH-000293", + "ACH-000302", + "ACH-000397", + "ACH-000407", + "ACH-000435", + "ACH-000831", + "ACH-000864", + "ACH-000879", + "ACH-000928", + "ACH-000941", + "ACH-000946", + "ACH-000961", + "ACH-000965", + "ACH-000972", + "ACH-000974", + "ACH-000978", + "ACH-000984", + "ACH-000988", + "ACH-000993", + "ACH-000994", + "ACH-000996", + "ACH-001495", + "ACH-001517", + "ACH-001518", + "ACH-002026", + "ACH-002027", + "ACH-002046" + ], + "hoverinfo": "text", + "marker": { + "color": "#E15F99", + "size": 7 + }, + "mode": "markers", + "name": "Endometrial Carcinoma", + "text": [ + "Endometrial Carcinoma | ACH-000192", + "Endometrial Carcinoma | ACH-000293", + "Endometrial Carcinoma | ACH-000302", + "Endometrial Carcinoma | ACH-000397", + "Endometrial Carcinoma | ACH-000407", + "Endometrial Carcinoma | ACH-000435", + "Endometrial Carcinoma | ACH-000831", + "Endometrial Carcinoma | ACH-000864", + "Endometrial Carcinoma | ACH-000879", + "Endometrial Carcinoma | ACH-000928", + "Endometrial Carcinoma | ACH-000941", + "Endometrial Carcinoma | ACH-000946", + "Endometrial Carcinoma | ACH-000961", + "Endometrial Carcinoma | ACH-000965", + "Endometrial Carcinoma | ACH-000972", + "Endometrial Carcinoma | ACH-000974", + "Endometrial Carcinoma | ACH-000978", + "Endometrial Carcinoma | ACH-000984", + "Endometrial Carcinoma | ACH-000988", + "Endometrial Carcinoma | ACH-000993", + "Endometrial Carcinoma | ACH-000994", + "Endometrial Carcinoma | ACH-000996", + "Endometrial Carcinoma | ACH-001495", + "Endometrial Carcinoma | ACH-001517", + "Endometrial Carcinoma | ACH-001518", + "Endometrial Carcinoma | ACH-002026", + "Endometrial Carcinoma | ACH-002027", + "Endometrial Carcinoma | ACH-002046" + ], + "type": "scattergl", + "x": { + "bdata": "ZTcuwCzRLsDBcVu8TuEAv6aAtT6YD3W/drbywG21EEDZ3V5AYZFaQApj+L+P3RtA+REyQJp7sUCL2PLA+pRWQPJwzT7YVuW/uXrFve9fMT6uyPLAnf2dviX/wr8mBHHAIuHywKrySUDSLbQ/gCDwvg==", + "dtype": "f4" + }, + "y": { + "bdata": 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ACH-001538", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001673", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001834", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001835", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001836", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001838", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001839", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001841", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001842", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001843", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001844", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001848", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001849", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001852", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001856", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001857", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001858", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001863", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001864", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001959", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001960", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001997", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-002647" + ], + "type": "scattergl", + "x": { + "bdata": "ZMDywAfM8sBKwvLADe+SvmLwqz4XkTI/RcdRPxyIZ0Dx4fLAmN7ywJ3W8sBY2PLABdTywD7H8sAkF9C+I9TywCbF8sC20PLA4dDywE4jjEBZWJc/X6zxP2OY5j/Lz/LAeBorP/twtEDSSwZADKvywBTK8j8=", + "dtype": "f4" + }, + "y": { + "bdata": "s1qrv2/Xqr+SB6u/GzU/P067pj/+rilAUp4iQGwmJcCdZKq/KLaqv6b7qr+V7aq/cwqrv08Aq79vQg5A4CurvzmHq7/Za6u/swerv9PDxz6JI+Y/7ATPPddm1z1Zuqq/leADvndMBb91KwRAjLWrv41Kxj8=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000217", + "ACH-000221", + "ACH-000316", + "ACH-000361", + 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Carcinoma | ACH-000493", + "Hepatocellular Carcinoma | ACH-000537", + "Hepatocellular Carcinoma | ACH-000577", + "Hepatocellular Carcinoma | ACH-000620", + "Hepatocellular Carcinoma | ACH-000734", + "Hepatocellular Carcinoma | ACH-000848", + "Hepatocellular Carcinoma | ACH-001318", + "Hepatocellular Carcinoma | ACH-002523" + ], + "type": "scattergl", + "x": { + "bdata": "C8IYQLSbnEDLQwM/r8ouP+Q1TcCdpbq/DVD+P7pqHj4X2yxANUxjv0J6rb/+zlVAXTfFv25pzD3xjsU/7iBvwPY/4T8dmIlAexSEQA6oE0Bx5sM/", + "dtype": "f4" + }, + "y": { + "bdata": "+cqaPv8JDr9wwItAC26nP0F4U0AfMS9AdtCGQP6lSEDZxE0+olJoP7t6OkAF5ck/AaBSQDY4N0D/ygJAuZ4eQCMOyzviuRK/DDxpv71zDD/7PpdA", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000305", + "ACH-000318", + "ACH-000408", + "ACH-000452", + "ACH-000488", + "ACH-000544", + "ACH-000561", + "ACH-000605", + "ACH-000637", + "ACH-000647", + "ACH-000693", + "ACH-000694", + "ACH-000717", + "ACH-000777", + "ACH-000784", + "ACH-000809", + "ACH-000823", + "ACH-000824", + "ACH-000855", + 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Squamous Cell Carcinoma | ACH-000784", + "Esophageal Squamous Cell Carcinoma | ACH-000809", + "Esophageal Squamous Cell Carcinoma | ACH-000823", + "Esophageal Squamous Cell Carcinoma | ACH-000824", + "Esophageal Squamous Cell Carcinoma | ACH-000855", + "Esophageal Squamous Cell Carcinoma | ACH-000865", + "Esophageal Squamous Cell Carcinoma | ACH-000873", + "Esophageal Squamous Cell Carcinoma | ACH-000917", + "Esophageal Squamous Cell Carcinoma | ACH-002243", + "Esophageal Squamous Cell Carcinoma | ACH-002263" + ], + "type": "scattergl", + "x": { + "bdata": "ApApP+4tBEA2dR1A6dCDvErrtEDU7yxAeWvtP8TxlT+nhmM+eqbqviH4sEA8uShAkQIsPCHEF0ASU1pARmB7QEn/VkA62qs/VtxSQEpAPUA7GURAE9Y+QD/G9D8/4CJA", + "dtype": "f4" + }, + "y": { + "bdata": "mT2SPxgRJj+bFio/Yj31P5jeLb9vaaw/NxiGvbg1oD+0YQxAX34GP5Z9sz6CQk0/XYjcP+1QYj8JJBI/TxfQvqSHD70Yrak/KBlHP16K9T9/oBa/E4ghv5xF4j9DLd6+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000456" + ], + "hoverinfo": "text", + "marker": { + "color": "#B68100", + 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"name": "Cervical Squamous Cell Carcinoma", + "text": [ + "Cervical Squamous Cell Carcinoma | ACH-000490", + "Cervical Squamous Cell Carcinoma | ACH-000556", + "Cervical Squamous Cell Carcinoma | ACH-001333", + "Cervical Squamous Cell Carcinoma | ACH-001334", + "Cervical Squamous Cell Carcinoma | ACH-001335", + "Cervical Squamous Cell Carcinoma | ACH-001336", + "Cervical Squamous Cell Carcinoma | ACH-001360", + "Cervical Squamous Cell Carcinoma | ACH-001402", + "Cervical Squamous Cell Carcinoma | ACH-001451", + "Cervical Squamous Cell Carcinoma | ACH-001515", + "Cervical Squamous Cell Carcinoma | ACH-001651", + "Cervical Squamous Cell Carcinoma | ACH-001652", + "Cervical Squamous Cell Carcinoma | ACH-002020" + ], + "type": "scattergl", + "x": { + "bdata": "B5f2P2pOGT+EsDxATgaiQCSpDEBchKc/GaKtwDv4jkC20fLAii1XPgVSicCURY4/l5ESvg==", + "dtype": "f4" + }, + "y": { + "bdata": "/tQJQBUDUr9ZPTA/43edv3antj7vgIU/8cQjPZvjnb+gFqu/qgDYvrDJEr9TNcI/Ay7KPQ==", + "dtype": "f4" + } + }, + { + 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7 + }, + "mode": "markers", + "name": "Hepatoblastoma", + "text": [ + "Hepatoblastoma | ACH-000671", + "Hepatoblastoma | ACH-000739" + ], + "type": "scattergl", + "x": { + "bdata": "li6PQKDngz8=", + "dtype": "f4" + }, + "y": { + "bdata": "UBloPzV9XL0=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000702", + "ACH-000754", + "ACH-001685" + ], + "hoverinfo": "text", + "marker": { + "color": "#FC0080", + "size": 7 + }, + "mode": "markers", + "name": "Hodgkin Lymphoma", + "text": [ + "Hodgkin Lymphoma | ACH-000702", + "Hodgkin Lymphoma | ACH-000754", + "Hodgkin Lymphoma | ACH-001685" + ], + "type": "scattergl", + "x": { + "bdata": "2a2yPvcujD+LipC/", + "dtype": "f4" + }, + "y": { + "bdata": "Icz9v9uCN8A6VBbA", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000716", + "ACH-000903", + "ACH-001528" + ], + "hoverinfo": "text", + "marker": { + "color": "#B2828D", + "size": 7 + }, + "mode": "markers", + "name": "Well-Differentiated Thyroid Cancer", + "text": [ + 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"Acute Myeloid Leukemia | ACH-000005", + "Acute Myeloid Leukemia | ACH-000045", + "Acute Myeloid Leukemia | ACH-000113", + "Acute Myeloid Leukemia | ACH-000146", + "Acute Myeloid Leukemia | ACH-000168", + "Acute Myeloid Leukemia | ACH-000190", + "Acute Myeloid Leukemia | ACH-000195", + "Acute Myeloid Leukemia | ACH-000263", + "Acute Myeloid Leukemia | ACH-000294", + "Acute Myeloid Leukemia | ACH-000336", + "Acute Myeloid Leukemia | ACH-000362", + "Acute Myeloid Leukemia | ACH-000387", + "Acute Myeloid Leukemia | ACH-000406", + "Acute Myeloid Leukemia | ACH-000498", + "Acute Myeloid Leukemia | ACH-000557", + "Acute Myeloid Leukemia | ACH-000602", + "Acute Myeloid Leukemia | ACH-000770", + "Acute Myeloid Leukemia | ACH-001036", + "Acute Myeloid Leukemia | ACH-001129", + "Acute Myeloid Leukemia | ACH-001574", + "Acute Myeloid Leukemia | ACH-001577", + "Acute Myeloid Leukemia | ACH-001613", + "Acute Myeloid Leukemia | ACH-001618", + "Acute Myeloid Leukemia | ACH-001647", + "Acute Myeloid Leukemia | ACH-001656" + ], + "type": "scattergl", + "x": { + "bdata": "+rUtP7CYfz5NbAJAteo1QOzUmz4B0Y0+5V1pP/Gv5D5HgAA9LuCBP36kG0DGEPo/fyxAP3IIBUABT0c+xvPLvrMdaT/0gtQ/sLqMP+z03j3cfgFAwiVjP4xd1T9NRpA/p8zGP66bvj8=", + "dtype": "f4" + }, + "y": { + "bdata": "fSqVvoqDgj4Dgpy/juD3v1/Pzj1XiaI+4ZrAvd0ht7yWIi0/lm4VvyHyxL+S/MC/SSGivmv4s7/snhI/AwyDP6EKuL4dhI6/Ze8Bv2mSGT877p+/GyJAvgI7YL/braG+3WqFv/SBYr8=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000007", + "ACH-000009", + "ACH-000202", + "ACH-000249", + "ACH-000252", + "ACH-000253", + "ACH-000286", + "ACH-000296", + "ACH-000350", + "ACH-000381", + "ACH-000403", + "ACH-000421", + "ACH-000467", + "ACH-000470", + "ACH-000489", + "ACH-000491", + "ACH-000501", + "ACH-000532", + "ACH-000552", + "ACH-000565", + "ACH-000651", + "ACH-000683", + "ACH-000722", + "ACH-000798", + "ACH-000820", + "ACH-000926", + "ACH-000935", + "ACH-000943", + "ACH-000950", + "ACH-000957", + "ACH-000958", + "ACH-000959", + "ACH-000963", + "ACH-000969", + 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Adenocarcinoma | ACH-000381", + "Colorectal Adenocarcinoma | ACH-000403", + "Colorectal Adenocarcinoma | ACH-000421", + "Colorectal Adenocarcinoma | ACH-000467", + "Colorectal Adenocarcinoma | ACH-000470", + "Colorectal Adenocarcinoma | ACH-000489", + "Colorectal Adenocarcinoma | ACH-000491", + "Colorectal Adenocarcinoma | ACH-000501", + "Colorectal Adenocarcinoma | ACH-000532", + "Colorectal Adenocarcinoma | ACH-000552", + "Colorectal Adenocarcinoma | ACH-000565", + "Colorectal Adenocarcinoma | ACH-000651", + "Colorectal Adenocarcinoma | ACH-000683", + "Colorectal Adenocarcinoma | ACH-000722", + "Colorectal Adenocarcinoma | ACH-000798", + "Colorectal Adenocarcinoma | ACH-000820", + "Colorectal Adenocarcinoma | ACH-000926", + "Colorectal Adenocarcinoma | ACH-000935", + "Colorectal Adenocarcinoma | ACH-000943", + "Colorectal Adenocarcinoma | ACH-000950", + "Colorectal Adenocarcinoma | ACH-000957", + "Colorectal Adenocarcinoma | ACH-000958", + "Colorectal Adenocarcinoma | ACH-000959", + "Colorectal Adenocarcinoma | ACH-000963", + "Colorectal Adenocarcinoma | ACH-000969", + "Colorectal Adenocarcinoma | ACH-000970", + "Colorectal Adenocarcinoma | ACH-000971", + "Colorectal Adenocarcinoma | ACH-000985", + "Colorectal Adenocarcinoma | ACH-000986", + "Colorectal Adenocarcinoma | ACH-000991", + "Colorectal Adenocarcinoma | ACH-000997", + "Colorectal Adenocarcinoma | ACH-001039", + "Colorectal Adenocarcinoma | ACH-001061", + "Colorectal Adenocarcinoma | ACH-001081", + "Colorectal Adenocarcinoma | ACH-001345", + "Colorectal Adenocarcinoma | ACH-001399", + "Colorectal Adenocarcinoma | ACH-001454", + "Colorectal Adenocarcinoma | ACH-001458", + "Colorectal Adenocarcinoma | ACH-001459", + "Colorectal Adenocarcinoma | ACH-001460", + "Colorectal Adenocarcinoma | ACH-001461", + "Colorectal Adenocarcinoma | ACH-001786", + "Colorectal Adenocarcinoma | ACH-002024", + "Colorectal Adenocarcinoma | ACH-002025", + "Colorectal Adenocarcinoma | ACH-002233", + "Colorectal Adenocarcinoma | ACH-002535", + "Colorectal Adenocarcinoma | ACH-002654", + "Colorectal Adenocarcinoma | ACH-002659", + "Colorectal Adenocarcinoma | ACH-002660", + "Colorectal Adenocarcinoma | ACH-002662", + "Colorectal Adenocarcinoma | ACH-002664", + "Colorectal Adenocarcinoma | ACH-002669" + ], + "type": "scattergl", + "x": { + "bdata": "PymxP45Yoz4BxwM/+201wGAqhj7ijvY+bYa7PnhHzT42tje/GhldP3uN1b6scWO+6iEywOTrkr7E8pc+ucK/PBi9LL71Hrs+WTVAP4WQBz+njIs/vx4uvmFcWj+Q5DXA6R1VPpc7NsCDETLA+EQowPHLnj/msLA/tzE3P5gddT9pEAS/fCk1wIRqBT8dDgA/u+EQP4yBMMA/+s8+T5+qPwnFgj9ZgN0/ISs4wNjFiz+9cdo+2CUGvwKQ8D6RKPs+fDmjP6ATPr81wMy8TwDPPuztMMDLObw+4EHJPoJMmb2/xKA/lYO0Psb+pD8FHWY/po1qPw==", + "dtype": "f4" + }, + "y": { + "bdata": 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Carcinoma", + "text": [ + "Bladder Urothelial Carcinoma | ACH-000011", + "Bladder Urothelial Carcinoma | ACH-000018", + "Bladder Urothelial Carcinoma | ACH-000026", + "Bladder Urothelial Carcinoma | ACH-000127", + "Bladder Urothelial Carcinoma | ACH-000142", + "Bladder Urothelial Carcinoma | ACH-000242", + "Bladder Urothelial Carcinoma | ACH-000396", + "Bladder Urothelial Carcinoma | ACH-000473", + "Bladder Urothelial Carcinoma | ACH-000486", + "Bladder Urothelial Carcinoma | ACH-000522", + "Bladder Urothelial Carcinoma | ACH-000545", + "Bladder Urothelial Carcinoma | ACH-000547", + "Bladder Urothelial Carcinoma | ACH-000593", + "Bladder Urothelial Carcinoma | ACH-000720", + "Bladder Urothelial Carcinoma | ACH-000724", + "Bladder Urothelial Carcinoma | ACH-000741", + "Bladder Urothelial Carcinoma | ACH-000753", + "Bladder Urothelial Carcinoma | ACH-000802", + "Bladder Urothelial Carcinoma | ACH-000834", + "Bladder Urothelial Carcinoma | ACH-000862", + "Bladder Urothelial Carcinoma | ACH-000896", + "Bladder Urothelial Carcinoma | ACH-000905", + "Bladder Urothelial Carcinoma | ACH-001183", + "Bladder Urothelial Carcinoma | ACH-001407", + "Bladder Urothelial Carcinoma | ACH-001409", + "Bladder Urothelial Carcinoma | ACH-001412", + "Bladder Urothelial Carcinoma | ACH-001413", + "Bladder Urothelial Carcinoma | ACH-001414", + "Bladder Urothelial Carcinoma | ACH-001415", + "Bladder Urothelial Carcinoma | ACH-001416" + ], + "type": "scattergl", + "x": { + "bdata": "a2SrPrsmbT434gA/Qaa4P1Xo/D4Llu8+CH/EvjAUNcCJSoQ/qZ0xwDF4NMARPDg/xVvqPuCvGz8/dia/19TnPp5AqT+pI4E/LESYP1jkNsB/cws/wgE8P8iyMsDVYDDAB1Y4wDj+OMB5/TTAWjQxwFA5PMCxYjjA", + "dtype": "f4" + }, + "y": { + "bdata": "b7urPpHvAT/Xy4k+JvUqv/EiTj4zFbQ+qLeXPzyRQL9XeIi+DA1jv4KJS79VsTk+JwS+PkJSXj7bj60/AvspPqV3Br+9eyS+icPhvtheKL/TSyw+/WKyO/p0Yb+cn4O/4Tkcv+jiCb/SOUG/1sd5v+zryr53hxu/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000012", + "ACH-000015", + "ACH-000021", + "ACH-000029", + "ACH-000030", + "ACH-000035", + 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"Non-Small Cell Lung Cancer | ACH-000176", + "Non-Small Cell Lung Cancer | ACH-000251", + "Non-Small Cell Lung Cancer | ACH-000261", + "Non-Small Cell Lung Cancer | ACH-000264", + "Non-Small Cell Lung Cancer | ACH-000311", + "Non-Small Cell Lung Cancer | ACH-000337", + "Non-Small Cell Lung Cancer | ACH-000339", + "Non-Small Cell Lung Cancer | ACH-000343", + "Non-Small Cell Lung Cancer | ACH-000378", + "Non-Small Cell Lung Cancer | ACH-000390", + "Non-Small Cell Lung Cancer | ACH-000395", + "Non-Small Cell Lung Cancer | ACH-000414", + "Non-Small Cell Lung Cancer | ACH-000416", + "Non-Small Cell Lung Cancer | ACH-000434", + "Non-Small Cell Lung Cancer | ACH-000438", + "Non-Small Cell Lung Cancer | ACH-000442", + "Non-Small Cell Lung Cancer | ACH-000444", + "Non-Small Cell Lung Cancer | ACH-000448", + "Non-Small Cell Lung Cancer | ACH-000454", + "Non-Small Cell Lung Cancer | ACH-000463", + "Non-Small Cell Lung Cancer | ACH-000481", + "Non-Small Cell Lung Cancer | ACH-000496", + "Non-Small Cell Lung Cancer | ACH-000510", + "Non-Small Cell Lung Cancer | ACH-000511", + "Non-Small Cell Lung Cancer | ACH-000521", + "Non-Small Cell Lung Cancer | ACH-000528", + "Non-Small Cell Lung Cancer | ACH-000562", + "Non-Small Cell Lung Cancer | ACH-000563", + "Non-Small Cell Lung Cancer | ACH-000585", + "Non-Small Cell Lung Cancer | ACH-000587", + "Non-Small Cell Lung Cancer | ACH-000589", + "Non-Small Cell Lung Cancer | ACH-000596", + "Non-Small Cell Lung Cancer | ACH-000627", + "Non-Small Cell Lung Cancer | ACH-000638", + "Non-Small Cell Lung Cancer | ACH-000662", + "Non-Small Cell Lung Cancer | ACH-000665", + "Non-Small Cell Lung Cancer | ACH-000666", + "Non-Small Cell Lung Cancer | ACH-000667", + "Non-Small Cell Lung Cancer | ACH-000672", + "Non-Small Cell Lung Cancer | ACH-000677", + "Non-Small Cell Lung Cancer | ACH-000681", + "Non-Small Cell Lung Cancer | ACH-000700", + "Non-Small Cell Lung Cancer | ACH-000706", + "Non-Small Cell Lung Cancer | ACH-000718", + "Non-Small Cell Lung Cancer | ACH-000747", + "Non-Small Cell Lung Cancer | ACH-000757", + "Non-Small Cell Lung Cancer | ACH-000766", + "Non-Small Cell Lung Cancer | ACH-000769", + "Non-Small Cell Lung Cancer | ACH-000774", + "Non-Small Cell Lung Cancer | ACH-000781", + "Non-Small Cell Lung Cancer | ACH-000785", + "Non-Small Cell Lung Cancer | ACH-000787", + "Non-Small Cell Lung Cancer | ACH-000791", + "Non-Small Cell Lung Cancer | ACH-000826", + "Non-Small Cell Lung Cancer | ACH-000837", + "Non-Small Cell Lung Cancer | ACH-000840", + "Non-Small Cell Lung Cancer | ACH-000841", + "Non-Small Cell Lung Cancer | ACH-000843", + "Non-Small Cell Lung Cancer | ACH-000845", + "Non-Small Cell Lung Cancer | ACH-000851", + "Non-Small Cell Lung Cancer | ACH-000853", + "Non-Small Cell Lung Cancer | ACH-000858", + "Non-Small Cell Lung Cancer | ACH-000860", + "Non-Small Cell Lung Cancer | ACH-000861", + "Non-Small Cell Lung Cancer | ACH-000867", + "Non-Small Cell Lung Cancer | ACH-000869", + "Non-Small Cell Lung Cancer | ACH-000872", + "Non-Small Cell Lung Cancer | ACH-000878", + "Non-Small Cell Lung Cancer | ACH-000886", + "Non-Small Cell Lung Cancer | ACH-000888", + "Non-Small Cell Lung Cancer | ACH-000894", + "Non-Small Cell Lung Cancer | ACH-000900", + "Non-Small Cell Lung Cancer | ACH-000901", + "Non-Small Cell Lung Cancer | ACH-000916", + "Non-Small Cell Lung Cancer | ACH-000921", + "Non-Small Cell Lung Cancer | ACH-000924", + "Non-Small Cell Lung Cancer | ACH-000929", + "Non-Small Cell Lung Cancer | ACH-000945", + "Non-Small Cell Lung Cancer | ACH-000975", + "Non-Small Cell Lung Cancer | ACH-000980", + "Non-Small Cell Lung Cancer | ACH-001075", + "Non-Small Cell Lung Cancer | ACH-001137", + "Non-Small Cell Lung Cancer | ACH-001233", + "Non-Small Cell Lung Cancer | ACH-002035", + "Non-Small Cell Lung Cancer | ACH-002156", + "Non-Small Cell Lung Cancer | ACH-002522", + "Non-Small Cell Lung Cancer | ACH-002526", + "Non-Small Cell Lung Cancer | ACH-002531", + "Non-Small Cell Lung Cancer | ACH-002650", + "Non-Small Cell Lung Cancer | ACH-003012" + ], + "type": "scattergl", + "x": { + "bdata": "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", + "dtype": "f4" + }, + "y": { + "bdata": 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"ACH-000827", + "ACH-000881", + "ACH-000882", + "ACH-000884", + "ACH-000899", + "ACH-000915", + "ACH-000968", + "ACH-001041", + "ACH-001190", + "ACH-001239", + "ACH-001522", + "ACH-001563", + "ACH-001566", + "ACH-001567", + "ACH-001568", + "ACH-001570", + "ACH-001645", + "ACH-001970", + "ACH-001972", + "ACH-001973", + "ACH-001975", + "ACH-001982", + "ACH-001986", + "ACH-001990", + "ACH-002001", + "ACH-002002", + "ACH-002003", + "ACH-002004", + "ACH-002005", + "ACH-002084", + "ACH-002143", + "ACH-002458", + "ACH-002460", + "ACH-002461", + "ACH-002508", + "ACH-002510", + "ACH-002511", + "ACH-002512", + "ACH-002847", + "ACH-002928" + ], + "hoverinfo": "text", + "marker": { + "color": "#19D3F3", + "size": 7 + }, + "mode": "markers", + "name": "Melanoma", + "text": [ + "Melanoma | ACH-000014", + "Melanoma | ACH-000219", + "Melanoma | ACH-000274", + "Melanoma | ACH-000304", + "Melanoma | ACH-000322", + "Melanoma | ACH-000348", + "Melanoma | ACH-000401", + "Melanoma | ACH-000404", + "Melanoma | ACH-000425", + "Melanoma | ACH-000441", + "Melanoma | ACH-000450", + "Melanoma | ACH-000458", + "Melanoma | ACH-000477", + "Melanoma | ACH-000550", + "Melanoma | ACH-000579", + "Melanoma | ACH-000580", + "Melanoma | ACH-000614", + "Melanoma | ACH-000632", + "Melanoma | ACH-000661", + "Melanoma | ACH-000765", + "Melanoma | ACH-000788", + "Melanoma | ACH-000799", + "Melanoma | ACH-000801", + "Melanoma | ACH-000805", + "Melanoma | ACH-000810", + "Melanoma | ACH-000822", + "Melanoma | ACH-000827", + "Melanoma | ACH-000881", + "Melanoma | ACH-000882", + "Melanoma | ACH-000884", + "Melanoma | ACH-000899", + "Melanoma | ACH-000915", + "Melanoma | ACH-000968", + "Melanoma | ACH-001041", + "Melanoma | ACH-001190", + "Melanoma | ACH-001239", + "Melanoma | ACH-001522", + "Melanoma | ACH-001563", + "Melanoma | ACH-001566", + "Melanoma | ACH-001567", + "Melanoma | ACH-001568", + "Melanoma | ACH-001570", + "Melanoma | ACH-001645", + "Melanoma | ACH-001970", + "Melanoma | ACH-001972", + "Melanoma | ACH-001973", + "Melanoma | ACH-001975", + "Melanoma | ACH-001982", + "Melanoma | ACH-001986", + "Melanoma | ACH-001990", + "Melanoma | ACH-002001", + "Melanoma | ACH-002002", + "Melanoma | ACH-002003", + "Melanoma | ACH-002004", + "Melanoma | ACH-002005", + "Melanoma | ACH-002084", + "Melanoma | ACH-002143", + "Melanoma | ACH-002458", + "Melanoma | ACH-002460", + "Melanoma | ACH-002461", + "Melanoma | ACH-002508", + "Melanoma | ACH-002510", + "Melanoma | ACH-002511", + "Melanoma | ACH-002512", + "Melanoma | ACH-002847", + "Melanoma | ACH-002928" + ], + "type": "scattergl", + "x": { + "bdata": "wIZwPwrOCUCZ4C6/IkRkPknklz+lRba+GRFjP70HM8ChWDTAD8S2P2WHMMApJDPAxRvdPQ4HLb9umDbA2HjgPZLpnj/KWE4/6rMwwLF6CD+hPgQ/agByPeDZMsD2ExU/fql2PrH1S7/AbQM/yHCfP0Djyj9SMo8/rjkwwM/cuz+22KE/q09PP06whb53SaA/iiwFP/XxM8BTXTPAdxw0wJYwNsCtMTDAkv8aPtl4PD9OxCrAOuMxwOYoLsBDp5M/ZNOyP0OEzT81d7s/pPQHQJBsQj9ekjTAj4qTP1Bahr2KFoO/GqlfP/GyWj+PEDQ9yrKcvs6dnD/lyne/WH4OPhGo5zvh/D+/", + "dtype": "f4" + }, + "y": { + "bdata": 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"ACH-001393", + "ACH-001394", + "ACH-001396", + "ACH-001419", + "ACH-001662", + "ACH-001683", + "ACH-001819", + "ACH-002179", + "ACH-002399", + "ACH-002401" + ], + "hoverinfo": "text", + "marker": { + "color": "#FF6692", + "size": 7 + }, + "mode": "markers", + "name": "Invasive Breast Carcinoma", + "text": [ + "Invasive Breast Carcinoma | ACH-000017", + "Invasive Breast Carcinoma | ACH-000019", + "Invasive Breast Carcinoma | ACH-000028", + "Invasive Breast Carcinoma | ACH-000097", + "Invasive Breast Carcinoma | ACH-000111", + "Invasive Breast Carcinoma | ACH-000147", + "Invasive Breast Carcinoma | ACH-000148", + "Invasive Breast Carcinoma | ACH-000212", + "Invasive Breast Carcinoma | ACH-000223", + "Invasive Breast Carcinoma | ACH-000248", + "Invasive Breast Carcinoma | ACH-000258", + "Invasive Breast Carcinoma | ACH-000276", + "Invasive Breast Carcinoma | ACH-000277", + "Invasive Breast Carcinoma | ACH-000288", + "Invasive Breast Carcinoma | ACH-000330", + "Invasive Breast Carcinoma | ACH-000352", + "Invasive Breast Carcinoma | ACH-000374", + "Invasive Breast Carcinoma | ACH-000554", + "Invasive Breast Carcinoma | ACH-000573", + "Invasive Breast Carcinoma | ACH-000621", + "Invasive Breast Carcinoma | ACH-000668", + "Invasive Breast Carcinoma | ACH-000699", + "Invasive Breast Carcinoma | ACH-000711", + "Invasive Breast Carcinoma | ACH-000721", + "Invasive Breast Carcinoma | ACH-000768", + "Invasive Breast Carcinoma | ACH-000783", + "Invasive Breast Carcinoma | ACH-000849", + "Invasive Breast Carcinoma | ACH-000856", + "Invasive Breast Carcinoma | ACH-000876", + "Invasive Breast Carcinoma | ACH-000910", + "Invasive Breast Carcinoma | ACH-000934", + "Invasive Breast Carcinoma | ACH-001065", + "Invasive Breast Carcinoma | ACH-001388", + "Invasive Breast Carcinoma | ACH-001389", + "Invasive Breast Carcinoma | ACH-001390", + "Invasive Breast Carcinoma | ACH-001391", + "Invasive Breast Carcinoma | ACH-001392", + "Invasive Breast Carcinoma | ACH-001393", + "Invasive Breast Carcinoma | ACH-001394", + "Invasive Breast Carcinoma | ACH-001396", + "Invasive Breast Carcinoma | ACH-001419", + "Invasive Breast Carcinoma | ACH-001662", + "Invasive Breast Carcinoma | ACH-001683", + "Invasive Breast Carcinoma | ACH-001819", + "Invasive Breast Carcinoma | ACH-002179", + "Invasive Breast Carcinoma | ACH-002399", + "Invasive Breast Carcinoma | ACH-002401" + ], + "type": "scattergl", + "x": { + "bdata": "ty4IPkG2SD8wkr8/Ryr7PkxfkD9HrpU/IPKMPqLb2T4Fr8O+ytY0P0QcMb7ZmfC9A2nIPaU9CT9dRwM/j3f1Pn+ZQD+I5xW/Au0TP5Rfg7+4vfa98V0Rv7zDQD+lpYw/NtbjPg4COb+uRZk/opENQJd7OL6hX68/WUptv2iQ5D/GtQ2/EwUxwISDFz/XVEq/CU45wIwoM8CkKDjAlWA6wIppcj4a2PO8CDtuPg4osr78rY8/dS78PqoWUj8=", + "dtype": "f4" + }, + "y": { + "bdata": "Pn1sPuZ3PLzIXkW/BV3lPYBms76TddK+pDbtPq6BCD7e5zU/fnWpvY1JPT/QlUY/rZikPsJqtj7nbsy8ZuQNO2XTj70nfpI/EuTkOwR9vj8NS1I/TsFmP8s+qr4YUuS+RFMePkBkij/VOJu+WTSav+K/Uz+AuBu/Ny/YP9ZqV79KupE/Up58v/OMmD6NHKg/2BIHv5xSYr+PRCG/j23ZvhyXpT4rOfE+mKyxPsvJJD+q0uS+/zWcPseZIL4=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000022", + "ACH-000023", + "ACH-000042", + "ACH-000060", + "ACH-000085", + "ACH-000093", + "ACH-000094", + "ACH-000114", + "ACH-000118", + "ACH-000138", + "ACH-000139", + "ACH-000155", + "ACH-000164", + "ACH-000178", + "ACH-000213", + "ACH-000222", + "ACH-000235", + "ACH-000243", + "ACH-000265", + "ACH-000266", + "ACH-000281", + "ACH-000307", + "ACH-000320", + "ACH-000332", + "ACH-000354", + "ACH-000417", + "ACH-000468", + "ACH-000502", + "ACH-000517", + "ACH-000535", + "ACH-000599", + "ACH-000601", + "ACH-000652", + "ACH-001098", + "ACH-001107", + "ACH-001353", + "ACH-001375", + "ACH-001377", + "ACH-001379", + "ACH-001380", + "ACH-001382", + "ACH-001999", + "ACH-002039", + "ACH-002186", + "ACH-002672" + ], + "hoverinfo": "text", + "marker": { + "color": "#B6E880", + "size": 7 + }, + "mode": "markers", + "name": "Pancreatic Adenocarcinoma", + "text": [ + "Pancreatic Adenocarcinoma | ACH-000022", + "Pancreatic Adenocarcinoma | ACH-000023", + "Pancreatic Adenocarcinoma | ACH-000042", + "Pancreatic Adenocarcinoma | ACH-000060", + "Pancreatic Adenocarcinoma | ACH-000085", + "Pancreatic Adenocarcinoma | ACH-000093", + "Pancreatic Adenocarcinoma | ACH-000094", + "Pancreatic Adenocarcinoma | ACH-000114", + "Pancreatic Adenocarcinoma | ACH-000118", + "Pancreatic Adenocarcinoma | ACH-000138", + "Pancreatic Adenocarcinoma | ACH-000139", + "Pancreatic Adenocarcinoma | ACH-000155", + "Pancreatic Adenocarcinoma | ACH-000164", + "Pancreatic Adenocarcinoma | ACH-000178", + "Pancreatic Adenocarcinoma | ACH-000213", + "Pancreatic Adenocarcinoma | ACH-000222", + "Pancreatic Adenocarcinoma | ACH-000235", + "Pancreatic Adenocarcinoma | ACH-000243", + "Pancreatic Adenocarcinoma | ACH-000265", + "Pancreatic Adenocarcinoma | ACH-000266", + "Pancreatic Adenocarcinoma | ACH-000281", + "Pancreatic Adenocarcinoma | ACH-000307", + "Pancreatic Adenocarcinoma | ACH-000320", + "Pancreatic Adenocarcinoma | ACH-000332", + "Pancreatic Adenocarcinoma | ACH-000354", + "Pancreatic Adenocarcinoma | ACH-000417", + "Pancreatic Adenocarcinoma | ACH-000468", + "Pancreatic Adenocarcinoma | ACH-000502", + "Pancreatic Adenocarcinoma | ACH-000517", + "Pancreatic Adenocarcinoma | ACH-000535", + "Pancreatic Adenocarcinoma | ACH-000599", + "Pancreatic Adenocarcinoma | ACH-000601", + "Pancreatic Adenocarcinoma | ACH-000652", + "Pancreatic Adenocarcinoma | ACH-001098", + "Pancreatic Adenocarcinoma | ACH-001107", + "Pancreatic Adenocarcinoma | ACH-001353", + "Pancreatic Adenocarcinoma | ACH-001375", + "Pancreatic Adenocarcinoma | ACH-001377", + "Pancreatic Adenocarcinoma | ACH-001379", + "Pancreatic Adenocarcinoma | ACH-001380", + "Pancreatic Adenocarcinoma | ACH-001382", + "Pancreatic Adenocarcinoma | ACH-001999", + "Pancreatic Adenocarcinoma | ACH-002039", + "Pancreatic Adenocarcinoma | ACH-002186", + "Pancreatic Adenocarcinoma | ACH-002672" + ], + "type": "scattergl", + "x": { + "bdata": 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"ACH-000660", + "ACH-000697", + "ACH-000714", + "ACH-000763", + "ACH-000817", + "ACH-000821", + "ACH-000829", + "ACH-000838", + "ACH-000889", + "ACH-000914", + "ACH-000944", + "ACH-001450", + "ACH-001498", + "ACH-001533", + "ACH-001539", + "ACH-001616", + "ACH-001634", + "ACH-001639", + "ACH-001677", + "ACH-001707", + "ACH-001709", + "ACH-002055", + "ACH-002062", + "ACH-002214", + "ACH-002215", + "ACH-002478", + "ACH-002485", + "ACH-002500", + "ACH-002677", + "ACH-002678" + ], + "hoverinfo": "text", + "marker": { + "color": "#FF97FF", + "size": 7 + }, + "mode": "markers", + "name": "Mature B-Cell Neoplasms", + "text": [ + "Mature B-Cell Neoplasms | ACH-000024", + "Mature B-Cell Neoplasms | ACH-000106", + "Mature B-Cell Neoplasms | ACH-000124", + "Mature B-Cell Neoplasms | ACH-000167", + "Mature B-Cell Neoplasms | ACH-000183", + "Mature B-Cell Neoplasms | ACH-000204", + "Mature B-Cell Neoplasms | ACH-000271", + "Mature B-Cell Neoplasms | ACH-000315", + "Mature B-Cell Neoplasms | ACH-000334", + "Mature B-Cell Neoplasms | ACH-000346", + "Mature B-Cell Neoplasms | ACH-000363", + "Mature B-Cell Neoplasms | ACH-000365", + "Mature B-Cell Neoplasms | ACH-000371", + "Mature B-Cell Neoplasms | ACH-000398", + "Mature B-Cell Neoplasms | ACH-000402", + "Mature B-Cell Neoplasms | ACH-000405", + "Mature B-Cell Neoplasms | ACH-000426", + "Mature B-Cell Neoplasms | ACH-000436", + "Mature B-Cell Neoplasms | ACH-000512", + "Mature B-Cell Neoplasms | ACH-000541", + "Mature B-Cell Neoplasms | ACH-000567", + "Mature B-Cell Neoplasms | ACH-000576", + "Mature B-Cell Neoplasms | ACH-000588", + "Mature B-Cell Neoplasms | ACH-000653", + "Mature B-Cell Neoplasms | ACH-000654", + "Mature B-Cell Neoplasms | ACH-000656", + "Mature B-Cell Neoplasms | ACH-000660", + "Mature B-Cell Neoplasms | ACH-000697", + "Mature B-Cell Neoplasms | ACH-000714", + "Mature B-Cell Neoplasms | ACH-000763", + "Mature B-Cell Neoplasms | ACH-000817", + "Mature B-Cell Neoplasms | ACH-000821", + "Mature B-Cell Neoplasms | ACH-000829", + "Mature B-Cell Neoplasms | ACH-000838", + "Mature B-Cell Neoplasms | ACH-000889", + "Mature B-Cell Neoplasms | ACH-000914", + "Mature B-Cell Neoplasms | ACH-000944", + "Mature B-Cell Neoplasms | ACH-001450", + "Mature B-Cell Neoplasms | ACH-001498", + "Mature B-Cell Neoplasms | ACH-001533", + "Mature B-Cell Neoplasms | ACH-001539", + "Mature B-Cell Neoplasms | ACH-001616", + "Mature B-Cell Neoplasms | ACH-001634", + "Mature B-Cell Neoplasms | ACH-001639", + "Mature B-Cell Neoplasms | ACH-001677", + "Mature B-Cell Neoplasms | ACH-001707", + "Mature B-Cell Neoplasms | ACH-001709", + "Mature B-Cell Neoplasms | ACH-002055", + "Mature B-Cell Neoplasms | ACH-002062", + "Mature B-Cell Neoplasms | ACH-002214", + "Mature B-Cell Neoplasms | ACH-002215", + "Mature B-Cell Neoplasms | ACH-002478", + "Mature B-Cell Neoplasms | ACH-002485", + "Mature B-Cell Neoplasms | ACH-002500", + "Mature B-Cell Neoplasms | ACH-002677", + "Mature B-Cell Neoplasms | ACH-002678" + ], + "type": "scattergl", + "x": { + "bdata": "NsiSPwC+Pz8hXiFABlJxP3Eq7T/SW9w/wAEzQDOXaT8lb8+9VWLKP+b6mD4RNvc/jpa5P+24oT8SvVk/qZLSPxK1kj5r8TPAToyeP3xcVj+ROC7AL+zwPrdI3z/84ow/YJ+QP87RJ0BuqyBAn+e0P16xhj9EaDE/8datP0xhTz/h4S/ApqBKPz5uAUBjWQtA2ZPRP09ozj+RT9w/3ZYwwGjeLj88OAlAn04zwNlVij9apT8/KyAzwKiWGEDihJo/73FbP1dxBkDYKbM/TdyaPxqUiT+tY/w/kr4BQMyihT8=", + "dtype": "f4" + }, + "y": { + "bdata": "nU04v2ntF7x+Wb6/1RnFvqnEvL8mYpG/ojLzv8Sm4r6b9gU/fwQyv2iwj70GBra/J1RXv9XTD79vsFq+L5iLvy7FAb6XtVi/nFQev/6UXL66OI2/rKsivv3Nnr+ZayO/yzoRv4pO0L9PWMC/DLdev6XoJb9aGq2+dYxSv1ido74nqYq/hW7qvv5avb+cScK/JX5xv/xuWb+IfYi/Jid/vyQiOr7xoNm/D7ZUvyfjOr7MuxO+DY1jv2qC3r+FuCK/vQJjvmPjp7/JZ1e/n8k3v0jHBb9J+ai/FxLDv+Sg8r4=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000025", + "ACH-001067", + "ACH-002070" + ], + "hoverinfo": "text", + "marker": { + "color": "#FECB52", + "size": 7 + }, + "mode": "markers", + "name": "Meningothelial Tumor", + "text": [ + "Meningothelial Tumor | ACH-000025", + "Meningothelial Tumor | ACH-001067", + "Meningothelial Tumor | ACH-002070" + ], + "type": "scattergl", + "x": { + "bdata": "BkN0P2IBL8BrNME+", + "dtype": "f4" + }, + "y": { + "bdata": "dSz3vbf5iL9jX7k+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000036", + "ACH-000040", + "ACH-000067", + "ACH-000075", + "ACH-000098", + "ACH-000128", + "ACH-000137", + "ACH-000152", + "ACH-000200", + "ACH-000208", + "ACH-000215", + "ACH-000231", + "ACH-000232", + "ACH-000244", + "ACH-000269", + "ACH-000273", + "ACH-000323", + "ACH-000329", + "ACH-000368", + "ACH-000370", + "ACH-000376", + "ACH-000389", + "ACH-000437", + "ACH-000445", + "ACH-000455", + "ACH-000464", + "ACH-000469", + "ACH-000479", + "ACH-000504", + "ACH-000558", + "ACH-000570", + "ACH-000571", + "ACH-000591", + "ACH-000592", + "ACH-000595", + "ACH-000609", + "ACH-000622", + "ACH-000623", + "ACH-000631", + "ACH-000634", + "ACH-000655", + "ACH-000673", + "ACH-000676", + "ACH-000738", + "ACH-000756", + "ACH-000760", + "ACH-000807", + "ACH-000819", + "ACH-000863", + "ACH-000887", + "ACH-001016", + "ACH-001126", + "ACH-001172", + "ACH-001329", + "ACH-001605", + "ACH-001606", + "ACH-001608", + "ACH-001609", + "ACH-001610", + "ACH-001611", + "ACH-001622", + "ACH-001623", + "ACH-001624", + "ACH-002228", + "ACH-002229", + "ACH-002230", + "ACH-002257", + "ACH-002269", + "ACH-002304", + "ACH-002680" + ], + "hoverinfo": "text", + "marker": { + "color": "#FD3216", + "size": 7 + }, + "mode": "markers", + "name": "Diffuse Glioma", + "text": [ + "Diffuse Glioma | ACH-000036", + "Diffuse Glioma | ACH-000040", + "Diffuse Glioma | ACH-000067", + "Diffuse Glioma | ACH-000075", + "Diffuse Glioma | ACH-000098", + "Diffuse Glioma | ACH-000128", + "Diffuse Glioma | ACH-000137", + "Diffuse Glioma | ACH-000152", + "Diffuse Glioma | ACH-000200", + "Diffuse Glioma | ACH-000208", + "Diffuse Glioma | ACH-000215", + "Diffuse Glioma | ACH-000231", + "Diffuse Glioma | ACH-000232", + "Diffuse Glioma | ACH-000244", + "Diffuse Glioma | ACH-000269", + "Diffuse Glioma | ACH-000273", + "Diffuse Glioma | ACH-000323", + "Diffuse Glioma | ACH-000329", + "Diffuse Glioma | ACH-000368", + "Diffuse Glioma | ACH-000370", + "Diffuse Glioma | ACH-000376", + "Diffuse Glioma | ACH-000389", + "Diffuse Glioma | ACH-000437", + "Diffuse Glioma | ACH-000445", + "Diffuse Glioma | ACH-000455", + "Diffuse Glioma | ACH-000464", + "Diffuse Glioma | ACH-000469", + "Diffuse Glioma | ACH-000479", + "Diffuse Glioma | ACH-000504", + "Diffuse Glioma | ACH-000558", + "Diffuse Glioma | ACH-000570", + "Diffuse Glioma | ACH-000571", + "Diffuse Glioma | ACH-000591", + "Diffuse Glioma | ACH-000592", + "Diffuse Glioma | ACH-000595", + "Diffuse Glioma | ACH-000609", + "Diffuse Glioma | ACH-000622", + "Diffuse Glioma | ACH-000623", + "Diffuse Glioma | ACH-000631", + "Diffuse Glioma | ACH-000634", + "Diffuse Glioma | ACH-000655", + "Diffuse Glioma | ACH-000673", + "Diffuse Glioma | ACH-000676", + "Diffuse Glioma | ACH-000738", + "Diffuse Glioma | ACH-000756", + "Diffuse Glioma | ACH-000760", + "Diffuse Glioma | ACH-000807", + "Diffuse Glioma | ACH-000819", + "Diffuse Glioma | ACH-000863", + "Diffuse Glioma | ACH-000887", + "Diffuse Glioma | ACH-001016", + "Diffuse Glioma | ACH-001126", + "Diffuse Glioma | ACH-001172", + "Diffuse Glioma | ACH-001329", + "Diffuse Glioma | ACH-001605", + "Diffuse Glioma | ACH-001606", + "Diffuse Glioma | ACH-001608", + "Diffuse Glioma | ACH-001609", + "Diffuse Glioma | ACH-001610", + "Diffuse Glioma | ACH-001611", + "Diffuse Glioma | ACH-001622", + "Diffuse Glioma | ACH-001623", + "Diffuse Glioma | ACH-001624", + "Diffuse Glioma | ACH-002228", + "Diffuse Glioma | ACH-002229", + "Diffuse Glioma | ACH-002230", + "Diffuse Glioma | ACH-002257", + "Diffuse Glioma | ACH-002269", + "Diffuse Glioma | ACH-002304", + "Diffuse Glioma | ACH-002680" + ], + "type": "scattergl", + "x": { + "bdata": 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[ + "Sarcoma, NOS | ACH-000037" + ], + "type": "scattergl", + "x": { + "bdata": "YKEUvw==", + "dtype": "f4" + }, + "y": { + "bdata": "DF+/Pw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000039", + "ACH-000041", + "ACH-000052", + "ACH-000087", + "ACH-000210", + "ACH-000279", + "ACH-000391", + "ACH-000424", + "ACH-000499", + "ACH-001029", + "ACH-001038", + "ACH-001192", + "ACH-001193", + "ACH-001205", + "ACH-001283", + "ACH-001430", + "ACH-001431", + "ACH-002105", + "ACH-002106", + "ACH-002109", + "ACH-002110", + "ACH-002114", + "ACH-002116", + "ACH-002119", + "ACH-002160" + ], + "hoverinfo": "text", + "marker": { + "color": "#6A76FC", + "size": 7 + }, + "mode": "markers", + "name": "Ewing Sarcoma", + "text": [ + "Ewing Sarcoma | ACH-000039", + "Ewing Sarcoma | ACH-000041", + "Ewing Sarcoma | ACH-000052", + "Ewing Sarcoma | ACH-000087", + "Ewing Sarcoma | ACH-000210", + "Ewing Sarcoma | ACH-000279", + "Ewing Sarcoma | ACH-000391", + "Ewing Sarcoma | ACH-000424", + "Ewing Sarcoma | ACH-000499", + "Ewing Sarcoma | ACH-001029", + "Ewing Sarcoma | ACH-001038", + "Ewing Sarcoma | ACH-001192", + "Ewing Sarcoma | ACH-001193", + "Ewing Sarcoma | ACH-001205", + "Ewing Sarcoma | ACH-001283", + "Ewing Sarcoma | ACH-001430", + "Ewing Sarcoma | ACH-001431", + "Ewing Sarcoma | ACH-002105", + "Ewing Sarcoma | ACH-002106", + "Ewing Sarcoma | ACH-002109", + "Ewing Sarcoma | ACH-002110", + "Ewing Sarcoma | ACH-002114", + "Ewing Sarcoma | ACH-002116", + "Ewing Sarcoma | ACH-002119", + "Ewing Sarcoma | ACH-002160" + ], + "type": "scattergl", + "x": { + "bdata": "5HyQve9fPT7rWWM+IvSFP54S8D4hQq4/A7vCPxxv8j+INpA/RBjTPx75kT+FYCY/TIzSPuAKID+2OWw/3FzoPtVdTj/netk+fujFPwDMQD/M+QBARHo1wD8pNcC+ouQ/VZDcPw==", + "dtype": "f4" + }, + "y": { + "bdata": "/ERmPwqqKz8gjiY/q2bgvaov5j4OhwK/nx10vpMNGr8AyXC+O3MgvzoEqb4/uoE+jpa9PmD2KT1J0K29hzjDPnaf5L0K2Dc/ZLUgv94Haj57XF2/cgY+v/J1Pb/Ctii/7+4Svw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000047", + "ACH-000144", + "ACH-000216", + "ACH-000239", + "ACH-000247", + "ACH-000255", + "ACH-000303", + "ACH-000325", + "ACH-000344", + "ACH-000356", + "ACH-000383", + "ACH-000427", + "ACH-000466", + "ACH-000485", + "ACH-000507", + "ACH-000581", + "ACH-000616", + "ACH-000633", + "ACH-000736", + "ACH-000746", + "ACH-000758", + "ACH-000764", + "ACH-000793", + "ACH-000847", + "ACH-000880", + "ACH-000898", + "ACH-000911", + "ACH-000919", + "ACH-000932", + "ACH-000948", + "ACH-001368", + "ACH-001496", + "ACH-001497", + "ACH-001500", + "ACH-001544", + "ACH-001653", + "ACH-001654", + "ACH-001664", + "ACH-002141", + "ACH-002161", + "ACH-002202", + "ACH-002446", + "ACH-002705", + "ACH-002706" + ], + "hoverinfo": "text", + "marker": { + "color": "#FED4C4", + "size": 7 + }, + "mode": "markers", + "name": "Esophagogastric Adenocarcinoma", + "text": [ + "Esophagogastric Adenocarcinoma | ACH-000047", + "Esophagogastric Adenocarcinoma | ACH-000144", + "Esophagogastric Adenocarcinoma | ACH-000216", + "Esophagogastric Adenocarcinoma | ACH-000239", + "Esophagogastric Adenocarcinoma | ACH-000247", + "Esophagogastric Adenocarcinoma | ACH-000255", + "Esophagogastric Adenocarcinoma | ACH-000303", + "Esophagogastric Adenocarcinoma | ACH-000325", + "Esophagogastric Adenocarcinoma | ACH-000344", + "Esophagogastric Adenocarcinoma | ACH-000356", + "Esophagogastric Adenocarcinoma | ACH-000383", + "Esophagogastric Adenocarcinoma | ACH-000427", + "Esophagogastric Adenocarcinoma | ACH-000466", + "Esophagogastric Adenocarcinoma | ACH-000485", + "Esophagogastric Adenocarcinoma | ACH-000507", + "Esophagogastric Adenocarcinoma | ACH-000581", + "Esophagogastric Adenocarcinoma | ACH-000616", + "Esophagogastric Adenocarcinoma | ACH-000633", + "Esophagogastric Adenocarcinoma | ACH-000736", + "Esophagogastric Adenocarcinoma | ACH-000746", + "Esophagogastric Adenocarcinoma | ACH-000758", + "Esophagogastric Adenocarcinoma | ACH-000764", + "Esophagogastric Adenocarcinoma | ACH-000793", + "Esophagogastric Adenocarcinoma | ACH-000847", + "Esophagogastric Adenocarcinoma | ACH-000880", + "Esophagogastric Adenocarcinoma | ACH-000898", + "Esophagogastric Adenocarcinoma | ACH-000911", + "Esophagogastric Adenocarcinoma | ACH-000919", + "Esophagogastric Adenocarcinoma | ACH-000932", + "Esophagogastric Adenocarcinoma | ACH-000948", + "Esophagogastric Adenocarcinoma | ACH-001368", + "Esophagogastric Adenocarcinoma | ACH-001496", + "Esophagogastric Adenocarcinoma | ACH-001497", + "Esophagogastric Adenocarcinoma | ACH-001500", + "Esophagogastric Adenocarcinoma | ACH-001544", + "Esophagogastric Adenocarcinoma | ACH-001653", + "Esophagogastric Adenocarcinoma | ACH-001654", + "Esophagogastric Adenocarcinoma | ACH-001664", + "Esophagogastric Adenocarcinoma | ACH-002141", + "Esophagogastric Adenocarcinoma | ACH-002161", + "Esophagogastric Adenocarcinoma | ACH-002202", + "Esophagogastric Adenocarcinoma | ACH-002446", + "Esophagogastric Adenocarcinoma | ACH-002705", + "Esophagogastric Adenocarcinoma | ACH-002706" + ], + "type": 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+ "Mature T and NK Neoplasms | ACH-000226", + "Mature T and NK Neoplasms | ACH-000233", + "Mature T and NK Neoplasms | ACH-000338", + "Mature T and NK Neoplasms | ACH-000664", + "Mature T and NK Neoplasms | ACH-000773", + "Mature T and NK Neoplasms | ACH-001111", + "Mature T and NK Neoplasms | ACH-001119", + "Mature T and NK Neoplasms | ACH-001737" + ], + "type": "scattergl", + "x": { + "bdata": "w/RRP0TM5j9x3Lc/5rKhP7Xy/D5hARJAzPhuPxnvNz/1NZ++yX8zPw==", + "dtype": "f4" + }, + "y": { + "bdata": "CX/IvjNkh78QJlS/lw0iv6BQyT4pp62/yj3Zvoh6Cz3D43I/75TxPQ==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000054" + ], + "hoverinfo": "text", + "marker": { + "color": "#0DF9FF", + "size": 7 + }, + "mode": "markers", + "name": "Fibrosarcoma", + "text": [ + "Fibrosarcoma | ACH-000054" + ], + "type": "scattergl", + "x": { + "bdata": "Xb2cPg==", + "dtype": "f4" + }, + "y": { + "bdata": "2PABPw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000055", + "ACH-000095", + "ACH-000160", + "ACH-000211", + "ACH-000776", + "ACH-001020", + "ACH-001028", + "ACH-001031", + "ACH-001033", + "ACH-001053", + "ACH-001054", + "ACH-001232", + "ACH-001289", + "ACH-001670", + "ACH-001711" + ], + "hoverinfo": "text", + "marker": { + "color": "#F6F926", + "size": 7 + }, + "mode": "markers", + "name": "Embryonal Tumor", + "text": [ + "Embryonal Tumor | ACH-000055", + "Embryonal Tumor | ACH-000095", + "Embryonal Tumor | ACH-000160", + "Embryonal Tumor | ACH-000211", + "Embryonal Tumor | ACH-000776", + "Embryonal Tumor | ACH-001020", + "Embryonal Tumor | ACH-001028", + "Embryonal Tumor | ACH-001031", + "Embryonal Tumor | ACH-001033", + "Embryonal Tumor | ACH-001053", + "Embryonal Tumor | ACH-001054", + "Embryonal Tumor | ACH-001232", + "Embryonal Tumor | ACH-001289", + "Embryonal Tumor | ACH-001670", + "Embryonal Tumor | ACH-001711" + ], + "type": "scattergl", + "x": { + "bdata": "J8WEP0P6Xz//2OA/5R6aPSWYIT+tPQY//We+P+DJvj/qpyU/l18bP7Ziyz8j2AA9uvk0P14NgT+i1Eo/", + "dtype": "f4" + }, + "y": { + "bdata": "CwenvkQ2Lr5OaFu/WsE7PySRKj7i35g+uEIXvyqTFb8zmE8+mSwJPU8nUr/zUIs/ofHDPekKPb6OtoY+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000070", + "ACH-000151", + "ACH-000782", + "ACH-000922", + "ACH-000938", + "ACH-000960", + "ACH-001484", + "ACH-001520", + "ACH-001669", + "ACH-001735", + "ACH-001736", + "ACH-001993", + "ACH-002059" + ], + "hoverinfo": "text", + "marker": { + "color": "#FF9616", + "size": 7 + }, + "mode": "markers", + "name": "B-Lymphoblastic Leukemia/Lymphoma", + "text": [ + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000070", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000151", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000782", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000922", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000938", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000960", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001484", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001520", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001669", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001735", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001736", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001993", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-002059" + ], + "type": "scattergl", + "x": { + "bdata": "zSnTPzVNcz8uvbk/E4gKQGpV8j+lytg/BXGlP1VYzj/+fP8/H+OjPymGCUA5A2k/MN+7Pw==", + "dtype": "f4" + }, + "y": { + "bdata": "xTR/vxyTAr+8Ekq/TKrJv/jokL/9A2y/jZ4zvzMNa78I/6W//So6vyh6tb+YgbG+cUZQvw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000074", + "ACH-000076", + "ACH-000198", + "ACH-000295", + "ACH-000326", + "ACH-000551", + "ACH-000604", + "ACH-000920", + "ACH-000983", + "ACH-002061" + ], + "hoverinfo": "text", + "marker": { + "color": "#479B55", + "size": 7 + }, + "mode": "markers", + "name": "Myeloproliferative Neoplasms", + "text": [ + "Myeloproliferative Neoplasms | ACH-000074", + "Myeloproliferative Neoplasms | ACH-000076", + "Myeloproliferative Neoplasms | ACH-000198", + "Myeloproliferative Neoplasms | ACH-000295", + "Myeloproliferative Neoplasms | ACH-000326", + "Myeloproliferative Neoplasms | ACH-000551", + "Myeloproliferative Neoplasms | ACH-000604", + "Myeloproliferative Neoplasms | ACH-000920", + "Myeloproliferative Neoplasms | ACH-000983", + "Myeloproliferative Neoplasms | ACH-002061" + ], + "type": "scattergl", + "x": { + "bdata": "sTGYPxZyqj/zjR1ATKYGPzTrwj+qiak/eXpjP73FAz8B8+c/QSymPw==", + "dtype": "f4" + }, + "y": { + "bdata": "fh4hv2Z8Kb8ddN2/YQOTPdfsfL/O4Bm/QXJYvrfEPT5FRpi/R6YDvw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000077", + "ACH-000583", + "ACH-001197", + "ACH-001642" + ], + "hoverinfo": "text", + "marker": { + "color": "#EEA6FB", + "size": 7 + }, + "mode": "markers", + "name": "Non-Hodgkin Lymphoma", + "text": [ + "Non-Hodgkin Lymphoma | ACH-000077", + "Non-Hodgkin Lymphoma | ACH-000583", + "Non-Hodgkin Lymphoma | ACH-001197", + "Non-Hodgkin Lymphoma | ACH-001642" + ], + "type": "scattergl", + "x": { + "bdata": "OgKzPwCyI8CdJ48/JesyPw==", + "dtype": "f4" + }, + "y": { + "bdata": "/9oovw5V0r+ougS/V/CsvA==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000078", + "ACH-000099", + "ACH-000120", + "ACH-000149", + "ACH-000203", + "ACH-000227", + "ACH-000259", + "ACH-000260", + "ACH-000310", + "ACH-000312", + "ACH-000341", + "ACH-000366", + "ACH-000804", + "ACH-001188", + "ACH-001300", + "ACH-001301", + "ACH-001302", + "ACH-001303", + "ACH-001338", + "ACH-001344", + "ACH-001354", + "ACH-001366", + "ACH-001367", + "ACH-001481", + "ACH-001548", + "ACH-001603", + "ACH-001674", + "ACH-002080", + "ACH-002083", + "ACH-002261", + "ACH-002278", + "ACH-002280", + "ACH-002282", + "ACH-002283", + "ACH-002284", + "ACH-002285", + "ACH-002922" + ], + "hoverinfo": "text", + "marker": { + "color": "#DC587D", + "size": 7 + }, + "mode": "markers", + "name": "Neuroblastoma", + "text": [ + "Neuroblastoma | ACH-000078", + "Neuroblastoma | ACH-000099", + "Neuroblastoma | ACH-000120", + "Neuroblastoma | ACH-000149", + "Neuroblastoma | ACH-000203", + "Neuroblastoma | ACH-000227", + "Neuroblastoma | ACH-000259", + "Neuroblastoma | ACH-000260", + "Neuroblastoma | ACH-000310", + "Neuroblastoma | ACH-000312", + "Neuroblastoma | ACH-000341", + "Neuroblastoma | ACH-000366", + "Neuroblastoma | ACH-000804", + "Neuroblastoma | ACH-001188", + "Neuroblastoma | ACH-001300", + "Neuroblastoma | ACH-001301", + "Neuroblastoma | ACH-001302", + "Neuroblastoma | ACH-001303", + "Neuroblastoma | ACH-001338", + "Neuroblastoma | ACH-001344", + "Neuroblastoma | ACH-001354", + "Neuroblastoma | ACH-001366", + "Neuroblastoma | ACH-001367", + "Neuroblastoma | ACH-001481", + "Neuroblastoma | ACH-001548", + "Neuroblastoma | ACH-001603", + "Neuroblastoma | ACH-001674", + "Neuroblastoma | ACH-002080", + "Neuroblastoma | ACH-002083", + "Neuroblastoma | ACH-002261", + "Neuroblastoma | ACH-002278", + "Neuroblastoma | ACH-002280", + "Neuroblastoma | ACH-002282", + "Neuroblastoma | ACH-002283", + "Neuroblastoma | ACH-002284", + "Neuroblastoma | ACH-002285", + "Neuroblastoma | ACH-002922" + ], + "type": "scattergl", + "x": { + "bdata": "m1kbP34SqD9tt+k+wRKDP57ogT0vgsu+5AnmP4aRZz91B8++cVg3P95kWj2qlT0/lnK3P0SWdD8FI6g/vs0SvMan8D5qo2I+LrK5P259kj6XTSA/4p9qPzEmlT85EA4+pMkWPhP/eT8srJM/3aMywO+Jzj/DrNk/G0fQP7ejzD/sp6Q/E+ZaP5NgM8DlfyFAwZCWPw==", + "dtype": "f4" + }, + "y": { + "bdata": "BQ2OPmMv/b4UQXU+99mcvDTAKD856qA/tFZ3v18FLb6ca5c/09sgPZ++Aj/NFRE9OUcwvwTpcr6hKeC+/ZRCPxQWyj4uUQk/X1kEv7UK+T6tdDY+JpBFvj7PxL4+kAk/NK4YP+I25b3K1vy+EFxSv+TQvL5BPkq/Sy8Vv3VJAL//c+S+IYgcvXtIUr9ENpK/UX7jvg==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000082", + "ACH-000359", + "ACH-000364", + "ACH-000410", + "ACH-000748", + "ACH-001001", + "ACH-001526", + "ACH-001715", + "ACH-001814", + "ACH-002067", + "ACH-002069", + "ACH-002471", + "ACH-002834" + ], + "hoverinfo": "text", + "marker": { + "color": "#D626FF", + "size": 7 + }, + "mode": "markers", + "name": "Osteosarcoma", + "text": [ + "Osteosarcoma | ACH-000082", + "Osteosarcoma | ACH-000359", + "Osteosarcoma | ACH-000364", + "Osteosarcoma | ACH-000410", + "Osteosarcoma | ACH-000748", + "Osteosarcoma | ACH-001001", + "Osteosarcoma | ACH-001526", + "Osteosarcoma | ACH-001715", + "Osteosarcoma | ACH-001814", + "Osteosarcoma | ACH-002067", + "Osteosarcoma | ACH-002069", + "Osteosarcoma | ACH-002471", + "Osteosarcoma | ACH-002834" + ], + "type": "scattergl", + "x": { + "bdata": "iIiEv+/OTb/Yl0c/yCXgPsQFND+4+OE/EprBvpuiB78lsSq/ZUTdPrrhNr2ve5C7aVM4wA==", + "dtype": "f4" + }, + "y": { + "bdata": "O5zRP+sHrT8CqIo9GdyvPp1FAj/SXAa/rROPP13Mhz8Zq8E/rV+GPhWMQT9HzGc/fiYavw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000086", + "ACH-000092", + "ACH-000153", + "ACH-000319", + "ACH-000331", + "ACH-000335", + "ACH-000367", + "ACH-000569", + "ACH-000645", + "ACH-000648", + "ACH-001547", + "ACH-001555", + "ACH-001556", + "ACH-001557", + "ACH-001558", + "ACH-001559", + "ACH-001560", + "ACH-001562", + "ACH-001977", + "ACH-001992", + "ACH-002033" + ], + "hoverinfo": "text", + "marker": { + "color": "#6E899C", + "size": 7 + }, + "mode": "markers", + "name": "Pleural Mesothelioma", + "text": [ + "Pleural Mesothelioma | ACH-000086", + "Pleural Mesothelioma | ACH-000092", + "Pleural Mesothelioma | ACH-000153", + "Pleural Mesothelioma | ACH-000319", + "Pleural Mesothelioma | ACH-000331", + "Pleural Mesothelioma | ACH-000335", + "Pleural Mesothelioma | ACH-000367", + "Pleural Mesothelioma | ACH-000569", + "Pleural Mesothelioma | ACH-000645", + "Pleural Mesothelioma | ACH-000648", + "Pleural Mesothelioma | ACH-001547", + "Pleural Mesothelioma | ACH-001555", + "Pleural Mesothelioma | ACH-001556", + "Pleural Mesothelioma | ACH-001557", + "Pleural Mesothelioma | ACH-001558", + "Pleural Mesothelioma | ACH-001559", + "Pleural Mesothelioma | ACH-001560", + "Pleural Mesothelioma | ACH-001562", + "Pleural Mesothelioma | ACH-001977", + "Pleural Mesothelioma | ACH-001992", + "Pleural Mesothelioma | ACH-002033" + ], + "type": "scattergl", + "x": { + "bdata": "h88/P0wYCr/maMS+Xl61vgigiz6T7U0/GCk5wM3GqT7FFPy+jRPNPnShcb6/dn89WugUP0dBij4OczrA0/s2wKY5NMBN6zDA1G+jPwiEcT+wSUq/", + "dtype": "f4" + }, + "y": { + "bdata": "jfPtPUJbnj8D45Y/ty2SPyCD0T6nzRE+z2gGv6coAj+7N6A/Qgq7Pj9yRj+iOhk//gSHPvaPGj/HUf++ChExvychV7+ta4C/5kERvwwDKb5wOL8/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000090", + "ACH-000115", + "ACH-000956", + "ACH-000977", + "ACH-000979", + "ACH-001422", + "ACH-001627", + "ACH-001648", + "ACH-001649" + ], + "hoverinfo": "text", + "marker": { + "color": "#00B5F7", + "size": 7 + }, + "mode": "markers", + "name": "Prostate Adenocarcinoma", + "text": [ + "Prostate Adenocarcinoma | ACH-000090", + "Prostate Adenocarcinoma | ACH-000115", + "Prostate Adenocarcinoma | ACH-000956", + "Prostate Adenocarcinoma | ACH-000977", + "Prostate Adenocarcinoma | ACH-000979", + "Prostate Adenocarcinoma | ACH-001422", + "Prostate Adenocarcinoma | ACH-001627", + "Prostate Adenocarcinoma | ACH-001648", + "Prostate Adenocarcinoma | ACH-001649" + ], + "type": "scattergl", + "x": { + "bdata": "aZDAPF8mXb8lu1M/6fbKPxuS6D7/ZoK/a0IswDp6LcAZojbA", + "dtype": "f4" + }, + "y": { + "bdata": "fb4gPwLimT+eLEu9xFtTv6K0Sj5qAso/MySav9AHlL8X8SW/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000096", + "ACH-000172", + "ACH-000533", + "ACH-000597", + "ACH-001099", + "ACH-001128", + "ACH-001211", + "ACH-001212", + "ACH-001532" + ], + "hoverinfo": "text", + "marker": { + "color": "#B68E00", + "size": 7 + }, + "mode": "markers", + "name": "Rhabdoid Cancer", + "text": [ + "Rhabdoid Cancer | ACH-000096", + "Rhabdoid Cancer | ACH-000172", + "Rhabdoid Cancer | ACH-000533", + "Rhabdoid Cancer | ACH-000597", + "Rhabdoid Cancer | ACH-001099", + "Rhabdoid Cancer | ACH-001128", + "Rhabdoid Cancer | ACH-001211", + "Rhabdoid Cancer | ACH-001212", + "Rhabdoid Cancer | ACH-001532" + ], + "type": "scattergl", + "x": { + "bdata": "BFprPyOAHz/qLtI/X6h9Pz2v2j9ULD8/HMBjP3B/GT8+FM8/", + "dtype": "f4" + }, + "y": { + "bdata": "So8FPSP5mD4e9Tm/pBJBvoR+Rr8MpZi6Nekyvtl5iT5pYWW/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000100", + "ACH-000169", + "ACH-000607", + "ACH-000833", + "ACH-001050", + "ACH-001096", + "ACH-001184", + "ACH-001196", + "ACH-001740", + "ACH-001745", + "ACH-001750", + "ACH-001765", + "ACH-002048" + ], + "hoverinfo": "text", + "marker": { + "color": "#C9FBE5", + "size": 7 + }, + "mode": "markers", + "name": "Rhabdomyosarcoma", + "text": [ + "Rhabdomyosarcoma | ACH-000100", + "Rhabdomyosarcoma | ACH-000169", + "Rhabdomyosarcoma | ACH-000607", + "Rhabdomyosarcoma | ACH-000833", + "Rhabdomyosarcoma | ACH-001050", + "Rhabdomyosarcoma | ACH-001096", + "Rhabdomyosarcoma | ACH-001184", + "Rhabdomyosarcoma | ACH-001196", + "Rhabdomyosarcoma | ACH-001740", + "Rhabdomyosarcoma | ACH-001745", + "Rhabdomyosarcoma | ACH-001750", + "Rhabdomyosarcoma | ACH-001765", + "Rhabdomyosarcoma | ACH-002048" + ], + "type": "scattergl", + "x": { + "bdata": "wPV0P5vxbD8mlCY/0gCBP0xqk72jI80/tUKsP998cz8DFB4/eelmP+7uVT/a8aY/YmnTPw==", + "dtype": "f4" + }, + "y": { + "bdata": "QLjSvH6p+70UzwI+f1slvgtZPj8iN1G/w0Iev5fhsL562HA9YLuDvr4AET4DafO+BiBTvw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000108", + "ACH-000685" + ], + "hoverinfo": "text", + "marker": { + "color": "#FF0092", + "size": 7 + }, + "mode": "markers", + "name": "Adenosquamous Carcinoma of the Pancreas", + "text": [ + "Adenosquamous Carcinoma of the Pancreas | ACH-000108", + "Adenosquamous Carcinoma of the Pancreas | ACH-000685" + ], + "type": "scattergl", + "x": { + "bdata": "Fy0zv7paYj8=", + "dtype": "f4" + }, + "y": { + "bdata": "QiSGPyPcpD0=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000133", + "ACH-001310", + "ACH-001453", + "ACH-002210", + "ACH-002247", + "ACH-002462", + "ACH-002463", + "ACH-002464", + "ACH-002465", + "ACH-002467" + ], + "hoverinfo": "text", + "marker": { + "color": "#22FFA7", + "size": 7 + }, + "mode": "markers", + "name": "Non-Cancerous", + "text": [ + "Non-Cancerous | ACH-000133", + "Non-Cancerous | ACH-001310", + "Non-Cancerous | ACH-001453", + "Non-Cancerous | ACH-002210", + "Non-Cancerous | ACH-002247", + "Non-Cancerous | ACH-002462", + "Non-Cancerous | ACH-002463", + "Non-Cancerous | ACH-002464", + "Non-Cancerous | ACH-002465", + "Non-Cancerous | ACH-002467" + ], + "type": "scattergl", + "x": { + "bdata": "JhcjPXM/MsC1s5o+rurhP1gZNsBN1zTAsqU3wHZuPMBl9jHAnOg2wA==", + "dtype": "f4" + }, + "y": { + "bdata": "/Wk5P4COZ78Rx7I++RuVvz2fPb965Ei/+FQfv73xyL5Vo2+/pNAtvw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000141", + "ACH-001607", + "ACH-001619", + "ACH-001850", + "ACH-001861", + "ACH-001961" + ], + "hoverinfo": "text", + "marker": { + "color": "#E3EE9E", + "size": 7 + }, + "mode": "markers", + "name": "Intracholecystic Papillary Neoplasm", + "text": [ + "Intracholecystic Papillary Neoplasm | ACH-000141", + "Intracholecystic Papillary Neoplasm | ACH-001607", + "Intracholecystic Papillary Neoplasm | ACH-001619", + "Intracholecystic Papillary Neoplasm | ACH-001850", + "Intracholecystic Papillary Neoplasm | ACH-001861", + "Intracholecystic Papillary Neoplasm | ACH-001961" + ], + "type": "scattergl", + "x": { + "bdata": "MJ45wJ7+cj8S3/a+1jtqP/MLMMAOAyw/", + "dtype": "f4" + }, + "y": { + "bdata": "B8ABv0adib6RoJo/keaTvpd3hr8pXLy8", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000145", + "ACH-000505", + "ACH-002785" + ], + "hoverinfo": "text", + "marker": { + "color": "#86CE00", + "size": 7 + }, + "mode": "markers", + "name": "Leiomyosarcoma", + "text": [ + "Leiomyosarcoma | ACH-000145", + "Leiomyosarcoma | ACH-000505", + "Leiomyosarcoma | ACH-002785" + ], + "type": "scattergl", + "x": { + "bdata": "atgmv5foZr+U+tK+", + "dtype": "f4" + }, + "y": { + "bdata": "oT+zP0oCyz8Zl6Y/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000159", + "ACH-000189", + "ACH-000234", + "ACH-000246", + "ACH-000250", + "ACH-000262", + "ACH-000272", + "ACH-000313", + "ACH-000317", + "ACH-000375", + "ACH-000385", + "ACH-000411", + "ACH-000433", + "ACH-000459", + "ACH-000484", + "ACH-000495", + "ACH-000649", + "ACH-000684", + "ACH-000709", + "ACH-000792", + "ACH-000907", + "ACH-001163", + "ACH-001194", + "ACH-001398", + "ACH-001687", + "ACH-001688", + "ACH-002150", + "ACH-002189", + "ACH-002533" + ], + "hoverinfo": "text", + "marker": { + "color": "#BC7196", + "size": 7 + }, + "mode": "markers", + "name": "Renal Cell Carcinoma", + "text": [ + "Renal Cell Carcinoma | ACH-000159", + "Renal Cell Carcinoma | ACH-000189", + "Renal Cell Carcinoma | ACH-000234", + "Renal Cell Carcinoma | ACH-000246", + "Renal Cell Carcinoma | ACH-000250", + "Renal Cell Carcinoma | ACH-000262", + "Renal Cell Carcinoma | ACH-000272", + "Renal Cell Carcinoma | ACH-000313", + "Renal Cell Carcinoma | ACH-000317", + "Renal Cell Carcinoma | ACH-000375", + "Renal Cell Carcinoma | ACH-000385", + "Renal Cell Carcinoma | ACH-000411", + "Renal Cell Carcinoma | ACH-000433", + "Renal Cell Carcinoma | ACH-000459", + "Renal Cell Carcinoma | ACH-000484", + "Renal Cell Carcinoma | ACH-000495", + "Renal Cell Carcinoma | ACH-000649", + "Renal Cell Carcinoma | ACH-000684", + "Renal Cell Carcinoma | ACH-000709", + "Renal Cell Carcinoma | ACH-000792", + "Renal Cell Carcinoma | ACH-000907", + "Renal Cell Carcinoma | ACH-001163", + "Renal Cell Carcinoma | ACH-001194", + "Renal Cell Carcinoma | ACH-001398", + "Renal Cell Carcinoma | ACH-001687", + "Renal Cell Carcinoma | ACH-001688", + "Renal Cell Carcinoma | ACH-002150", + "Renal Cell Carcinoma | ACH-002189", + "Renal Cell Carcinoma | ACH-002533" + ], + "type": "scattergl", + "x": { + "bdata": "ORHTvlekN8DrbDq/io4wwB8PNsB+wzTAwg04wITiYL/oQjPAzf2kP3oNwjxO+cs+XS6GvtRIB8ByOTzARZTLvkMLHT/0ok69XFhCvwqJMz7pYIa/gkcSP14HPsCzxsG8gpwzwEL1OsBrrjLAyaKSv5x2gj8=", + "dtype": "f4" + }, + "y": { + "bdata": 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"ACH-001695", + "ACH-001696", + "ACH-001698", + "ACH-001699", + "ACH-001701", + "ACH-002029", + "ACH-002030", + "ACH-002042", + "ACH-002043", + "ACH-002044", + "ACH-002045", + "ACH-002212", + "ACH-002249", + "ACH-002250", + "ACH-002251", + "ACH-002265", + "ACH-002294", + "ACH-002295", + "ACH-002296", + "ACH-002297", + "ACH-002298", + "ACH-002305" + ], + "hoverinfo": "text", + "marker": { + "color": "#7E7DCD", + "size": 7 + }, + "mode": "markers", + "name": "Head and Neck Squamous Cell Carcinoma", + "text": [ + "Head and Neck Squamous Cell Carcinoma | ACH-000163", + "Head and Neck Squamous Cell Carcinoma | ACH-000181", + "Head and Neck Squamous Cell Carcinoma | ACH-000188", + "Head and Neck Squamous Cell Carcinoma | ACH-000207", + "Head and Neck Squamous Cell Carcinoma | ACH-000228", + "Head and Neck Squamous Cell Carcinoma | ACH-000238", + "Head and Neck Squamous Cell Carcinoma | ACH-000415", + "Head and Neck Squamous Cell Carcinoma | ACH-000472", + "Head and Neck Squamous Cell Carcinoma | ACH-000500", + "Head and Neck Squamous Cell Carcinoma | ACH-000503", + "Head and Neck Squamous Cell Carcinoma | ACH-000518", + "Head and Neck Squamous Cell Carcinoma | ACH-000546", + "Head and Neck Squamous Cell Carcinoma | ACH-000548", + "Head and Neck Squamous Cell Carcinoma | ACH-000549", + "Head and Neck Squamous Cell Carcinoma | ACH-000606", + "Head and Neck Squamous Cell Carcinoma | ACH-000618", + "Head and Neck Squamous Cell Carcinoma | ACH-000619", + "Head and Neck Squamous Cell Carcinoma | ACH-000630", + "Head and Neck Squamous Cell Carcinoma | ACH-000682", + "Head and Neck Squamous Cell Carcinoma | ACH-000732", + "Head and Neck Squamous Cell Carcinoma | ACH-000735", + "Head and Neck Squamous Cell Carcinoma | ACH-000740", + "Head and Neck Squamous Cell Carcinoma | ACH-000762", + "Head and Neck Squamous Cell Carcinoma | ACH-000771", + "Head and Neck Squamous Cell Carcinoma | ACH-000778", + "Head and Neck Squamous Cell Carcinoma | ACH-000794", + "Head and Neck Squamous Cell Carcinoma | ACH-000832", + "Head and Neck Squamous Cell Carcinoma | ACH-000836", + "Head and Neck Squamous Cell Carcinoma | ACH-000846", + "Head and Neck Squamous Cell Carcinoma | ACH-001228", + "Head and Neck Squamous Cell Carcinoma | ACH-001229", + "Head and Neck Squamous Cell Carcinoma | ACH-001331", + "Head and Neck Squamous Cell Carcinoma | ACH-001332", + "Head and Neck Squamous Cell Carcinoma | ACH-001346", + "Head and Neck Squamous Cell Carcinoma | ACH-001347", + "Head and Neck Squamous Cell Carcinoma | ACH-001385", + "Head and Neck Squamous Cell Carcinoma | ACH-001509", + "Head and Neck Squamous Cell Carcinoma | ACH-001510", + "Head and Neck Squamous Cell Carcinoma | ACH-001511", + "Head and Neck Squamous Cell Carcinoma | ACH-001542", + "Head and Neck Squamous Cell Carcinoma | ACH-001543", + "Head and Neck Squamous Cell Carcinoma | ACH-001625", + "Head and Neck Squamous Cell Carcinoma | ACH-001626", + "Head and Neck Squamous Cell Carcinoma | ACH-001641", + "Head and Neck Squamous Cell Carcinoma | ACH-001675", + "Head and Neck Squamous Cell Carcinoma | ACH-001690", + "Head and Neck Squamous Cell Carcinoma | ACH-001691", + "Head and Neck Squamous Cell Carcinoma | ACH-001692", + "Head and Neck Squamous Cell Carcinoma | ACH-001694", + "Head and Neck Squamous Cell Carcinoma | ACH-001695", + "Head and Neck Squamous Cell Carcinoma | ACH-001696", + "Head and Neck Squamous Cell Carcinoma | ACH-001698", + "Head and Neck Squamous Cell Carcinoma | ACH-001699", + "Head and Neck Squamous Cell Carcinoma | ACH-001701", + "Head and Neck Squamous Cell Carcinoma | ACH-002029", + "Head and Neck Squamous Cell Carcinoma | ACH-002030", + "Head and Neck Squamous Cell Carcinoma | ACH-002042", + "Head and Neck Squamous Cell Carcinoma | ACH-002043", + "Head and Neck Squamous Cell Carcinoma | ACH-002044", + "Head and Neck Squamous Cell Carcinoma | ACH-002045", + "Head and Neck Squamous Cell Carcinoma | ACH-002212", + "Head and Neck Squamous Cell Carcinoma | ACH-002249", 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ACH-002041" + ], + "type": "scattergl", + "x": { + "bdata": "lJeCPmle0j5yIm++pZYkvzOQir9QapY93yx1vQ==", + "dtype": "f4" + }, + "y": { + "bdata": "6zIaP/PbSz6CgZQ/qry2PzWAwD/Qnzk/PPqKPw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000182", + "ACH-000377", + "ACH-001862", + "ACH-002023" + ], + "hoverinfo": "text", + "marker": { + "color": "#E48F72", + "size": 7 + }, + "mode": "markers", + "name": "Ampullary Carcinoma", + "text": [ + "Ampullary Carcinoma | ACH-000182", + "Ampullary Carcinoma | ACH-000377", + "Ampullary Carcinoma | ACH-001862", + "Ampullary Carcinoma | ACH-002023" + ], + "type": "scattergl", + "x": { + "bdata": "Tog0wNMTNcAYF4G+U+kxPw==", + "dtype": "f4" + }, + "y": { + "bdata": "RolKv+WfSL/Cvio/tRZVvg==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000187", + "ACH-000257", + "ACH-000290", + "ACH-000292", + "ACH-000355", + "ACH-000431", + "ACH-000514", + "ACH-000515", + "ACH-000525", + "ACH-000559", + "ACH-000639", + "ACH-000695", + "ACH-000698", + 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Neuroendocrine Tumor | ACH-000767", + "Lung Neuroendocrine Tumor | ACH-000775", + "Lung Neuroendocrine Tumor | ACH-000790", + "Lung Neuroendocrine Tumor | ACH-000800", + "Lung Neuroendocrine Tumor | ACH-000866", + "Lung Neuroendocrine Tumor | ACH-000871", + "Lung Neuroendocrine Tumor | ACH-000890", + "Lung Neuroendocrine Tumor | ACH-000912", + "Lung Neuroendocrine Tumor | ACH-001386", + "Lung Neuroendocrine Tumor | ACH-001549", + "Lung Neuroendocrine Tumor | ACH-002051", + "Lung Neuroendocrine Tumor | ACH-002052", + "Lung Neuroendocrine Tumor | ACH-002077" + ], + "type": "scattergl", + "x": { + "bdata": "3m1kP4zVBj6sLEI/fS/AP2PatT/JI6g+q9CtvTreUD9fDzQ/in4mvhq+wj9VFl++CkmMPyB9Zj8Q/KO8w25RP4C3hj+sexY/RULEP2nWtT+g6la+a95YPw0usT4dwec+5TEDv7SulD1U/qa+", + "dtype": "f4" + }, + "y": { + "bdata": "DZuUvVxOKz/C8pe9cvQdv4j1NL+oEgE/Q7pHP/2UXL7UV668RrEpP+6yfL9pV2w//lQEv1iEHr6kjVQ/0w5WvmdsOr7vonA+eb5Pv8YnGL87pWs/CZ26vc0AnD5/DLw+RFSlP0p1ND+a8n4/", + "dtype": "f4" + } + }, + { + "customdata": [ + 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"Endometrial Carcinoma | ACH-000941", + "Endometrial Carcinoma | ACH-000946", + "Endometrial Carcinoma | ACH-000961", + "Endometrial Carcinoma | ACH-000965", + "Endometrial Carcinoma | ACH-000972", + "Endometrial Carcinoma | ACH-000974", + "Endometrial Carcinoma | ACH-000978", + "Endometrial Carcinoma | ACH-000984", + "Endometrial Carcinoma | ACH-000988", + "Endometrial Carcinoma | ACH-000993", + "Endometrial Carcinoma | ACH-000994", + "Endometrial Carcinoma | ACH-000996", + "Endometrial Carcinoma | ACH-001495", + "Endometrial Carcinoma | ACH-001517", + "Endometrial Carcinoma | ACH-001518", + "Endometrial Carcinoma | ACH-002026", + "Endometrial Carcinoma | ACH-002027", + "Endometrial Carcinoma | ACH-002046" + ], + "type": "scattergl", + "x": { + "bdata": "cZ9Yvyr4Ub/BCrI8bRaavUkyCz4LzWq+KC4xwBdZVz9w9Zc/Nx2TPzhpEL9AdmY/UAhgP5bI2T8D7jjARYqNP36mLz4JTd6+p3EIPY367z1uRTPADhwCPfRctr6uIIy/dJA9wDk8kT+qNws/YpqqvQ==", + "dtype": "f4" + }, + "y": { + "bdata": 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ACH-001538", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001673", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001834", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001835", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001836", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001838", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001839", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001841", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001842", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001843", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001844", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001848", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001849", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001852", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001856", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001857", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001858", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001863", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001864", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001959", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001960", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001997", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-002647" + ], + "type": "scattergl", + "x": { + "bdata": "U1Q3wLMgOMCBbzPAnjI3PAuiPj5MGIQ+xQ2XPhBjqD+QXznAHoszwNrONsA9eTzA04g2wLWMMsAwmYW9HYc2wOTsM8DqzTPAcy00wG36rD/h/NM+/sUlP416HT9aiDrAPE6aPoBB4z9EmDQ/Xao3wMigIT8=", + "dtype": "f4" + }, + "y": { + "bdata": "1OMjvwzWEb/Dsk+/VqEQP75c6D6azvw+7UD6PonjNL/Dyg6/6lxTv/oANL/tkLy+eeQsv9+HbL+f8lg/Ipsvv84HVr8/ele/y+RIv37HGL+odoc+MQwHPmNVMb4mSwO/toywPZmofr+JoEs+fTckv6tlUj4=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000217", + "ACH-000221", + "ACH-000316", + "ACH-000361", + 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Carcinoma | ACH-000493", + "Hepatocellular Carcinoma | ACH-000537", + "Hepatocellular Carcinoma | ACH-000577", + "Hepatocellular Carcinoma | ACH-000620", + "Hepatocellular Carcinoma | ACH-000734", + "Hepatocellular Carcinoma | ACH-000848", + "Hepatocellular Carcinoma | ACH-001318", + "Hepatocellular Carcinoma | ACH-002523" + ], + "type": "scattergl", + "x": { + "bdata": "1flGP2aUzT8A3D0+QYqePnKVfr+S/N2+2iASP708kLxdxlw/JmSSvoa0v74M6og/hF/1vhMvmj24PgI/0JmOv/GlIT/TUa0/aiOoP0Q2PD8Wcfc+", + "dtype": "f4" + }, + "y": { + "bdata": "5fBDvdbs/75YxEk/5K8BP0+P6T8joJQ/phWDPhXoHj/lpgq9bwBuP6Cnfz8yhFe+esWQP+rvOT+Vz8o9vDzgP1KS2r3powW/Vf4Jv8nBhT1xP+E+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000305", + "ACH-000318", + "ACH-000408", + "ACH-000452", + "ACH-000488", + "ACH-000544", + "ACH-000561", + "ACH-000605", + "ACH-000637", + "ACH-000647", + "ACH-000693", + "ACH-000694", + "ACH-000717", + "ACH-000777", + "ACH-000784", + "ACH-000809", + "ACH-000823", + "ACH-000824", + "ACH-000855", + 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Squamous Cell Carcinoma | ACH-000784", + "Esophageal Squamous Cell Carcinoma | ACH-000809", + "Esophageal Squamous Cell Carcinoma | ACH-000823", + "Esophageal Squamous Cell Carcinoma | ACH-000824", + "Esophageal Squamous Cell Carcinoma | ACH-000855", + "Esophageal Squamous Cell Carcinoma | ACH-000865", + "Esophageal Squamous Cell Carcinoma | ACH-000873", + "Esophageal Squamous Cell Carcinoma | ACH-000917", + "Esophageal Squamous Cell Carcinoma | ACH-002243", + "Esophageal Squamous Cell Carcinoma | ACH-002263" + ], + "type": "scattergl", + "x": { + "bdata": "x7SYPmRgSD/+Lkg/oEaDPWYX5j+BEVo/IdY0PzCP9T7loQs+Kl/yvX7O5D9Bm2Q/ZBhePbaxTj/awoo/nHWkPxsHkD8UhhM/GumGP/T6dz/1wII/sGKAP2Z+ND+1dVo/", + "dtype": "f4" + }, + "y": { + "bdata": "Y7+4PmXuBjy9vJY7DGEQP9EbXb97m7a9n6fOvKPdoT67sis/y981P3SdLL/K3Ri+B4kZPxjeYr55squ+NNQJv+I1jr7edp0+lMbAvQZBKr1oC1m+FjKcvs1uVz7YYXW+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000456" + ], + "hoverinfo": "text", + "marker": { + "color": "#B68100", + 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"name": "Cervical Squamous Cell Carcinoma", + "text": [ + "Cervical Squamous Cell Carcinoma | ACH-000490", + "Cervical Squamous Cell Carcinoma | ACH-000556", + "Cervical Squamous Cell Carcinoma | ACH-001333", + "Cervical Squamous Cell Carcinoma | ACH-001334", + "Cervical Squamous Cell Carcinoma | ACH-001335", + "Cervical Squamous Cell Carcinoma | ACH-001336", + "Cervical Squamous Cell Carcinoma | ACH-001360", + "Cervical Squamous Cell Carcinoma | ACH-001402", + "Cervical Squamous Cell Carcinoma | ACH-001451", + "Cervical Squamous Cell Carcinoma | ACH-001515", + "Cervical Squamous Cell Carcinoma | ACH-001651", + "Cervical Squamous Cell Carcinoma | ACH-001652", + "Cervical Squamous Cell Carcinoma | ACH-002020" + ], + "type": "scattergl", + "x": { + "bdata": "Ty0rPxIomj6HkXQ/+/HPPzAVUT9fqwM/eGjOv1oqsz/tTTjAXfVePuvXrb/gReo+8WgGPA==", + "dtype": "f4" + }, + "y": { + "bdata": "KFORPjjf1j6WjKq9/UNSv1GltTymq44+kygWQK7Y3b46hiK/kz8XP1j7AkBUyqc+qdcWPw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000516" + ], + "hoverinfo": "text", + "marker": { + "color": "#511CFB", + "size": 7 + }, + "mode": "markers", + "name": "Chondrosarcoma", + "text": [ + "Chondrosarcoma | ACH-000516" + ], + "type": "scattergl", + "x": { + "bdata": "TGNovw==", + "dtype": "f4" + }, + "y": { + "bdata": "KXTYPw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000624", + "ACH-000725", + "ACH-000859" + ], + "hoverinfo": "text", + "marker": { + "color": "#00A08B", + "size": 7 + }, + "mode": "markers", + "name": "Breast Ductal Carcinoma In Situ", + "text": [ + "Breast Ductal Carcinoma In Situ | ACH-000624", + "Breast Ductal Carcinoma In Situ | ACH-000725", + "Breast Ductal Carcinoma In Situ | ACH-000859" + ], + "type": "scattergl", + "x": { + "bdata": "EXLqPuNdPr8BHNK6", + "dtype": "f4" + }, + "y": { + "bdata": "x617vRUBrD+J/Ak/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000671", + "ACH-000739" + ], + "hoverinfo": "text", + "marker": { + "color": "#FB00D1", + "size": 7 + }, + "mode": "markers", + "name": "Hepatoblastoma", + "text": [ + "Hepatoblastoma | ACH-000671", + "Hepatoblastoma | ACH-000739" + ], + "type": "scattergl", + "x": { + "bdata": "R96vP/gruz4=", + "dtype": "f4" + }, + "y": { + "bdata": "UHgBvwhVpj4=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000702", + "ACH-000754", + "ACH-001685" + ], + "hoverinfo": "text", + "marker": { + "color": "#FC0080", + "size": 7 + }, + "mode": "markers", + "name": "Hodgkin Lymphoma", + "text": [ + "Hodgkin Lymphoma | ACH-000702", + "Hodgkin Lymphoma | ACH-000754", + "Hodgkin Lymphoma | ACH-001685" + ], + "type": "scattergl", + "x": { + "bdata": "ArigPoiJHD+My4a7", + "dtype": "f4" + }, + "y": { + "bdata": "7FBdPiHBDj4pHxE/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000716", + "ACH-000903", + "ACH-001528" + ], + "hoverinfo": "text", + "marker": { + "color": "#B2828D", + "size": 7 + }, + "mode": "markers", + "name": "Well-Differentiated Thyroid Cancer", + "text": [ + 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Cell Carcinoma | ACH-001551", + "Merkel Cell Carcinoma | ACH-001552" + ], + "type": "scattergl", + "x": { + "bdata": "H9emvh0RpT/zzya/", + "dtype": "f4" + }, + "y": { + "bdata": "9V2XPyJBwL7oaMg/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-001554", + "ACH-002014", + "ACH-002015", + "ACH-002016", + "ACH-002018", + "ACH-002687", + "ACH-002925", + "ACH-002926" + ], + "hoverinfo": "text", + "marker": { + "color": "#FF6692", + "size": 7 + }, + "mode": "markers", + "name": "Ocular Melanoma", + "text": [ + "Ocular Melanoma | ACH-001554", + "Ocular Melanoma | ACH-002014", + "Ocular Melanoma | ACH-002015", + "Ocular Melanoma | ACH-002016", + "Ocular Melanoma | ACH-002018", + "Ocular Melanoma | ACH-002687", + "Ocular Melanoma | ACH-002925", + "Ocular Melanoma | ACH-002926" + ], + "type": "scattergl", + "x": { + "bdata": "xoQvwPh2+z6A5Kg+NnIev6p0Pj9x5DHA9OAxwL4PLcA=", + "dtype": "f4" + }, + "y": { + "bdata": "/IaIv+eVhj5pUP0+wI+ZP8o7Tr6yi2e/K8yAv/lRmb8=", + "dtype": "f4" + } + }, + { 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"ACH-000985", + "ACH-000986", + "ACH-000991", + "ACH-000997", + "ACH-001039", + "ACH-001061", + "ACH-001081", + "ACH-001345", + "ACH-001399", + "ACH-001454", + "ACH-001458", + "ACH-001459", + "ACH-001460", + "ACH-001461", + "ACH-001786", + "ACH-002024", + "ACH-002025", + "ACH-002233", + "ACH-002535", + "ACH-002654", + "ACH-002659", + "ACH-002660", + "ACH-002662", + "ACH-002664", + "ACH-002669" + ], + "hoverinfo": "text", + "marker": { + "color": "#00CC96", + "size": 7 + }, + "mode": "markers", + "name": "Colorectal Adenocarcinoma", + "text": [ + "Colorectal Adenocarcinoma | ACH-000007", + "Colorectal Adenocarcinoma | ACH-000009", + "Colorectal Adenocarcinoma | ACH-000202", + "Colorectal Adenocarcinoma | ACH-000249", + "Colorectal Adenocarcinoma | ACH-000252", + "Colorectal Adenocarcinoma | ACH-000253", + "Colorectal Adenocarcinoma | ACH-000286", + "Colorectal Adenocarcinoma | ACH-000296", + "Colorectal Adenocarcinoma | ACH-000350", + "Colorectal Adenocarcinoma | ACH-000381", + "Colorectal Adenocarcinoma | ACH-000403", + "Colorectal Adenocarcinoma | ACH-000421", + "Colorectal Adenocarcinoma | ACH-000467", + "Colorectal Adenocarcinoma | ACH-000470", + "Colorectal Adenocarcinoma | ACH-000489", + "Colorectal Adenocarcinoma | ACH-000491", + "Colorectal Adenocarcinoma | ACH-000501", + "Colorectal Adenocarcinoma | ACH-000532", + "Colorectal Adenocarcinoma | ACH-000552", + "Colorectal Adenocarcinoma | ACH-000565", + "Colorectal Adenocarcinoma | ACH-000651", + "Colorectal Adenocarcinoma | ACH-000683", + "Colorectal Adenocarcinoma | ACH-000722", + "Colorectal Adenocarcinoma | ACH-000798", + "Colorectal Adenocarcinoma | ACH-000820", + "Colorectal Adenocarcinoma | ACH-000926", + "Colorectal Adenocarcinoma | ACH-000935", + "Colorectal Adenocarcinoma | ACH-000943", + "Colorectal Adenocarcinoma | ACH-000950", + "Colorectal Adenocarcinoma | ACH-000957", + "Colorectal Adenocarcinoma | ACH-000958", + "Colorectal Adenocarcinoma | ACH-000959", + "Colorectal Adenocarcinoma | ACH-000963", + "Colorectal Adenocarcinoma | ACH-000969", + "Colorectal Adenocarcinoma | ACH-000970", + "Colorectal Adenocarcinoma | ACH-000971", + "Colorectal Adenocarcinoma | ACH-000985", + "Colorectal Adenocarcinoma | ACH-000986", + "Colorectal Adenocarcinoma | ACH-000991", + "Colorectal Adenocarcinoma | ACH-000997", + "Colorectal Adenocarcinoma | ACH-001039", + "Colorectal Adenocarcinoma | ACH-001061", + "Colorectal Adenocarcinoma | ACH-001081", + "Colorectal Adenocarcinoma | ACH-001345", + "Colorectal Adenocarcinoma | ACH-001399", + "Colorectal Adenocarcinoma | ACH-001454", + "Colorectal Adenocarcinoma | ACH-001458", + "Colorectal Adenocarcinoma | ACH-001459", + "Colorectal Adenocarcinoma | ACH-001460", + "Colorectal Adenocarcinoma | ACH-001461", + "Colorectal Adenocarcinoma | ACH-001786", + "Colorectal Adenocarcinoma | ACH-002024", + "Colorectal Adenocarcinoma | ACH-002025", + "Colorectal Adenocarcinoma | ACH-002233", + "Colorectal Adenocarcinoma | ACH-002535", + "Colorectal Adenocarcinoma | ACH-002654", + "Colorectal Adenocarcinoma | ACH-002659", + "Colorectal Adenocarcinoma | ACH-002660", + "Colorectal Adenocarcinoma | ACH-002662", + "Colorectal Adenocarcinoma | ACH-002664", + "Colorectal Adenocarcinoma | ACH-002669" + ], + "type": "scattergl", + "x": { + "bdata": "Pj5MQJQn5z9ZM9M/tU/1wMHqRz71BYw/X7mpP51M4D8Z+xHA2fcoQMaEnb9Y0iS/XVH1wFC11L1RFoY/SDaFv+sez7whYoA/WRrNP5Fclz9S0C9AjWtrvuiJ2T80Y/XANglePyph9cBGXvXAThf1wIQ1WkB2GVtAzP4CQOYtI0CZ6J2/9V/1wI0s0T89tcs/SkVZP2pK9cAc7Jc/F0w0QA0yMkAr32BAnFL1wJxoCEAPLYM/tnarvzsJXD+il94/UiJFQLGhwr9BTPY+6/6gP7ZF9cB/R6M+pusxPxJGKb00gzpA/KuXP+1cKEDljipAPo9FQA==", + "dtype": "f4" + }, + "y": { + "bdata": 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Carcinoma", + "text": [ + "Bladder Urothelial Carcinoma | ACH-000011", + "Bladder Urothelial Carcinoma | ACH-000018", + "Bladder Urothelial Carcinoma | ACH-000026", + "Bladder Urothelial Carcinoma | ACH-000127", + "Bladder Urothelial Carcinoma | ACH-000142", + "Bladder Urothelial Carcinoma | ACH-000242", + "Bladder Urothelial Carcinoma | ACH-000396", + "Bladder Urothelial Carcinoma | ACH-000473", + "Bladder Urothelial Carcinoma | ACH-000486", + "Bladder Urothelial Carcinoma | ACH-000522", + "Bladder Urothelial Carcinoma | ACH-000545", + "Bladder Urothelial Carcinoma | ACH-000547", + "Bladder Urothelial Carcinoma | ACH-000593", + "Bladder Urothelial Carcinoma | ACH-000720", + "Bladder Urothelial Carcinoma | ACH-000724", + "Bladder Urothelial Carcinoma | ACH-000741", + "Bladder Urothelial Carcinoma | ACH-000753", + "Bladder Urothelial Carcinoma | ACH-000802", + "Bladder Urothelial Carcinoma | ACH-000834", + "Bladder Urothelial Carcinoma | ACH-000862", + "Bladder Urothelial Carcinoma | ACH-000896", + "Bladder Urothelial Carcinoma | ACH-000905", + "Bladder Urothelial Carcinoma | ACH-001183", + "Bladder Urothelial Carcinoma | ACH-001407", + "Bladder Urothelial Carcinoma | ACH-001409", + "Bladder Urothelial Carcinoma | ACH-001412", + "Bladder Urothelial Carcinoma | ACH-001413", + "Bladder Urothelial Carcinoma | ACH-001414", + "Bladder Urothelial Carcinoma | ACH-001415", + "Bladder Urothelial Carcinoma | ACH-001416" + ], + "type": "scattergl", + "x": { + "bdata": "0rv5PzG3yj+vyNg/FhtpQDqeCUAYkt4/6UXbvcBk9cADpklACDL1wFdV9cDAIwVApjTgP3fmAkBPV3O/cGzOP4y1VEBUPlBA7EJTQAGJ9cC0txFATzMbQLZZ9cAoOPXA90b1wNRY9cBkMvXAuFn1wD6N9cAQW/XA", + "dtype": "f4" + }, + "y": { + "bdata": "hcSLP9+nzD+pwsA9NZ2gu0SA2T4BWpo+kxOOP+H0br6XAgU/ZhR0vo+Jbb7meFQ/aJesP52y6T+q1KQ/bMNAPjR9IT99XYw/u/U1Pwu8Wb5bMjM/M4kPP5r9Xb4GpW++gyhovq9/bL5X74C+jlddvs4RZb6kAHO+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000012", + "ACH-000015", + "ACH-000021", + "ACH-000029", + "ACH-000030", + "ACH-000035", + "ACH-000143", + "ACH-000161", + "ACH-000176", + "ACH-000251", + "ACH-000261", + "ACH-000264", + "ACH-000311", + "ACH-000337", + "ACH-000339", + "ACH-000343", + "ACH-000378", + "ACH-000390", + "ACH-000395", + "ACH-000414", + "ACH-000416", + "ACH-000434", + "ACH-000438", + "ACH-000442", + "ACH-000444", + "ACH-000448", + "ACH-000454", + "ACH-000463", + "ACH-000481", + "ACH-000496", + "ACH-000510", + "ACH-000511", + "ACH-000521", + "ACH-000528", + "ACH-000562", + "ACH-000563", + "ACH-000585", + "ACH-000587", + "ACH-000589", + "ACH-000596", + "ACH-000627", + "ACH-000638", + "ACH-000662", + "ACH-000665", + "ACH-000666", + "ACH-000667", + "ACH-000672", + "ACH-000677", + "ACH-000681", + "ACH-000700", + "ACH-000706", + "ACH-000718", + "ACH-000747", + "ACH-000757", + "ACH-000766", + "ACH-000769", + "ACH-000774", + "ACH-000781", + "ACH-000785", + "ACH-000787", + "ACH-000791", + "ACH-000826", + "ACH-000837", + "ACH-000840", + "ACH-000841", + "ACH-000843", + "ACH-000845", + "ACH-000851", + "ACH-000853", + "ACH-000858", + "ACH-000860", + "ACH-000861", + "ACH-000867", + "ACH-000869", + "ACH-000872", + "ACH-000878", + "ACH-000886", + "ACH-000888", + "ACH-000894", + "ACH-000900", + "ACH-000901", + "ACH-000916", + "ACH-000921", + "ACH-000924", + "ACH-000929", + "ACH-000945", + "ACH-000975", + "ACH-000980", + "ACH-001075", + "ACH-001137", + "ACH-001233", + "ACH-002035", + "ACH-002156", + "ACH-002522", + "ACH-002526", + "ACH-002531", + "ACH-002650", + "ACH-003012" + ], + "hoverinfo": "text", + "marker": { + "color": "#FFA15A", + "size": 7 + }, + "mode": "markers", + "name": "Non-Small Cell Lung Cancer", + "text": [ + "Non-Small Cell Lung Cancer | ACH-000012", + "Non-Small Cell Lung Cancer | ACH-000015", + "Non-Small Cell Lung Cancer | ACH-000021", + "Non-Small Cell Lung Cancer | ACH-000029", + "Non-Small Cell Lung Cancer | ACH-000030", + "Non-Small Cell Lung Cancer | ACH-000035", + "Non-Small Cell Lung Cancer | ACH-000143", + "Non-Small Cell Lung Cancer | ACH-000161", + "Non-Small Cell Lung Cancer | ACH-000176", + "Non-Small Cell Lung Cancer | ACH-000251", + "Non-Small Cell Lung Cancer | ACH-000261", + "Non-Small Cell Lung Cancer | ACH-000264", + "Non-Small Cell Lung Cancer | ACH-000311", + "Non-Small Cell Lung Cancer | ACH-000337", + "Non-Small Cell Lung Cancer | ACH-000339", + "Non-Small Cell Lung Cancer | ACH-000343", + "Non-Small Cell Lung Cancer | ACH-000378", + "Non-Small Cell Lung Cancer | ACH-000390", + "Non-Small Cell Lung Cancer | ACH-000395", + "Non-Small Cell Lung Cancer | ACH-000414", + "Non-Small Cell Lung Cancer | ACH-000416", + "Non-Small Cell Lung Cancer | ACH-000434", + "Non-Small Cell Lung Cancer | ACH-000438", + "Non-Small Cell Lung Cancer | ACH-000442", + "Non-Small Cell Lung Cancer | ACH-000444", + "Non-Small Cell Lung Cancer | ACH-000448", + "Non-Small Cell Lung Cancer | ACH-000454", + "Non-Small Cell Lung Cancer | ACH-000463", + "Non-Small Cell Lung Cancer | ACH-000481", + "Non-Small Cell Lung Cancer | ACH-000496", + "Non-Small Cell Lung Cancer | ACH-000510", + "Non-Small Cell Lung Cancer | ACH-000511", + "Non-Small Cell Lung Cancer | ACH-000521", + "Non-Small Cell Lung Cancer | ACH-000528", + "Non-Small Cell Lung Cancer | ACH-000562", + "Non-Small Cell Lung Cancer | ACH-000563", + "Non-Small Cell Lung Cancer | ACH-000585", + "Non-Small Cell Lung Cancer | ACH-000587", + "Non-Small Cell Lung Cancer | ACH-000589", + "Non-Small Cell Lung Cancer | ACH-000596", + "Non-Small Cell Lung Cancer | ACH-000627", + "Non-Small Cell Lung Cancer | ACH-000638", + "Non-Small Cell Lung Cancer | ACH-000662", + "Non-Small Cell Lung Cancer | ACH-000665", + "Non-Small Cell Lung Cancer | ACH-000666", + "Non-Small Cell Lung Cancer | ACH-000667", + "Non-Small Cell Lung Cancer | ACH-000672", + "Non-Small Cell Lung Cancer | ACH-000677", + "Non-Small Cell Lung Cancer | ACH-000681", + "Non-Small Cell Lung Cancer | ACH-000700", + "Non-Small Cell Lung Cancer | ACH-000706", + "Non-Small Cell Lung Cancer | ACH-000718", + "Non-Small Cell Lung Cancer | ACH-000747", + "Non-Small Cell Lung Cancer | ACH-000757", + "Non-Small Cell Lung Cancer | ACH-000766", + "Non-Small Cell Lung Cancer | ACH-000769", + "Non-Small Cell Lung Cancer | ACH-000774", + "Non-Small Cell Lung Cancer | ACH-000781", + "Non-Small Cell Lung Cancer | ACH-000785", + "Non-Small Cell Lung Cancer | ACH-000787", + "Non-Small Cell Lung Cancer | ACH-000791", + "Non-Small Cell Lung Cancer | ACH-000826", + "Non-Small Cell Lung Cancer | ACH-000837", + "Non-Small Cell Lung Cancer | ACH-000840", + "Non-Small Cell Lung Cancer | ACH-000841", + "Non-Small Cell Lung Cancer | ACH-000843", + "Non-Small Cell Lung Cancer | ACH-000845", + "Non-Small Cell Lung Cancer | ACH-000851", + "Non-Small Cell Lung Cancer | ACH-000853", + "Non-Small Cell Lung Cancer | ACH-000858", + "Non-Small Cell Lung Cancer | ACH-000860", + "Non-Small Cell Lung Cancer | ACH-000861", + "Non-Small Cell Lung Cancer | ACH-000867", + "Non-Small Cell Lung Cancer | ACH-000869", + "Non-Small Cell Lung Cancer | ACH-000872", + "Non-Small Cell Lung Cancer | ACH-000878", + "Non-Small Cell Lung Cancer | ACH-000886", + "Non-Small Cell Lung Cancer | ACH-000888", + "Non-Small Cell Lung Cancer | ACH-000894", + "Non-Small Cell Lung Cancer | ACH-000900", + "Non-Small Cell Lung Cancer | ACH-000901", + "Non-Small Cell Lung Cancer | ACH-000916", + "Non-Small Cell Lung Cancer | ACH-000921", + "Non-Small Cell Lung Cancer | ACH-000924", + "Non-Small Cell Lung Cancer | ACH-000929", + "Non-Small Cell Lung Cancer | ACH-000945", + "Non-Small Cell Lung Cancer | ACH-000975", + "Non-Small Cell Lung Cancer | ACH-000980", + "Non-Small Cell Lung Cancer | ACH-001075", + "Non-Small Cell Lung Cancer | ACH-001137", + "Non-Small Cell Lung Cancer | ACH-001233", + "Non-Small Cell Lung Cancer | ACH-002035", + "Non-Small Cell Lung Cancer | ACH-002156", + "Non-Small Cell Lung Cancer | ACH-002522", + "Non-Small Cell Lung Cancer | ACH-002526", + "Non-Small Cell Lung Cancer | ACH-002531", + "Non-Small Cell Lung Cancer | ACH-002650", + "Non-Small Cell Lung Cancer | ACH-003012" + ], + "type": "scattergl", + "x": { + "bdata": "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", + "dtype": "f4" + }, + "y": { + "bdata": 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"ACH-000827", + "ACH-000881", + "ACH-000882", + "ACH-000884", + "ACH-000899", + "ACH-000915", + "ACH-000968", + "ACH-001041", + "ACH-001190", + "ACH-001239", + "ACH-001522", + "ACH-001563", + "ACH-001566", + "ACH-001567", + "ACH-001568", + "ACH-001570", + "ACH-001645", + "ACH-001970", + "ACH-001972", + "ACH-001973", + "ACH-001975", + "ACH-001982", + "ACH-001986", + "ACH-001990", + "ACH-002001", + "ACH-002002", + "ACH-002003", + "ACH-002004", + "ACH-002005", + "ACH-002084", + "ACH-002143", + "ACH-002458", + "ACH-002460", + "ACH-002461", + "ACH-002508", + "ACH-002510", + "ACH-002511", + "ACH-002512", + "ACH-002847", + "ACH-002928" + ], + "hoverinfo": "text", + "marker": { + "color": "#19D3F3", + "size": 7 + }, + "mode": "markers", + "name": "Melanoma", + "text": [ + "Melanoma | ACH-000014", + "Melanoma | ACH-000219", + "Melanoma | ACH-000274", + "Melanoma | ACH-000304", + "Melanoma | ACH-000322", + "Melanoma | ACH-000348", + "Melanoma | ACH-000401", + "Melanoma | ACH-000404", + "Melanoma | ACH-000425", + "Melanoma | ACH-000441", + "Melanoma | ACH-000450", + "Melanoma | ACH-000458", + "Melanoma | ACH-000477", + "Melanoma | ACH-000550", + "Melanoma | ACH-000579", + "Melanoma | ACH-000580", + "Melanoma | ACH-000614", + "Melanoma | ACH-000632", + "Melanoma | ACH-000661", + "Melanoma | ACH-000765", + "Melanoma | ACH-000788", + "Melanoma | ACH-000799", + "Melanoma | ACH-000801", + "Melanoma | ACH-000805", + "Melanoma | ACH-000810", + "Melanoma | ACH-000822", + "Melanoma | ACH-000827", + "Melanoma | ACH-000881", + "Melanoma | ACH-000882", + "Melanoma | ACH-000884", + "Melanoma | ACH-000899", + "Melanoma | ACH-000915", + "Melanoma | ACH-000968", + "Melanoma | ACH-001041", + "Melanoma | ACH-001190", + "Melanoma | ACH-001239", + "Melanoma | ACH-001522", + "Melanoma | ACH-001563", + "Melanoma | ACH-001566", + "Melanoma | ACH-001567", + "Melanoma | ACH-001568", + "Melanoma | ACH-001570", + "Melanoma | ACH-001645", + "Melanoma | ACH-001970", + "Melanoma | ACH-001972", + "Melanoma | ACH-001973", + "Melanoma | ACH-001975", + "Melanoma | ACH-001982", + "Melanoma | ACH-001986", + "Melanoma | ACH-001990", + "Melanoma | ACH-002001", + "Melanoma | ACH-002002", + "Melanoma | ACH-002003", + "Melanoma | ACH-002004", + "Melanoma | ACH-002005", + "Melanoma | ACH-002084", + "Melanoma | ACH-002143", + "Melanoma | ACH-002458", + "Melanoma | ACH-002460", + "Melanoma | ACH-002461", + "Melanoma | ACH-002508", + "Melanoma | ACH-002510", + "Melanoma | ACH-002511", + "Melanoma | ACH-002512", + "Melanoma | ACH-002847", + "Melanoma | ACH-002928" + ], + "type": "scattergl", + "x": { + "bdata": "RBoeQKmUpEBPvdC/Ne4KP3NkUkDyuRK/3akpQL1E9cCkbvXAlydcQDpV9cCcRfXAgTMlP8WRL7+OXfXAMmmqPmSkPEC0nyNAvmD1wJ4I4T8lkMU/5uURP7Z29cAIQc8/ouplP0KT1r8UMOo/WnVEQMDDakCWWjhAgkj1wIHxPkD0mi1AWfzrP5jKqrzmHDdAv7XuP9FI9cDfavXAgHL1wHZe9cDEVfXAjir1PPkzF0BTJvXA4Fn1wHxo9cD5ogVANGdCQCr6W0B9b2JA2LGPQHwAFEBYPfXA1utYQLMNPzuR2AvAKUcqQJo1GkCGwDE/KKZtPhI9OEBV5gTAySquP/zkrD7i4P2/", + "dtype": "f4" + }, + "y": { + "bdata": "RQEyP8tjKD9anoc//YAMPxiYaD9ZqKs/QtxfP5IDar6KK2C+oWq0Pkq3Xb4rWXS+5YucPzVJMEDr9mK+SOYkP4oQND93nwBAt59nvhpriz8cBMA/aZ7AP2DSXr570gU+SvcSP7buzL4sR3s/of+bPSHTjb7j0WG9dJZevrYIEr83/rm7mdW8P/1Xwz8/nXg+lzxGP32ZeL6az2i+7AlfvlLeXr6Gv3O+xhfOvtPBtT8DIHa+qbVpvi2vab78eTm/iyMYPmG45T1hF5s+Cc42v/wgDT8xAm6+wAvgupPnej8MZLc+MRzBP+iQHT8UDzU/sHQ/QC/rkj0zYgc/16vDPz1dFEDw70U+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000017", + "ACH-000019", + "ACH-000028", + "ACH-000097", + "ACH-000111", + "ACH-000147", + "ACH-000148", + "ACH-000212", + "ACH-000223", + "ACH-000248", + "ACH-000258", + "ACH-000276", + "ACH-000277", + "ACH-000288", + "ACH-000330", + "ACH-000352", + "ACH-000374", + "ACH-000554", + "ACH-000573", + "ACH-000621", + "ACH-000668", + "ACH-000699", + "ACH-000711", + "ACH-000721", + "ACH-000768", + "ACH-000783", + "ACH-000849", + "ACH-000856", + "ACH-000876", + "ACH-000910", + "ACH-000934", + "ACH-001065", + "ACH-001388", + "ACH-001389", + "ACH-001390", + "ACH-001391", + "ACH-001392", + "ACH-001393", + "ACH-001394", + "ACH-001396", + "ACH-001419", + "ACH-001662", + "ACH-001683", + "ACH-001819", + "ACH-002179", + "ACH-002399", + "ACH-002401" + ], + "hoverinfo": "text", + "marker": { + "color": "#FF6692", + "size": 7 + }, + "mode": "markers", + "name": "Invasive Breast Carcinoma", + "text": [ + "Invasive Breast Carcinoma | ACH-000017", + "Invasive Breast Carcinoma | ACH-000019", + "Invasive Breast Carcinoma | ACH-000028", + "Invasive Breast Carcinoma | ACH-000097", + "Invasive Breast Carcinoma | ACH-000111", + "Invasive Breast Carcinoma | ACH-000147", + "Invasive Breast Carcinoma | ACH-000148", + "Invasive Breast Carcinoma | ACH-000212", + "Invasive Breast Carcinoma | ACH-000223", + "Invasive Breast Carcinoma | ACH-000248", + "Invasive Breast Carcinoma | ACH-000258", + "Invasive Breast Carcinoma | ACH-000276", + "Invasive Breast Carcinoma | ACH-000277", + "Invasive Breast Carcinoma | ACH-000288", + "Invasive Breast Carcinoma | ACH-000330", + "Invasive Breast Carcinoma | ACH-000352", + "Invasive Breast Carcinoma | ACH-000374", + "Invasive Breast Carcinoma | ACH-000554", + "Invasive Breast Carcinoma | ACH-000573", + "Invasive Breast Carcinoma | ACH-000621", + "Invasive Breast Carcinoma | ACH-000668", + "Invasive Breast Carcinoma | ACH-000699", + "Invasive Breast Carcinoma | ACH-000711", + "Invasive Breast Carcinoma | ACH-000721", + "Invasive Breast Carcinoma | ACH-000768", + "Invasive Breast Carcinoma | ACH-000783", + "Invasive Breast Carcinoma | ACH-000849", + "Invasive Breast Carcinoma | ACH-000856", + "Invasive Breast Carcinoma | ACH-000876", + "Invasive Breast Carcinoma | ACH-000910", + "Invasive Breast Carcinoma | ACH-000934", + "Invasive Breast Carcinoma | ACH-001065", + "Invasive Breast Carcinoma | ACH-001388", + "Invasive Breast Carcinoma | ACH-001389", + "Invasive Breast Carcinoma | ACH-001390", + "Invasive Breast Carcinoma | ACH-001391", + "Invasive Breast Carcinoma | ACH-001392", + "Invasive Breast Carcinoma | ACH-001393", + "Invasive Breast Carcinoma | ACH-001394", + "Invasive Breast Carcinoma | ACH-001396", + "Invasive Breast Carcinoma | ACH-001419", + "Invasive Breast Carcinoma | ACH-001662", + "Invasive Breast Carcinoma | ACH-001683", + "Invasive Breast Carcinoma | ACH-001819", + "Invasive Breast Carcinoma | ACH-002179", + "Invasive Breast Carcinoma | ACH-002399", + "Invasive Breast Carcinoma | ACH-002401" + ], + "type": "scattergl", + "x": { + "bdata": "hOtRPmIYlT8ZFEJA/CokP62K0T9n0/c/fZToPpTtwD/IHnS/hZaxP3A4P75uMuK9sjkuvjxB1D8x9Rk/8wMDPwPIxT9ykDbAUauiP/vWGsDh95K+/ajHv/y+AUDQuj1AjB3NP3DHEMB6zShAtN+SQAUJ9r9tMfU/sjqAwJQDdUC2glm/2Vf1wHw1B0AiRLa/4V71wHBa9cDuY/XAb4b1wCUeYD8cOXu+v1QZu2/stL84zZE/jMOoP8j+J0A=", + "dtype": "f4" + }, + "y": { + "bdata": "bx9mv6Y817962tO/YaGSv3qEBsDlEMO/Jy6SP1WVCD9/Yyy/JaW8v27Bdr42n0k+U5B1v0OtEEAICoW/Fke1vww4P79nMA3APro9PmqgCD5PYqi/rEjaPvOTKr9xixO/XppvPEoxrr9cYwm/45ckPkjs7r/E4RrAZoL6vxMd1r8O5K48JuBivhgkMT+RPiM+aYJovo9YbL5xWG6+CeVpvl395b6JHiC/H750v3OXdr+PSibA33rjvs3rVL0=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000022", + "ACH-000023", + "ACH-000042", + "ACH-000060", + "ACH-000085", + "ACH-000093", + "ACH-000094", + "ACH-000114", + "ACH-000118", + "ACH-000138", + "ACH-000139", + "ACH-000155", + "ACH-000164", + "ACH-000178", + "ACH-000213", + "ACH-000222", + "ACH-000235", + "ACH-000243", + "ACH-000265", + "ACH-000266", + "ACH-000281", + "ACH-000307", + "ACH-000320", + "ACH-000332", + "ACH-000354", + "ACH-000417", + "ACH-000468", + "ACH-000502", + "ACH-000517", + "ACH-000535", + "ACH-000599", + "ACH-000601", + "ACH-000652", + "ACH-001098", + "ACH-001107", + "ACH-001353", + "ACH-001375", + "ACH-001377", + "ACH-001379", + "ACH-001380", + "ACH-001382", + "ACH-001999", + "ACH-002039", + "ACH-002186", + "ACH-002672" + ], + "hoverinfo": "text", + "marker": { + "color": "#B6E880", + "size": 7 + }, + "mode": "markers", + "name": "Pancreatic Adenocarcinoma", + "text": [ + "Pancreatic Adenocarcinoma | ACH-000022", + "Pancreatic Adenocarcinoma | ACH-000023", + "Pancreatic Adenocarcinoma | ACH-000042", + "Pancreatic Adenocarcinoma | ACH-000060", + "Pancreatic Adenocarcinoma | ACH-000085", + "Pancreatic Adenocarcinoma | ACH-000093", + "Pancreatic Adenocarcinoma | ACH-000094", + "Pancreatic Adenocarcinoma | ACH-000114", + "Pancreatic Adenocarcinoma | ACH-000118", + "Pancreatic Adenocarcinoma | ACH-000138", + "Pancreatic Adenocarcinoma | ACH-000139", + "Pancreatic Adenocarcinoma | ACH-000155", + "Pancreatic Adenocarcinoma | ACH-000164", + "Pancreatic Adenocarcinoma | ACH-000178", + "Pancreatic Adenocarcinoma | ACH-000213", + "Pancreatic Adenocarcinoma | ACH-000222", + "Pancreatic Adenocarcinoma | ACH-000235", + "Pancreatic Adenocarcinoma | ACH-000243", + "Pancreatic Adenocarcinoma | ACH-000265", + "Pancreatic Adenocarcinoma | ACH-000266", + "Pancreatic Adenocarcinoma | ACH-000281", + "Pancreatic Adenocarcinoma | ACH-000307", + "Pancreatic Adenocarcinoma | ACH-000320", + "Pancreatic Adenocarcinoma | ACH-000332", + "Pancreatic Adenocarcinoma | ACH-000354", + "Pancreatic Adenocarcinoma | ACH-000417", + "Pancreatic Adenocarcinoma | ACH-000468", + "Pancreatic Adenocarcinoma | ACH-000502", + "Pancreatic Adenocarcinoma | ACH-000517", + "Pancreatic Adenocarcinoma | ACH-000535", + "Pancreatic Adenocarcinoma | ACH-000599", + "Pancreatic Adenocarcinoma | ACH-000601", + "Pancreatic Adenocarcinoma | ACH-000652", + "Pancreatic Adenocarcinoma | ACH-001098", + "Pancreatic Adenocarcinoma | ACH-001107", + "Pancreatic Adenocarcinoma | ACH-001353", + "Pancreatic Adenocarcinoma | ACH-001375", + "Pancreatic Adenocarcinoma | ACH-001377", + "Pancreatic Adenocarcinoma | ACH-001379", + "Pancreatic Adenocarcinoma | ACH-001380", + "Pancreatic Adenocarcinoma | ACH-001382", + "Pancreatic Adenocarcinoma | ACH-001999", + "Pancreatic Adenocarcinoma | ACH-002039", + "Pancreatic Adenocarcinoma | ACH-002186", + "Pancreatic Adenocarcinoma | ACH-002672" + ], + "type": "scattergl", + "x": { + "bdata": "rgS9PzeViEDK2QW/btWKvnGMTj+PEks/C91evyPCfD1oPeM/5nQHQCkfoz+O2l4+kHnIP6rUF0Drk+E/ltQFwHxQlT8vmglAhcuOQOpJt79dYQ8/Omf1wNZyPkCacLk/g4b7Pm4vNL8HjvXA29zRP1Bhab9iAo0/VTp9P4ckX0C1BeM/2iwrQLRMSz7H8lc/jKWYPmqCEkA0je8/HGAqQEo7AD9CYPXAbV/1wHVX9cByhdE/", + "dtype": "f4" + }, + "y": { + "bdata": "pdfKvqClkj/z5uG9W9/vPi8SAD/zN0k/2jmnv40UQz9/cRq/Yzp+PiUrj706yi8+l5ypvRcupT7kAay/16ytvwsz675yqTY/6N2fPtKamT5e9As/7RBuvoVaAj8fLLg+JMqfv90fMr9BqVO+ixhnPcGDPz+NOA0/HKetvzUF8b4/X/c+HDuwvmijSj+7MTg/vO4MP/2WnT4M3Rg7RPMrPhC7uz9jNXC+xO1ivgb4c76ggXg9", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000024", + "ACH-000106", + "ACH-000124", + "ACH-000167", + "ACH-000183", + "ACH-000204", + "ACH-000271", + "ACH-000315", + "ACH-000334", + "ACH-000346", + "ACH-000363", + "ACH-000365", + "ACH-000371", + "ACH-000398", + "ACH-000402", + "ACH-000405", + "ACH-000426", + "ACH-000436", + "ACH-000512", + "ACH-000541", + "ACH-000567", + "ACH-000576", + "ACH-000588", + "ACH-000653", + "ACH-000654", + "ACH-000656", + "ACH-000660", + "ACH-000697", + "ACH-000714", + "ACH-000763", + "ACH-000817", + "ACH-000821", + "ACH-000829", + "ACH-000838", + "ACH-000889", + "ACH-000914", + "ACH-000944", + "ACH-001450", + "ACH-001498", + "ACH-001533", + "ACH-001539", + "ACH-001616", + "ACH-001634", + "ACH-001639", + "ACH-001677", + "ACH-001707", + "ACH-001709", + "ACH-002055", + "ACH-002062", + "ACH-002214", + "ACH-002215", + "ACH-002478", + "ACH-002485", + "ACH-002500", + "ACH-002677", + "ACH-002678" + ], + "hoverinfo": "text", + "marker": { + "color": "#FF97FF", + "size": 7 + }, + "mode": "markers", + "name": "Mature B-Cell Neoplasms", + "text": [ + "Mature B-Cell Neoplasms | ACH-000024", + "Mature B-Cell Neoplasms | ACH-000106", + "Mature B-Cell Neoplasms | ACH-000124", + "Mature B-Cell Neoplasms | ACH-000167", + "Mature B-Cell Neoplasms | ACH-000183", + "Mature B-Cell Neoplasms | ACH-000204", + "Mature B-Cell Neoplasms | ACH-000271", + "Mature B-Cell Neoplasms | ACH-000315", + "Mature B-Cell Neoplasms | ACH-000334", + "Mature B-Cell Neoplasms | ACH-000346", + "Mature B-Cell Neoplasms | ACH-000363", + "Mature B-Cell Neoplasms | ACH-000365", + "Mature B-Cell Neoplasms | ACH-000371", + "Mature B-Cell Neoplasms | ACH-000398", + "Mature B-Cell Neoplasms | ACH-000402", + "Mature B-Cell Neoplasms | ACH-000405", + "Mature B-Cell Neoplasms | ACH-000426", + "Mature B-Cell Neoplasms | ACH-000436", + "Mature B-Cell Neoplasms | ACH-000512", + "Mature B-Cell Neoplasms | ACH-000541", + "Mature B-Cell Neoplasms | ACH-000567", + "Mature B-Cell Neoplasms | ACH-000576", + "Mature B-Cell Neoplasms | ACH-000588", + "Mature B-Cell Neoplasms | ACH-000653", + "Mature B-Cell Neoplasms | ACH-000654", + "Mature B-Cell Neoplasms | ACH-000656", + "Mature B-Cell Neoplasms | ACH-000660", + "Mature B-Cell Neoplasms | ACH-000697", + "Mature B-Cell Neoplasms | ACH-000714", + "Mature B-Cell Neoplasms | ACH-000763", + "Mature B-Cell Neoplasms | ACH-000817", + "Mature B-Cell Neoplasms | ACH-000821", + "Mature B-Cell Neoplasms | ACH-000829", + "Mature B-Cell Neoplasms | ACH-000838", + "Mature B-Cell Neoplasms | ACH-000889", + "Mature B-Cell Neoplasms | ACH-000914", + "Mature B-Cell Neoplasms | ACH-000944", + "Mature B-Cell Neoplasms | ACH-001450", + "Mature B-Cell Neoplasms | ACH-001498", + "Mature B-Cell Neoplasms | ACH-001533", + "Mature B-Cell Neoplasms | ACH-001539", + "Mature B-Cell Neoplasms | ACH-001616", + "Mature B-Cell Neoplasms | ACH-001634", + "Mature B-Cell Neoplasms | ACH-001639", + "Mature B-Cell Neoplasms | ACH-001677", + "Mature B-Cell Neoplasms | ACH-001707", + "Mature B-Cell Neoplasms | ACH-001709", + "Mature B-Cell Neoplasms | ACH-002055", + "Mature B-Cell Neoplasms | ACH-002062", + "Mature B-Cell Neoplasms | ACH-002214", + "Mature B-Cell Neoplasms | ACH-002215", + "Mature B-Cell Neoplasms | ACH-002478", + "Mature B-Cell Neoplasms | ACH-002485", + "Mature B-Cell Neoplasms | ACH-002500", + "Mature B-Cell Neoplasms | ACH-002677", + "Mature B-Cell Neoplasms | ACH-002678" + ], + "type": "scattergl", + "x": { + "bdata": "J+omQHwl4z/a75ZA1dcUQPpscUDoeTVAQ/6jQEygAUCxBoK/lL5FQB9fCr/CXmxAxpQnQI6mGkBIQgxAusJpQLnAjD5BR/XA8uskQDLarD/NDPXACkNGP2rOWUBxyQtAMAoEQPhEoUCJcqZA32hQQMBs/j9/llY/bHFGQI302j90PfXA+U7XP2Kte0DUrn5ALTRXQKn/L0CRplpA4i71wPG+pj8bYmxAn1H1wJCcjj+fMNc/LFj1wDNch0ASkSpA5MQLQAk4eECyfE5AByQpQCyYIUCKQXhAlFRvQAh4AUA=", + "dtype": "f4" + }, + "y": { + "bdata": "MOcTwGrcTr9+/wTATzXkv45bJcBrpFnALixAwKVG6r+H4hHAIMIHwDdXMcCjNDPAtAMowBmnG8BistS/SrD5v1sC4b9agXO+jPn8v3OFEcDFfYO+zHMDwNcGHsANEifAAFoqwIzEFsC+pd+/QAjbv4sEKsBks/G/kdIawGSH8b+Jvm6+sbQHwMTaEsAXQTLAr5kPwAgyNsAQ6RPA69d/vtnt07+M+kvATZF0vhXMTcCBNW6/6MB5vgHKNcDwbwPAlrHTv8AeMcARA+W/dwkNwINqmb+TIgDA3Fs+wNwqDsA=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000025", + "ACH-001067", + "ACH-002070" + ], + "hoverinfo": "text", + "marker": { + "color": "#FECB52", + "size": 7 + }, + "mode": "markers", + "name": "Meningothelial Tumor", + "text": [ + "Meningothelial Tumor | ACH-000025", + "Meningothelial Tumor | ACH-001067", + "Meningothelial Tumor | ACH-002070" + ], + "type": "scattergl", + "x": { + "bdata": "yABNQNop9cD6YO4/", + "dtype": "f4" + }, + "y": { + "bdata": "7jABQMvIc749eaQ/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000036", + "ACH-000040", + "ACH-000067", + "ACH-000075", + "ACH-000098", + "ACH-000128", + "ACH-000137", + "ACH-000152", + "ACH-000200", + "ACH-000208", + "ACH-000215", + "ACH-000231", + "ACH-000232", + "ACH-000244", + "ACH-000269", + "ACH-000273", + "ACH-000323", + "ACH-000329", + "ACH-000368", + "ACH-000370", + "ACH-000376", + "ACH-000389", + "ACH-000437", + "ACH-000445", + "ACH-000455", + "ACH-000464", + "ACH-000469", + "ACH-000479", + "ACH-000504", + "ACH-000558", + "ACH-000570", + "ACH-000571", + "ACH-000591", + "ACH-000592", + "ACH-000595", + "ACH-000609", + "ACH-000622", + "ACH-000623", + "ACH-000631", + "ACH-000634", + "ACH-000655", + "ACH-000673", + "ACH-000676", + "ACH-000738", + "ACH-000756", + "ACH-000760", + "ACH-000807", + "ACH-000819", + "ACH-000863", + "ACH-000887", + "ACH-001016", + "ACH-001126", + "ACH-001172", + "ACH-001329", + "ACH-001605", + "ACH-001606", + "ACH-001608", + "ACH-001609", + "ACH-001610", + "ACH-001611", + "ACH-001622", + "ACH-001623", + "ACH-001624", + "ACH-002228", + "ACH-002229", + "ACH-002230", + "ACH-002257", + "ACH-002269", + "ACH-002304", + "ACH-002680" + ], + "hoverinfo": "text", + "marker": { + "color": "#FD3216", + "size": 7 + }, + "mode": "markers", + "name": "Diffuse Glioma", + "text": [ + "Diffuse Glioma | ACH-000036", + "Diffuse Glioma | ACH-000040", + "Diffuse Glioma | ACH-000067", + "Diffuse Glioma | ACH-000075", + "Diffuse Glioma | ACH-000098", + "Diffuse Glioma | ACH-000128", + "Diffuse Glioma | ACH-000137", + "Diffuse Glioma | ACH-000152", + "Diffuse Glioma | ACH-000200", + "Diffuse Glioma | ACH-000208", + "Diffuse Glioma | ACH-000215", + "Diffuse Glioma | ACH-000231", + "Diffuse Glioma | ACH-000232", + "Diffuse Glioma | ACH-000244", + "Diffuse Glioma | ACH-000269", + "Diffuse Glioma | ACH-000273", + "Diffuse Glioma | ACH-000323", + "Diffuse Glioma | ACH-000329", + "Diffuse Glioma | ACH-000368", + "Diffuse Glioma | ACH-000370", + "Diffuse Glioma | ACH-000376", + "Diffuse Glioma | ACH-000389", + "Diffuse Glioma | ACH-000437", + "Diffuse Glioma | ACH-000445", + "Diffuse Glioma | ACH-000455", + "Diffuse Glioma | ACH-000464", + "Diffuse Glioma | ACH-000469", + "Diffuse Glioma | ACH-000479", + "Diffuse Glioma | ACH-000504", + "Diffuse Glioma | ACH-000558", + "Diffuse Glioma | ACH-000570", + "Diffuse Glioma | ACH-000571", + "Diffuse Glioma | ACH-000591", + "Diffuse Glioma | ACH-000592", + "Diffuse Glioma | ACH-000595", + "Diffuse Glioma | ACH-000609", + "Diffuse Glioma | ACH-000622", + "Diffuse Glioma | ACH-000623", + "Diffuse Glioma | ACH-000631", + "Diffuse Glioma | ACH-000634", + "Diffuse Glioma | ACH-000655", + "Diffuse Glioma | ACH-000673", + "Diffuse Glioma | ACH-000676", + "Diffuse Glioma | ACH-000738", + "Diffuse Glioma | ACH-000756", + "Diffuse Glioma | ACH-000760", + "Diffuse Glioma | ACH-000807", + "Diffuse Glioma | ACH-000819", + "Diffuse Glioma | ACH-000863", + "Diffuse Glioma | ACH-000887", + "Diffuse Glioma | ACH-001016", + "Diffuse Glioma | ACH-001126", + "Diffuse Glioma | ACH-001172", + "Diffuse Glioma | ACH-001329", + "Diffuse Glioma | ACH-001605", + "Diffuse Glioma | ACH-001606", + "Diffuse Glioma | ACH-001608", + "Diffuse Glioma | ACH-001609", + "Diffuse Glioma | ACH-001610", + "Diffuse Glioma | ACH-001611", + "Diffuse Glioma | ACH-001622", + "Diffuse Glioma | ACH-001623", + "Diffuse Glioma | ACH-001624", + "Diffuse Glioma | ACH-002228", + "Diffuse Glioma | ACH-002229", + "Diffuse Glioma | ACH-002230", + "Diffuse Glioma | ACH-002257", + "Diffuse Glioma | ACH-002269", + "Diffuse Glioma | ACH-002304", + "Diffuse Glioma | ACH-002680" + ], + "type": "scattergl", + "x": { + "bdata": "ygmvP89N+b29fTS/QAfnvvIPmT8iee8/f8nZP9oa/b6ZbPXAH6ZoP27ADECr7q4/hrlUQCLlEMCq4I29orkyQLJnbT9wk26+GJy1PhFm4L46kmpAetGaP4PHqz9s0Pk+hPVcQCr2zL8SfqE/4L5fP8RmAMCLasU/ct0DQMdXob84M44/i/wWv90sxz+ELTc/CIIGwFTdCr9Pf60+T9bRP/yXBz9qffXATF9MQAJDNkBIrCdAEDJvP1lx5z/p960/6lErQJYHAUCuo/Y/Eln1wBFGV0A3+1m/trwlPWARrr+/ag9AxVGrP/RbkT+pPLU/5r5YPoEJ/b6P9zO+6lz1wAY+9cCdUvXAOjxCP71yU0CAOfXA9mVkPw==", + "dtype": "f4" + }, + "y": { + "bdata": "+5M6QEexPkCn1BFAcmgTQC5XXUC5OBc/vjkYQAzSA0CnHl++dtGrP6wHBUBKvw9AbOJzP0oSP0CUIsU+6mENQOsR0T9ranI/fYFlQCBuEj+N5qA/pvIQQNfeB0D0px1A/kNLP+L9IUCLmBlALkPvP7tVAkAp8vk/oGYqQLzjtz9rwUpAQaMBQBYKBkAVCw5AZe0NP+d0IkDRjrw/YsnZP5T0ZD8w6VS+aMTUvt+2Yj/LtyBAhbUlPy2DXz6cUt8/cpkOQG8WPD/3yIo/b4FvvjN2xT7S/xtA0CbvPykpoz8jrdg/ah/AP8mQuT/Gn9M/zK06QJxMK0AzdDs/Si1wviRqYb6ImWS+OJpgQFheqz/Xvnm+xko8QA==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000037" + ], + "hoverinfo": "text", + "marker": { + "color": "#00FE35", + "size": 7 + }, + "mode": "markers", + "name": "Sarcoma, NOS", + "text": [ + "Sarcoma, NOS | ACH-000037" + ], + "type": "scattergl", + "x": { + "bdata": "LiYbvw==", + "dtype": "f4" + }, + "y": { + "bdata": "atrvPw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000039", + "ACH-000041", + "ACH-000052", + "ACH-000087", + "ACH-000210", + "ACH-000279", + "ACH-000391", + "ACH-000424", + "ACH-000499", + "ACH-001029", + "ACH-001038", + "ACH-001192", + "ACH-001193", + "ACH-001205", + "ACH-001283", + "ACH-001430", + "ACH-001431", + "ACH-002105", + "ACH-002106", + "ACH-002109", + "ACH-002110", + "ACH-002114", + "ACH-002116", + "ACH-002119", + "ACH-002160" + ], + "hoverinfo": "text", + "marker": { + "color": "#6A76FC", + "size": 7 + }, + "mode": "markers", + "name": "Ewing Sarcoma", + "text": [ + "Ewing Sarcoma | ACH-000039", + "Ewing Sarcoma | ACH-000041", + "Ewing Sarcoma | ACH-000052", + "Ewing Sarcoma | ACH-000087", + "Ewing Sarcoma | ACH-000210", + "Ewing Sarcoma | ACH-000279", + "Ewing Sarcoma | ACH-000391", + "Ewing Sarcoma | ACH-000424", + "Ewing Sarcoma | ACH-000499", + "Ewing Sarcoma | ACH-001029", + "Ewing Sarcoma | ACH-001038", + "Ewing Sarcoma | ACH-001192", + "Ewing Sarcoma | ACH-001193", + "Ewing Sarcoma | ACH-001205", + "Ewing Sarcoma | ACH-001283", + "Ewing Sarcoma | ACH-001430", + "Ewing Sarcoma | ACH-001431", + "Ewing Sarcoma | ACH-002105", + "Ewing Sarcoma | ACH-002106", + "Ewing Sarcoma | ACH-002109", + "Ewing Sarcoma | ACH-002110", + "Ewing Sarcoma | ACH-002114", + "Ewing Sarcoma | ACH-002116", + "Ewing Sarcoma | ACH-002119", + "Ewing Sarcoma | ACH-002160" + ], + "type": "scattergl", + "x": { + "bdata": "DIWCPlcphD4KdZ8/thsdQLIjlz9V7UpAk0tyQCU3j0DyikRAMshnQJhb6z9/vPg/VwPoPxxY7j+fkARAc8PTPwXXBkDiogBAl7lOQGySBUBVWphA7U/1wHBz9cDmIoNAD2t4QA==", + "dtype": "f4" + }, + "y": { + "bdata": "F6ncPh4t474dvcY/3PfOvmmndb5xT/a+RMSRP8TFaj8rhCI/O74qP5zz0L+ynJA+tmSQP2iMAj5lVgw+P1gIPxWHhr4laBJA7r+tvyxFxT6QGBk+5lJqvktxY76d8gc/iJ/7vQ==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000047", + "ACH-000144", + "ACH-000216", + "ACH-000239", + "ACH-000247", + "ACH-000255", + "ACH-000303", + "ACH-000325", + "ACH-000344", + "ACH-000356", + "ACH-000383", + "ACH-000427", + "ACH-000466", + "ACH-000485", + "ACH-000507", + "ACH-000581", + "ACH-000616", + "ACH-000633", + "ACH-000736", + "ACH-000746", + "ACH-000758", + "ACH-000764", + "ACH-000793", + "ACH-000847", + "ACH-000880", + "ACH-000898", + "ACH-000911", + "ACH-000919", + "ACH-000932", + "ACH-000948", + "ACH-001368", + "ACH-001496", + "ACH-001497", + "ACH-001500", + "ACH-001544", + "ACH-001653", + "ACH-001654", + "ACH-001664", + "ACH-002141", + "ACH-002161", + "ACH-002202", + "ACH-002446", + "ACH-002705", + "ACH-002706" + ], + "hoverinfo": "text", + "marker": { + "color": "#FED4C4", + "size": 7 + }, + "mode": "markers", + "name": "Esophagogastric Adenocarcinoma", + "text": [ + "Esophagogastric Adenocarcinoma | ACH-000047", + "Esophagogastric Adenocarcinoma | ACH-000144", + "Esophagogastric Adenocarcinoma | ACH-000216", + "Esophagogastric Adenocarcinoma | ACH-000239", + "Esophagogastric Adenocarcinoma | ACH-000247", + "Esophagogastric Adenocarcinoma | ACH-000255", + "Esophagogastric Adenocarcinoma | ACH-000303", + "Esophagogastric Adenocarcinoma | ACH-000325", + "Esophagogastric Adenocarcinoma | ACH-000344", + "Esophagogastric Adenocarcinoma | ACH-000356", + "Esophagogastric Adenocarcinoma | ACH-000383", + "Esophagogastric Adenocarcinoma | ACH-000427", + "Esophagogastric Adenocarcinoma | ACH-000466", + "Esophagogastric Adenocarcinoma | ACH-000485", + "Esophagogastric Adenocarcinoma | ACH-000507", + "Esophagogastric Adenocarcinoma | ACH-000581", + "Esophagogastric Adenocarcinoma | ACH-000616", + "Esophagogastric Adenocarcinoma | ACH-000633", + "Esophagogastric Adenocarcinoma | ACH-000736", + "Esophagogastric Adenocarcinoma | ACH-000746", + "Esophagogastric Adenocarcinoma | ACH-000758", + "Esophagogastric Adenocarcinoma | ACH-000764", + "Esophagogastric Adenocarcinoma | ACH-000793", + "Esophagogastric Adenocarcinoma | ACH-000847", + "Esophagogastric Adenocarcinoma | ACH-000880", + "Esophagogastric Adenocarcinoma | ACH-000898", + "Esophagogastric Adenocarcinoma | ACH-000911", + "Esophagogastric Adenocarcinoma | ACH-000919", + "Esophagogastric Adenocarcinoma | ACH-000932", + "Esophagogastric Adenocarcinoma | ACH-000948", + "Esophagogastric Adenocarcinoma | ACH-001368", + "Esophagogastric Adenocarcinoma | ACH-001496", + "Esophagogastric Adenocarcinoma | ACH-001497", + "Esophagogastric Adenocarcinoma | ACH-001500", + "Esophagogastric Adenocarcinoma | ACH-001544", + "Esophagogastric Adenocarcinoma | ACH-001653", + "Esophagogastric Adenocarcinoma | ACH-001654", + "Esophagogastric Adenocarcinoma | ACH-001664", + "Esophagogastric Adenocarcinoma | ACH-002141", + "Esophagogastric Adenocarcinoma | ACH-002161", + "Esophagogastric Adenocarcinoma | ACH-002202", + "Esophagogastric Adenocarcinoma | ACH-002446", + "Esophagogastric Adenocarcinoma | ACH-002705", + "Esophagogastric Adenocarcinoma | ACH-002706" + ], + "type": "scattergl", + "x": { + "bdata": "WLhTQBshJ8BPCxlA/opNPxZrKUDoZe8/mdIJQBIuGEDqf6A/D0DcP/GbFz9yYvXANyF2P71lHEBmrlJA1IbnP/HTND8AgbA/gPlJQEMCvD6f5yJAcmj1wAK8GUDtHvXADD94QC1qAT/jeltA3evlP8X1OkD3PztAGjzPP0oDPT+4rqQ/L7ckQHpu5z2xfQZAF3spQL34WkCcO4BA5+X/P74GPUCVxhZAVLciQPEjWUA=", + "dtype": "f4" + }, + "y": { + "bdata": "FveQv2c2Vb80eC0/JatOPQWBvb8B1NU/YR4vv4vSHMAQkEI/LCf6vn7Rw7/Z7nS+9qzlP3D2q79F+5K/aITvvyP+yj/qi66/zAK/v8HLGMCoro+/2tVgvna4AcDOBoG+UqaQvsv8+L8SlUm/08L7vhRX3r+THXm/2dDjv2Sn9r8Uj6W/HFdhPwkX0L8FWIe/JzPHPwM1DcDJQ8u/DgE+v82cOr5IofW+Em3Uvv7Cyb4=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000053", + "ACH-000101", + "ACH-000226", + "ACH-000233", + "ACH-000338", + "ACH-000664", + "ACH-000773", + "ACH-001111", + "ACH-001119", + "ACH-001737" + ], + "hoverinfo": "text", + "marker": { + "color": "#FE00CE", + "size": 7 + }, + "mode": "markers", + "name": "Mature T and NK Neoplasms", + "text": [ + "Mature T and NK Neoplasms | ACH-000053", + "Mature T and NK Neoplasms | ACH-000101", + "Mature T and NK Neoplasms | ACH-000226", + "Mature T and NK Neoplasms | ACH-000233", + "Mature T and NK Neoplasms | ACH-000338", + "Mature T and NK Neoplasms | ACH-000664", + "Mature T and NK Neoplasms | ACH-000773", + "Mature T and NK Neoplasms | ACH-001111", + "Mature T and NK Neoplasms | ACH-001119", + "Mature T and NK Neoplasms | ACH-001737" + ], + "type": "scattergl", + "x": { + "bdata": "EWe6P5C9Z0BdeE5AwjM9QJPJvD+sbItATXoLQPlr7j/09zG/8jMfQA==", + "dtype": "f4" + }, + "y": { + "bdata": "7uwIwIumIcDK5v+/HiW7v8fczL6mmhXAb47Xv85/hb9OAzW/aUcuPg==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000054" + ], + "hoverinfo": "text", + "marker": { + "color": "#0DF9FF", + "size": 7 + }, + "mode": "markers", + "name": "Fibrosarcoma", + "text": [ + "Fibrosarcoma | ACH-000054" + ], + "type": "scattergl", + "x": { + "bdata": "DTuBPw==", + "dtype": "f4" + }, + "y": { + "bdata": "fpSPPw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000055", + "ACH-000095", + "ACH-000160", + "ACH-000211", + "ACH-000776", + "ACH-001020", + "ACH-001028", + "ACH-001031", + "ACH-001033", + "ACH-001053", + "ACH-001054", + "ACH-001232", + "ACH-001289", + "ACH-001670", + "ACH-001711" + ], + "hoverinfo": "text", + "marker": { + "color": "#F6F926", + "size": 7 + }, + "mode": "markers", + "name": "Embryonal Tumor", + "text": [ + "Embryonal Tumor | ACH-000055", + "Embryonal Tumor | ACH-000095", + "Embryonal Tumor | ACH-000160", + "Embryonal Tumor | ACH-000211", + "Embryonal Tumor | ACH-000776", + "Embryonal Tumor | ACH-001020", + "Embryonal Tumor | ACH-001028", + "Embryonal Tumor | ACH-001031", + "Embryonal Tumor | ACH-001033", + "Embryonal Tumor | ACH-001053", + "Embryonal Tumor | ACH-001054", + "Embryonal Tumor | ACH-001232", + "Embryonal Tumor | ACH-001289", + "Embryonal Tumor | ACH-001670", + "Embryonal Tumor | ACH-001711" + ], + "type": "scattergl", + "x": { + "bdata": "/esoQHAd9z9/anFAHl5zP3E6BECd5QJA1vFTQCNMY0C6Mdg/3HTSPygGWkDQKFA/TeugPwsmOkBiSA9A", + "dtype": "f4" + }, + "y": { + "bdata": "Q8R1v+p5Lb8gP/Y+C+LtP/W6Qz/CeHU/IU+kvpUT8D6yS+M+6LWbviaXi78FYC5AOGz2vu+Q5T7U2sc+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000070", + "ACH-000151", + "ACH-000782", + "ACH-000922", + "ACH-000938", + "ACH-000960", + "ACH-001484", + "ACH-001520", + "ACH-001669", + "ACH-001735", + "ACH-001736", + "ACH-001993", + "ACH-002059" + ], + "hoverinfo": "text", + "marker": { + "color": "#FF9616", + "size": 7 + }, + "mode": "markers", + "name": "B-Lymphoblastic Leukemia/Lymphoma", + "text": [ + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000070", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000151", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000782", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000922", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000938", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000960", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001484", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001520", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001669", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001735", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001736", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001993", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-002059" + ], + "type": "scattergl", + "x": { + "bdata": "DitMQDjJqz/1ZDtAUVFtQEOATUBzyEpA6Xo1QDW7VUBJHm5AC3EhQGJAeUDe6dA/KUE+QA==", + "dtype": "f4" + }, + "y": { + "bdata": "+i4gwBykJcBwwirAq+ZBwC5PWsC1HDPAq8YAwAIsCsDFainAeBA5wOYvRcDGSwrAlaf5vw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000074", + "ACH-000076", + "ACH-000198", + "ACH-000295", + "ACH-000326", + "ACH-000551", + "ACH-000604", + "ACH-000920", + "ACH-000983", + "ACH-002061" + ], + "hoverinfo": "text", + "marker": { + "color": "#479B55", + "size": 7 + }, + "mode": "markers", + "name": "Myeloproliferative Neoplasms", + "text": [ + "Myeloproliferative Neoplasms | ACH-000074", + "Myeloproliferative Neoplasms | ACH-000076", + "Myeloproliferative Neoplasms | ACH-000198", + "Myeloproliferative Neoplasms | ACH-000295", + "Myeloproliferative Neoplasms | ACH-000326", + "Myeloproliferative Neoplasms | ACH-000551", + "Myeloproliferative Neoplasms | ACH-000604", + "Myeloproliferative Neoplasms | ACH-000920", + "Myeloproliferative Neoplasms | ACH-000983", + "Myeloproliferative Neoplasms | ACH-002061" + ], + "type": "scattergl", + "x": { + "bdata": "u1n9P1XPSkA1Y4xAHpSaP8A6X0CWkB1A6Gb9P1Obzj8DFGlADDJEQA==", + "dtype": "f4" + }, + "y": { + "bdata": "WHsbwGzt4L8QWjTAZlPLv25QBcDHQx7AuYDgv8ilFL++ByLAo6L8vw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000077", + "ACH-000583", + "ACH-001197", + "ACH-001642" + ], + "hoverinfo": "text", + "marker": { + "color": "#EEA6FB", + "size": 7 + }, + "mode": "markers", + "name": "Non-Hodgkin Lymphoma", + "text": [ + "Non-Hodgkin Lymphoma | ACH-000077", + "Non-Hodgkin Lymphoma | ACH-000583", + "Non-Hodgkin Lymphoma | ACH-001197", + "Non-Hodgkin Lymphoma | ACH-001642" + ], + "type": "scattergl", + "x": { + "bdata": "k+NUQEUn9cAoSSJABGnVPw==", + "dtype": "f4" + }, + "y": { + "bdata": "vr1nvz1chL4rKPq/i8u3vw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000078", + "ACH-000099", + "ACH-000120", + "ACH-000149", + "ACH-000203", + "ACH-000227", + "ACH-000259", + "ACH-000260", + "ACH-000310", + "ACH-000312", + "ACH-000341", + "ACH-000366", + "ACH-000804", + "ACH-001188", + "ACH-001300", + "ACH-001301", + "ACH-001302", + "ACH-001303", + "ACH-001338", + "ACH-001344", + "ACH-001354", + "ACH-001366", + "ACH-001367", + "ACH-001481", + "ACH-001548", + "ACH-001603", + "ACH-001674", + "ACH-002080", + "ACH-002083", + "ACH-002261", + "ACH-002278", + "ACH-002280", + "ACH-002282", + "ACH-002283", + "ACH-002284", + "ACH-002285", + "ACH-002922" + ], + "hoverinfo": "text", + "marker": { + "color": "#DC587D", + "size": 7 + }, + "mode": "markers", + "name": "Neuroblastoma", + "text": [ + "Neuroblastoma | ACH-000078", + "Neuroblastoma | ACH-000099", + "Neuroblastoma | ACH-000120", + "Neuroblastoma | ACH-000149", + "Neuroblastoma | ACH-000203", + "Neuroblastoma | ACH-000227", + "Neuroblastoma | ACH-000259", + "Neuroblastoma | ACH-000260", + "Neuroblastoma | ACH-000310", + "Neuroblastoma | ACH-000312", + "Neuroblastoma | ACH-000341", + "Neuroblastoma | ACH-000366", + "Neuroblastoma | ACH-000804", + "Neuroblastoma | ACH-001188", + "Neuroblastoma | ACH-001300", + "Neuroblastoma | ACH-001301", + "Neuroblastoma | ACH-001302", + "Neuroblastoma | ACH-001303", + "Neuroblastoma | ACH-001338", + "Neuroblastoma | ACH-001344", + "Neuroblastoma | ACH-001354", + "Neuroblastoma | ACH-001366", + "Neuroblastoma | ACH-001367", + "Neuroblastoma | ACH-001481", + "Neuroblastoma | ACH-001548", + "Neuroblastoma | ACH-001603", + "Neuroblastoma | ACH-001674", + "Neuroblastoma | ACH-002080", + "Neuroblastoma | ACH-002083", + "Neuroblastoma | ACH-002261", + "Neuroblastoma | ACH-002278", + "Neuroblastoma | ACH-002280", + "Neuroblastoma | ACH-002282", + "Neuroblastoma | ACH-002283", + "Neuroblastoma | ACH-002284", + "Neuroblastoma | ACH-002285", + "Neuroblastoma | ACH-002922" + ], + "type": "scattergl", + "x": { + "bdata": "Xm9AP+mTHkDgf30/cRkuQBOtET9j7e+/VONSQHdECUAyo8W/zXc0P92s5b4Xe7E/J3ZVQN/AC0AIbixAewHfvG/VWj/d9lA+YhUnQF9Gij/zJLo/P03zPxpGHkAPO0o/qGo3PwaYoj967c8/ein1wFK5ckBl20JANbMzQCeQIUD1RA9AHxwQQFlI9cDNS6dATmspQA==", + "dtype": "f4" + }, + "y": { + "bdata": "Tdwyv8WvWL9jkEw/xtSfPux4yT46Dmu/iU95vxjGez/qCR2/DuuQv3KPlD5dFsm+9i20vs9z0z7FtJa+UDXmPiHBr743CFy+62XRv5SOnj8rH2i9zNAov8DHGr91irE/LjTvPrNHKb8QadS/BTF8vhITvT9jMm6/qDoOv2V8Rb/C9wK/MsopPzncab5VWSY/+c1Cvw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000082", + "ACH-000359", + "ACH-000364", + "ACH-000410", + "ACH-000748", + "ACH-001001", + "ACH-001526", + "ACH-001715", + "ACH-001814", + "ACH-002067", + "ACH-002069", + "ACH-002471", + "ACH-002834" + ], + "hoverinfo": "text", + "marker": { + "color": "#D626FF", + "size": 7 + }, + "mode": "markers", + "name": "Osteosarcoma", + "text": [ + "Osteosarcoma | ACH-000082", + "Osteosarcoma | ACH-000359", + "Osteosarcoma | ACH-000364", + "Osteosarcoma | ACH-000410", + "Osteosarcoma | ACH-000748", + "Osteosarcoma | ACH-001001", + "Osteosarcoma | ACH-001526", + "Osteosarcoma | ACH-001715", + "Osteosarcoma | ACH-001814", + "Osteosarcoma | ACH-002067", + "Osteosarcoma | ACH-002069", + "Osteosarcoma | ACH-002471", + "Osteosarcoma | ACH-002834" + ], + "type": "scattergl", + "x": { + "bdata": "tqkRwK0axL/2lQdA5suAPzL9DUBoBWFAiAibvjQj+b5AbcS+TBajP6qLgj9bGTQ/qo71wA==", + "dtype": "f4" + }, + "y": { + "bdata": "DXmcP+yRpz++IwNANiqXPz8gN0CgQ6y+UTChP3jguT+JYBZAHyIOP7UaIkBKmbw/SeJavg==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000086", + "ACH-000092", + "ACH-000153", + "ACH-000319", + "ACH-000331", + "ACH-000335", + "ACH-000367", + "ACH-000569", + "ACH-000645", + "ACH-000648", + "ACH-001547", + "ACH-001555", + "ACH-001556", + "ACH-001557", + "ACH-001558", + "ACH-001559", + "ACH-001560", + "ACH-001562", + "ACH-001977", + "ACH-001992", + "ACH-002033" + ], + "hoverinfo": "text", + "marker": { + "color": "#6E899C", + "size": 7 + }, + "mode": "markers", + "name": "Pleural Mesothelioma", + "text": [ + "Pleural Mesothelioma | ACH-000086", + "Pleural Mesothelioma | ACH-000092", + "Pleural Mesothelioma | ACH-000153", + "Pleural Mesothelioma | ACH-000319", + "Pleural Mesothelioma | ACH-000331", + "Pleural Mesothelioma | ACH-000335", + "Pleural Mesothelioma | ACH-000367", + "Pleural Mesothelioma | ACH-000569", + "Pleural Mesothelioma | ACH-000645", + "Pleural Mesothelioma | ACH-000648", + "Pleural Mesothelioma | ACH-001547", + "Pleural Mesothelioma | ACH-001555", + "Pleural Mesothelioma | ACH-001556", + "Pleural Mesothelioma | ACH-001557", + "Pleural Mesothelioma | ACH-001558", + "Pleural Mesothelioma | ACH-001559", + "Pleural Mesothelioma | ACH-001560", + "Pleural Mesothelioma | ACH-001562", + "Pleural Mesothelioma | ACH-001977", + "Pleural Mesothelioma | ACH-001992", + "Pleural Mesothelioma | ACH-002033" + ], + "type": "scattergl", + "x": { + "bdata": "2ScXQOObKr9EWAI97RhwPWrLlj+bpiJAO0r1wCyKjD/Vv1a/VSLXP2qhZj/GUKU/KGH4PwQKrT8UZPXACjr1wF1Z9cCEMPXAL2lJQKNGN0AXSP+/", + "dtype": "f4" + }, + "y": { + "bdata": "iK3GP9RAzz+GvQFA5HQVQF7T3j+CjLE+xWFsvs6ECT9X1Ng/Mkm/P8kNJEDVm/A/c7dRP0VMBUCxDmK+m15xvsy9bL6Ll2u+Eqv/vWZojT8f2Gs+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000090", + "ACH-000115", + "ACH-000956", + "ACH-000977", + "ACH-000979", + "ACH-001422", + "ACH-001627", + "ACH-001648", + "ACH-001649" + ], + "hoverinfo": "text", + "marker": { + "color": "#00B5F7", + "size": 7 + }, + "mode": "markers", + "name": "Prostate Adenocarcinoma", + "text": [ + "Prostate Adenocarcinoma | ACH-000090", + "Prostate Adenocarcinoma | ACH-000115", + "Prostate Adenocarcinoma | ACH-000956", + "Prostate Adenocarcinoma | ACH-000977", + "Prostate Adenocarcinoma | ACH-000979", + "Prostate Adenocarcinoma | ACH-001422", + "Prostate Adenocarcinoma | ACH-001627", + "Prostate Adenocarcinoma | ACH-001648", + "Prostate Adenocarcinoma | ACH-001649" + ], + "type": "scattergl", + "x": { + "bdata": "5niCP7HAFsAfKUI/XY9KQID1pD93MEDAujD1wFUp9cCyY/XA", + "dtype": "f4" + }, + "y": { + "bdata": "q6SdP5k+L78R376/jie9v00E/D7XvsK/vs98vkiAfL4HQGa+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000096", + "ACH-000172", + "ACH-000533", + "ACH-000597", + "ACH-001099", + "ACH-001128", + "ACH-001211", + "ACH-001212", + "ACH-001532" + ], + "hoverinfo": "text", + "marker": { + "color": "#B68E00", + "size": 7 + }, + "mode": "markers", + "name": "Rhabdoid Cancer", + "text": [ + "Rhabdoid Cancer | ACH-000096", + "Rhabdoid Cancer | ACH-000172", + "Rhabdoid Cancer | ACH-000533", + "Rhabdoid Cancer | ACH-000597", + "Rhabdoid Cancer | ACH-001099", + "Rhabdoid Cancer | ACH-001128", + "Rhabdoid Cancer | ACH-001211", + "Rhabdoid Cancer | ACH-001212", + "Rhabdoid Cancer | ACH-001532" + ], + "type": "scattergl", + "x": { + "bdata": "gQ/7Pxz6AEDGinVAxe0vQHBzeECgdxNAZk0kQM7A7T+J4W9A", + "dtype": "f4" + }, + "y": { + "bdata": "eH2zPnlXgD/lvKY+JwteP1q2Nj+9qwc/p3fuPmuwpz/pf/m+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000100", + "ACH-000169", + "ACH-000607", + "ACH-000833", + "ACH-001050", + "ACH-001096", + "ACH-001184", + "ACH-001196", + "ACH-001740", + "ACH-001745", + "ACH-001750", + "ACH-001765", + "ACH-002048" + ], + "hoverinfo": "text", + "marker": { + "color": "#C9FBE5", + "size": 7 + }, + "mode": "markers", + "name": "Rhabdomyosarcoma", + "text": [ + "Rhabdomyosarcoma | ACH-000100", + "Rhabdomyosarcoma | ACH-000169", + "Rhabdomyosarcoma | ACH-000607", + "Rhabdomyosarcoma | ACH-000833", + "Rhabdomyosarcoma | ACH-001050", + "Rhabdomyosarcoma | ACH-001096", + "Rhabdomyosarcoma | ACH-001184", + "Rhabdomyosarcoma | ACH-001196", + "Rhabdomyosarcoma | ACH-001740", + "Rhabdomyosarcoma | ACH-001745", + "Rhabdomyosarcoma | ACH-001750", + "Rhabdomyosarcoma | ACH-001765", + "Rhabdomyosarcoma | ACH-002048" + ], + "type": "scattergl", + "x": { + "bdata": "OQcIQCJnGUAkqeA/+v8aQIslaD8NtFdAiPE9QNgvN0DlANI/FFUPQL5i/z9qezxAZBxsQA==", + "dtype": "f4" + }, + "y": { + "bdata": "SakQv5iQeD7fAQ4/uQibva5RL0DuAna+UnQkv0xqGz+2F949OFOOvivajD8QylK/mycWvg==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000108", + "ACH-000685" + ], + "hoverinfo": "text", + "marker": { + "color": "#FF0092", + "size": 7 + }, + "mode": "markers", + "name": "Adenosquamous Carcinoma of the Pancreas", + "text": [ + "Adenosquamous Carcinoma of the Pancreas | ACH-000108", + "Adenosquamous Carcinoma of the Pancreas | ACH-000685" + ], + "type": "scattergl", + "x": { + "bdata": "Q21bv+xvOkA=", + "dtype": "f4" + }, + "y": { + "bdata": "YnGZPkp3wz8=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000133", + "ACH-001310", + "ACH-001453", + "ACH-002210", + "ACH-002247", + "ACH-002462", + "ACH-002463", + "ACH-002464", + "ACH-002465", + "ACH-002467" + ], + "hoverinfo": "text", + "marker": { + "color": "#22FFA7", + "size": 7 + }, + "mode": "markers", + "name": "Non-Cancerous", + "text": [ + "Non-Cancerous | ACH-000133", + "Non-Cancerous | ACH-001310", + "Non-Cancerous | ACH-001453", + "Non-Cancerous | ACH-002210", + "Non-Cancerous | ACH-002247", + "Non-Cancerous | ACH-002462", + "Non-Cancerous | ACH-002463", + "Non-Cancerous | ACH-002464", + "Non-Cancerous | ACH-002465", + "Non-Cancerous | ACH-002467" + ], + "type": "scattergl", + "x": { + "bdata": "inBOP8U49cBENfg/ORyPQFk79cBSfPXAZVn1wIes9cA3ZfXAyFT1wA==", + "dtype": "f4" + }, + "y": { + "bdata": "WREnQHe2db7Lvq8/INL9v0cbdr7rFmG+UjtjvsLDWb63JGy+lztsvg==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000141", + "ACH-001607", + "ACH-001619", + "ACH-001850", + "ACH-001861", + "ACH-001961" + ], + "hoverinfo": "text", + "marker": { + "color": "#E3EE9E", + "size": 7 + }, + "mode": "markers", + "name": "Intracholecystic Papillary Neoplasm", + "text": [ + "Intracholecystic Papillary Neoplasm | ACH-000141", + "Intracholecystic Papillary Neoplasm | ACH-001607", + "Intracholecystic Papillary Neoplasm | ACH-001619", + "Intracholecystic Papillary Neoplasm | ACH-001850", + "Intracholecystic Papillary Neoplasm | ACH-001861", + "Intracholecystic Papillary Neoplasm | ACH-001961" + ], + "type": "scattergl", + "x": { + "bdata": "ho31wPBPLkBRPsK+qDdCQGd09cDhdyVA", + "dtype": "f4" + }, + "y": { + "bdata": "CmZTvgIhHb9T5aU/vgpHPrcRZr5dMpi+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000145", + "ACH-000505", + "ACH-002785" + ], + "hoverinfo": "text", + "marker": { + "color": "#86CE00", + "size": 7 + }, + "mode": "markers", + "name": "Leiomyosarcoma", + "text": [ + "Leiomyosarcoma | ACH-000145", + "Leiomyosarcoma | ACH-000505", + "Leiomyosarcoma | ACH-002785" + ], + "type": "scattergl", + "x": { + "bdata": "mskwv9vcwb+ghI+/", + "dtype": "f4" + }, + "y": { + "bdata": "a0XnP4YXxz+YzK4+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000159", + "ACH-000189", + "ACH-000234", + "ACH-000246", + "ACH-000250", + "ACH-000262", + "ACH-000272", + "ACH-000313", + "ACH-000317", + "ACH-000375", + "ACH-000385", + "ACH-000411", + "ACH-000433", + "ACH-000459", + "ACH-000484", + "ACH-000495", + "ACH-000649", + "ACH-000684", + "ACH-000709", + "ACH-000792", + "ACH-000907", + "ACH-001163", + "ACH-001194", + "ACH-001398", + "ACH-001687", + "ACH-001688", + "ACH-002150", + "ACH-002189", + "ACH-002533" + ], + "hoverinfo": "text", + "marker": { + "color": "#BC7196", + "size": 7 + }, + "mode": "markers", + "name": "Renal Cell Carcinoma", + "text": [ + "Renal Cell Carcinoma | ACH-000159", + "Renal Cell Carcinoma | ACH-000189", + "Renal Cell Carcinoma | ACH-000234", + "Renal Cell Carcinoma | ACH-000246", + "Renal Cell Carcinoma | ACH-000250", + "Renal Cell Carcinoma | ACH-000262", + "Renal Cell Carcinoma | ACH-000272", + "Renal Cell Carcinoma | ACH-000313", + "Renal Cell Carcinoma | ACH-000317", + "Renal Cell Carcinoma | ACH-000375", + "Renal Cell Carcinoma | ACH-000385", + "Renal Cell Carcinoma | ACH-000411", + "Renal Cell Carcinoma | ACH-000433", + "Renal Cell Carcinoma | ACH-000459", + "Renal Cell Carcinoma | ACH-000484", + "Renal Cell Carcinoma | ACH-000495", + "Renal Cell Carcinoma | ACH-000649", + "Renal Cell Carcinoma | ACH-000684", + "Renal Cell Carcinoma | ACH-000709", + "Renal Cell Carcinoma | ACH-000792", + "Renal Cell Carcinoma | ACH-000907", + "Renal Cell Carcinoma | ACH-001163", + "Renal Cell Carcinoma | ACH-001194", + "Renal Cell Carcinoma | ACH-001398", + "Renal Cell Carcinoma | ACH-001687", + "Renal Cell Carcinoma | ACH-001688", + "Renal Cell Carcinoma | ACH-002150", + "Renal Cell Carcinoma | ACH-002189", + "Renal Cell Carcinoma | ACH-002533" + ], + "type": "scattergl", + "x": { + "bdata": "SJ0vv4Bo9cDFbNi+iVf1wGxD9cCKVfXA04b1wGoBmr9Oe/XAl+ZOQPRrnT+1NQRAL9r9PSSwlsBzjPXA4JUSPgVOG0BVBV4/x9B8vwLmyD9RTfS/W3OBPxKX9cD6TCy+Azv1wGeS9cBgSfXAhvkXwCjzVUA=", + "dtype": "f4" + }, + "y": { + "bdata": "EfAeP/DXVr7SkvU/Z5tivtGtZL4hmFe+1p5cviFWsj/q1GO+UMW9PNC9vT8zRtc/chD2P+D62b6EeGO+5J/sPz6o8z9FDBRAjsmxP5beRUADrABA1CWcv7bySL5WTu8+VcVovui+Z74FjWy+VZFzPzt0nrs=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000163", + "ACH-000181", + "ACH-000188", + "ACH-000207", + "ACH-000228", + "ACH-000238", + "ACH-000415", + "ACH-000472", + "ACH-000500", + "ACH-000503", + "ACH-000518", + "ACH-000546", + "ACH-000548", + "ACH-000549", + "ACH-000606", + "ACH-000618", + "ACH-000619", + "ACH-000630", + "ACH-000682", + "ACH-000732", + "ACH-000735", + "ACH-000740", + "ACH-000762", + "ACH-000771", + "ACH-000778", + "ACH-000794", + "ACH-000832", + "ACH-000836", + "ACH-000846", + "ACH-001228", + "ACH-001229", + "ACH-001331", + "ACH-001332", + "ACH-001346", + "ACH-001347", + "ACH-001385", + "ACH-001509", + "ACH-001510", + "ACH-001511", + "ACH-001542", + "ACH-001543", + "ACH-001625", + "ACH-001626", + "ACH-001641", + "ACH-001675", + "ACH-001690", + "ACH-001691", + "ACH-001692", + "ACH-001694", + "ACH-001695", + "ACH-001696", + "ACH-001698", + "ACH-001699", + "ACH-001701", + "ACH-002029", + "ACH-002030", + "ACH-002042", + "ACH-002043", + "ACH-002044", + "ACH-002045", + "ACH-002212", + "ACH-002249", + "ACH-002250", + "ACH-002251", + "ACH-002265", + "ACH-002294", + "ACH-002295", + "ACH-002296", + "ACH-002297", + "ACH-002298", + "ACH-002305" + ], + "hoverinfo": "text", + "marker": { + "color": "#7E7DCD", + "size": 7 + }, + "mode": "markers", + "name": "Head and Neck Squamous Cell Carcinoma", + "text": [ + "Head and Neck Squamous Cell Carcinoma | ACH-000163", + "Head and Neck Squamous Cell Carcinoma | ACH-000181", + "Head and Neck Squamous Cell Carcinoma | ACH-000188", + "Head and Neck Squamous Cell Carcinoma | ACH-000207", + "Head and Neck Squamous Cell Carcinoma | ACH-000228", + "Head and Neck Squamous Cell Carcinoma | ACH-000238", + "Head and Neck Squamous Cell Carcinoma | ACH-000415", + "Head and Neck Squamous Cell Carcinoma | ACH-000472", + "Head and Neck Squamous Cell Carcinoma | ACH-000500", + "Head and Neck Squamous Cell Carcinoma | ACH-000503", + "Head and Neck Squamous Cell Carcinoma | ACH-000518", + "Head and Neck Squamous Cell Carcinoma | ACH-000546", + "Head and Neck Squamous Cell Carcinoma | ACH-000548", + "Head and Neck Squamous Cell Carcinoma | ACH-000549", + "Head and Neck Squamous Cell Carcinoma | ACH-000606", + "Head and Neck Squamous Cell Carcinoma | ACH-000618", + "Head and Neck Squamous Cell Carcinoma | ACH-000619", + "Head and Neck Squamous Cell Carcinoma | ACH-000630", + "Head and Neck Squamous Cell Carcinoma | ACH-000682", + "Head and Neck Squamous Cell Carcinoma | ACH-000732", + "Head and Neck Squamous Cell Carcinoma | ACH-000735", + "Head and Neck Squamous Cell Carcinoma | ACH-000740", + "Head and Neck Squamous Cell Carcinoma | ACH-000762", + "Head and Neck Squamous Cell Carcinoma | ACH-000771", + "Head and Neck Squamous Cell Carcinoma | ACH-000778", + "Head and Neck Squamous Cell Carcinoma | ACH-000794", + "Head and Neck Squamous Cell Carcinoma | ACH-000832", + "Head and Neck Squamous Cell Carcinoma | ACH-000836", + "Head and Neck Squamous Cell Carcinoma | ACH-000846", + "Head and Neck Squamous Cell Carcinoma | ACH-001228", + "Head and Neck Squamous Cell Carcinoma | ACH-001229", + "Head and Neck Squamous Cell Carcinoma | ACH-001331", + "Head and Neck Squamous Cell Carcinoma | ACH-001332", + "Head and Neck Squamous Cell Carcinoma | ACH-001346", + "Head and Neck Squamous Cell Carcinoma | ACH-001347", + "Head and Neck Squamous Cell Carcinoma | ACH-001385", + "Head and Neck Squamous Cell Carcinoma | ACH-001509", + "Head and Neck Squamous Cell Carcinoma | ACH-001510", + "Head and Neck Squamous Cell Carcinoma | ACH-001511", + "Head and Neck Squamous Cell Carcinoma | ACH-001542", + "Head and Neck Squamous Cell Carcinoma | ACH-001543", + "Head and Neck Squamous Cell Carcinoma | ACH-001625", + "Head and Neck Squamous Cell Carcinoma | ACH-001626", + "Head and Neck Squamous Cell Carcinoma | ACH-001641", + "Head and Neck Squamous Cell Carcinoma | ACH-001675", + "Head and Neck Squamous Cell Carcinoma | ACH-001690", + "Head and Neck Squamous Cell Carcinoma | ACH-001691", + "Head and Neck Squamous Cell Carcinoma | ACH-001692", + "Head and Neck Squamous Cell Carcinoma | ACH-001694", + "Head and Neck Squamous Cell Carcinoma | ACH-001695", + "Head and Neck Squamous Cell Carcinoma | ACH-001696", + "Head and Neck Squamous Cell Carcinoma | ACH-001698", + "Head and Neck Squamous Cell Carcinoma | ACH-001699", + "Head and Neck Squamous Cell Carcinoma | ACH-001701", + "Head and Neck Squamous Cell Carcinoma | ACH-002029", + "Head and Neck Squamous Cell Carcinoma | ACH-002030", + "Head and Neck Squamous Cell Carcinoma | ACH-002042", + "Head and Neck Squamous Cell Carcinoma | ACH-002043", + "Head and Neck Squamous Cell Carcinoma | ACH-002044", + "Head and Neck Squamous Cell Carcinoma | ACH-002045", + "Head and Neck Squamous Cell Carcinoma | ACH-002212", + "Head and Neck Squamous Cell Carcinoma | ACH-002249", + "Head and Neck Squamous Cell Carcinoma | ACH-002250", + "Head and Neck Squamous Cell Carcinoma | ACH-002251", + "Head and Neck Squamous Cell Carcinoma | ACH-002265", + "Head and Neck Squamous Cell Carcinoma | ACH-002294", + "Head and Neck Squamous Cell Carcinoma | ACH-002295", + "Head and Neck Squamous Cell Carcinoma | ACH-002296", + "Head and Neck Squamous Cell Carcinoma | ACH-002297", + "Head and Neck Squamous Cell Carcinoma | ACH-002298", + "Head and Neck Squamous Cell Carcinoma | ACH-002305" + ], + "type": "scattergl", + "x": { + "bdata": "3LxePzs2AkDYNBZA+lL1wDlf9cD9IN0/uG/1wIUzjT5zSDg/zm/1wL7VY0Bg30tARd3qPgmFCkBcXyJA88tuQKq4XEAk+RFAveJBQNyb6T9wpwBA/t6/P7cR9j+HYvXAZ4AkvXngOUC5l5NA6XwbQASrbEAaAlG+RkHePzp19cCMePXAoyITQPDxGkDiWlxAw2eWP7UjFEDbZjU+QUqDQNjSD0Ao7yq/znubv61T9cA99f4/NslPQCzQXD+MwU9Ac0suQCLqD0AM+B1AHW8AQAuZcEA0uCVACkCAQN/ELkDscoa+Y5AjQGycc0AV2DJAuGb1wJABd0BCc4Q/ScVMQAlF9cA/rSpAiuNbP9ygjEDtAGFAF3x6QD1l9cA=", + "dtype": "f4" + }, + "y": { + "bdata": 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ACH-002041" + ], + "type": "scattergl", + "x": { + "bdata": "QZrQPzuE8j/0Zco+ti6Sv8VlCcC1eo4/Ds4YPw==", + "dtype": "f4" + }, + "y": { + "bdata": "vw3SP5GYyT/AZSZAp5hOP/nwk72qnaA/hGEbQA==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000182", + "ACH-000377", + "ACH-001862", + "ACH-002023" + ], + "hoverinfo": "text", + "marker": { + "color": "#E48F72", + "size": 7 + }, + "mode": "markers", + "name": "Ampullary Carcinoma", + "text": [ + "Ampullary Carcinoma | ACH-000182", + "Ampullary Carcinoma | ACH-000377", + "Ampullary Carcinoma | ACH-001862", + "Ampullary Carcinoma | ACH-002023" + ], + "type": "scattergl", + "x": { + "bdata": "okP1wF9K9cCtYQK/I6ggQA==", + "dtype": "f4" + }, + "y": { + "bdata": "+rB/vp1Rbb5jYXg+ulJgvw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000187", + "ACH-000257", + "ACH-000290", + "ACH-000292", + "ACH-000355", + "ACH-000431", + "ACH-000514", + "ACH-000515", + "ACH-000525", + "ACH-000559", + "ACH-000639", + "ACH-000695", + "ACH-000698", + "ACH-000749", + "ACH-000767", + "ACH-000775", + "ACH-000790", + "ACH-000800", + "ACH-000866", + "ACH-000871", + "ACH-000890", + "ACH-000912", + "ACH-001386", + "ACH-001549", + "ACH-002051", + "ACH-002052", + "ACH-002077" + ], + "hoverinfo": "text", + "marker": { + "color": "#2E91E5", + "size": 7 + }, + "mode": "markers", + "name": "Lung Neuroendocrine Tumor", + "text": [ + "Lung Neuroendocrine Tumor | ACH-000187", + "Lung Neuroendocrine Tumor | ACH-000257", + "Lung Neuroendocrine Tumor | ACH-000290", + "Lung Neuroendocrine Tumor | ACH-000292", + "Lung Neuroendocrine Tumor | ACH-000355", + "Lung Neuroendocrine Tumor | ACH-000431", + "Lung Neuroendocrine Tumor | ACH-000514", + "Lung Neuroendocrine Tumor | ACH-000515", + "Lung Neuroendocrine Tumor | ACH-000525", + "Lung Neuroendocrine Tumor | ACH-000559", + "Lung Neuroendocrine Tumor | ACH-000639", + "Lung Neuroendocrine Tumor | ACH-000695", + "Lung Neuroendocrine Tumor | ACH-000698", + "Lung Neuroendocrine Tumor | ACH-000749", + "Lung Neuroendocrine Tumor | ACH-000767", + "Lung Neuroendocrine Tumor | ACH-000775", + "Lung Neuroendocrine Tumor | ACH-000790", + "Lung Neuroendocrine Tumor | ACH-000800", + "Lung Neuroendocrine Tumor | ACH-000866", + "Lung Neuroendocrine Tumor | ACH-000871", + "Lung Neuroendocrine Tumor | ACH-000890", + "Lung Neuroendocrine Tumor | ACH-000912", + "Lung Neuroendocrine Tumor | ACH-001386", + "Lung Neuroendocrine Tumor | ACH-001549", + "Lung Neuroendocrine Tumor | ACH-002051", + "Lung Neuroendocrine Tumor | ACH-002052", + "Lung Neuroendocrine Tumor | ACH-002077" + ], + "type": "scattergl", + "x": { + "bdata": "v60WP1hRub4G5NQ+k1ZWQNpHVECeBZE7p+yev4/PDEBR15w/uLiAvw4kOUDpLlG/k4riPxzn6j+RSKG/inv7P39cE0BmUQBAeypAQADJOkA8Olk/LC0pQMQi3704ydE+Cgvzv96bf7/PwYa/", + "dtype": "f4" + }, + "y": { + "bdata": "iZ8pwNhWvr840gXA1OmiPhRzBr8wiW+/pfLav5u6X7/r2bG/AGiuv1SXDsDVg36/g6UewLpKa77t1/m/Ljf4vrkQoL9JjFA/cnazv12ynr8uywdAcY8HP391w79Adau/u/jKv+rm6L+rpWS/", + "dtype": "f4" + } + }, + { + "customdata": [ + 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"Endometrial Carcinoma | ACH-000941", + "Endometrial Carcinoma | ACH-000946", + "Endometrial Carcinoma | ACH-000961", + "Endometrial Carcinoma | ACH-000965", + "Endometrial Carcinoma | ACH-000972", + "Endometrial Carcinoma | ACH-000974", + "Endometrial Carcinoma | ACH-000978", + "Endometrial Carcinoma | ACH-000984", + "Endometrial Carcinoma | ACH-000988", + "Endometrial Carcinoma | ACH-000993", + "Endometrial Carcinoma | ACH-000994", + "Endometrial Carcinoma | ACH-000996", + "Endometrial Carcinoma | ACH-001495", + "Endometrial Carcinoma | ACH-001517", + "Endometrial Carcinoma | ACH-001518", + "Endometrial Carcinoma | ACH-002026", + "Endometrial Carcinoma | ACH-002027", + "Endometrial Carcinoma | ACH-002046" + ], + "type": "scattergl", + "x": { + "bdata": "Y1IewEPDAsDLISE+GpczP8fQiD82IAs+x1b1wP/pdD/V/CJAhF9KQDL5jb/V0QtAfgs4QD2jcEDKcPXAPfMxQJVcbj+yhW2/S9tOP6vEhz+CZ/XAZF3RPp0kHL8FHSjAQqf1wLxyKkD09co/oaoSPw==", + "dtype": "f4" + }, + "y": { + "bdata": 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ACH-001538", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001673", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001834", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001835", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001836", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001838", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001839", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001841", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001842", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001843", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001844", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001848", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001849", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001852", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001856", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001857", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001858", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001863", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001864", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001959", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001960", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001997", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-002647" + ], + "type": "scattergl", + "x": { + "bdata": "8Fv1wOZT9cCSKvXAEcSSP1aw3D95UMU/N0IMQHi1RUDXfPXAu4j1wNqF9cB3e/XAl2L1wOtV9cCy9Xc/gWb1wA5o9cAmb/XAkyL1wIbubUC1DbM/IVLcP4v9E0A3jPXArScqP2TZcUAPKiNAMVT1wA5JG0A=", + "dtype": "f4" + }, + "y": { + "bdata": "vAhrvoXAYb7Oe3G+GCm8PqQLHz87R+I//cvuP3889b/jRk++TsBfvm80W77v4ma+DRdnvlkdar6qXrY/9ANkvi+Tcb4HHVy+Jv1+voETWT7hS6I/Lqy+vR57kj60gF6+zyPuvhYE1rvh3LU/Wixnvlx9gj8=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000217", + "ACH-000221", + "ACH-000316", + "ACH-000361", + 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Carcinoma | ACH-000493", + "Hepatocellular Carcinoma | ACH-000537", + "Hepatocellular Carcinoma | ACH-000577", + "Hepatocellular Carcinoma | ACH-000620", + "Hepatocellular Carcinoma | ACH-000734", + "Hepatocellular Carcinoma | ACH-000848", + "Hepatocellular Carcinoma | ACH-001318", + "Hepatocellular Carcinoma | ACH-002523" + ], + "type": "scattergl", + "x": { + "bdata": "JCnUP9pFVUBKWcw/YsavP26grL+hdeG+UjkPQJvqnj851AxAj1wSv9meQT71JyxARB9tvyHdUT+m37c//D3zv0Tloj9Z/jxA7DtEQKam9T+iDPQ/", + "dtype": "f4" + }, + "y": { + "bdata": "4f8QPtPO377vozxAypmIP/Hf6z8NK+o/y7Y+QGxPDEC7JC09weWlPgX8/D9Ey4A/KxLrP4hbDECtX8Y/uH+mP25HgL6yqTS/Bpc6vxlLVD5iA0BA", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000305", + "ACH-000318", + "ACH-000408", + "ACH-000452", + "ACH-000488", + "ACH-000544", + "ACH-000561", + "ACH-000605", + "ACH-000637", + "ACH-000647", + "ACH-000693", + "ACH-000694", + "ACH-000717", + "ACH-000777", + "ACH-000784", + "ACH-000809", + "ACH-000823", + "ACH-000824", + "ACH-000855", + 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Squamous Cell Carcinoma | ACH-000784", + "Esophageal Squamous Cell Carcinoma | ACH-000809", + "Esophageal Squamous Cell Carcinoma | ACH-000823", + "Esophageal Squamous Cell Carcinoma | ACH-000824", + "Esophageal Squamous Cell Carcinoma | ACH-000855", + "Esophageal Squamous Cell Carcinoma | ACH-000865", + "Esophageal Squamous Cell Carcinoma | ACH-000873", + "Esophageal Squamous Cell Carcinoma | ACH-000917", + "Esophageal Squamous Cell Carcinoma | ACH-002243", + "Esophageal Squamous Cell Carcinoma | ACH-002263" + ], + "type": "scattergl", + "x": { + "bdata": "B89eP+s5JUCKxjlAUiRRP+F/eEC+5jdAqmXiP2Tb2j99/Lo/69QfPRltgUAGHBpA1aqqP/fCMEC9HChANmlmQHGvP0DdxBVA1VddQAYcQ0CI4VFAyRIsQLJmEEAtSD1A", + "dtype": "f4" + }, + "y": { + "bdata": "7Ba9Pnq/kz5m/qk+/P2XP1BuCr94QFs/67Hgvvr5Kz9wFqc/ELxHvdgVLT4vTHE+mKBDP/JiDz8mY5s+urSmvgSfC77hh0c/E+voPkTflz9Jb9K+bzYmvwxPoj98w/e+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000456" + ], + "hoverinfo": "text", + "marker": { + "color": "#B68100", + 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true, + true, + true, + true + ] + }, + { + "title": "PCA Highlighted: Salivary Carcinoma" + } + ], + "label": "Salivary Carcinoma", + "method": "update" + } + ], + "direction": "down", + "showactive": true, + "x": 1.15, + "xanchor": "left", + "y": 1.15, + "yanchor": "top" + } + ], + "width": 1500, + "xaxis": { + "title": { + "text": "PCA1" + } + }, + "yaxis": { + "title": { + "text": "PCA2" + } + } + } + } + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "92e3889c12d5473f886a52d78b22ca39", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Output()" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Assuming combined_df is your full dataset\n", + "reactome_fig, reactome_out = make_dropdown_pca_with_selection(\n", + " reactome_matrix, \"PCA: Reactome Subset\"\n", + ")\n", + "corum_fig, corum_out = make_dropdown_pca_with_selection(\n", + " corum_matrix, \"PCA: CORUM Subset\"\n", + ")\n", + "drug_fig, drug_out = make_dropdown_pca_with_selection(drug_matrix, \"PCA: Drug Subset\")\n", + "\n", + "# Show plots\n", + "reactome_fig.show()\n", + "display(reactome_out)\n", + "\n", + "corum_fig.show()\n", + "display(corum_out)\n", + "\n", + "drug_fig.show()\n", + "display(drug_out)\n", + "\n", + "# Save HTMLs\n", + "reactome_fig.write_html(\"pca_reactome.html\")\n", + "corum_fig.write_html(\"pca_corum.html\")\n", + "drug_fig.write_html(\"pca_drug.html\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "abstract_embedding", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.14" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/9.webapp/8.spider_plots.ipynb b/9.webapp/8.spider_plots.ipynb new file mode 100644 index 0000000..829b73e --- /dev/null +++ b/9.webapp/8.spider_plots.ipynb @@ -0,0 +1,266 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "d32e077c", + "metadata": {}, + "outputs": [], + "source": [ + "import textwrap\n", + "\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import pandas as pd" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "4e20869b", + "metadata": {}, + "outputs": [], + "source": [ + "model_ids = [\"ACH-000323\", \"ACH-002083\", \"ACH-002228\"]\n", + "files = {\n", + " \"Reactome Pathways\": \"../5.drug-dependency/results/all_reactome_results.parquet\",\n", + " \"CORUM Complexes\": \"../5.drug-dependency/results/all_corum_results.parquet\",\n", + " \"Drug Responses\": \"../5.drug-dependency/results/all_drug_results.parquet\",\n", + "}\n", + "# Adjust these if your column names differ\n", + "feature_colnames = {\n", + " \"Reactome Pathways\": \"reactome_pathway\",\n", + " \"CORUM Complexes\": \"reactome_pathway\",\n", + " \"Drug Responses\": \"name\",\n", + "}\n", + "score_col = \"pathway_score\"\n", + "\n", + "model_colors = {\n", + " \"ACH-000323\": \"#00FFFF\", # cyan\n", + " \"ACH-002083\": \"#FF69B4\", # pink\n", + " \"ACH-002228\": \"#800080\", # purple\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "08894e82", + "metadata": {}, + "outputs": [], + "source": [ + "def clean_label(x: str) -> str:\n", + " \"\"\"\n", + " Clean or override specific long labels before truncation.\n", + " \"\"\"\n", + " # Polymerase switching\n", + " if \"Polymerase Switching\" in x:\n", + " return \"Polymerase Switching\"\n", + "\n", + " # Negative MET regulation\n", + " if \"Negative Regulation Of MET\" in x or \"Negative Regulation of MET\" in x:\n", + " return \"Negative MET Regulation\"\n", + "\n", + " return truncate_label(x)\n", + "\n", + "\n", + "def truncate_label(\n", + " label: str,\n", + " max_chars_per_line: int = 22,\n", + " max_total_words: int = 4,\n", + " max_lines: int = 2,\n", + ") -> str:\n", + " \"\"\"\n", + " Truncate a label according to character and line limits.\n", + " \"\"\"\n", + " words = label.split()\n", + " short = \" \".join(words[:max_total_words])\n", + "\n", + " # Wrap\n", + " lines = textwrap.wrap(short, width=max_chars_per_line)\n", + "\n", + " # clamp to max lines\n", + " if len(lines) > max_lines:\n", + " lines = lines[:max_lines]\n", + "\n", + " wrapped = \"\\n\".join(lines)\n", + "\n", + " # Determine if truncated\n", + " if len(words) > max_total_words or (\n", + " len(lines) >= max_lines\n", + " and len(lines) < len(textwrap.wrap(short, width=max_chars_per_line))\n", + " ):\n", + " wrapped += \"...\"\n", + "\n", + " return wrapped\n", + "\n", + "\n", + "def place_labels_polar(ax, angles, labels, radius: float) -> None:\n", + " \"\"\"\n", + " Place labels around a polar plot at a given radius.\n", + " \"\"\"\n", + " for angle, label in zip(angles[:-1], labels):\n", + " r = radius\n", + "\n", + " # left / right alignment\n", + " if 0 <= angle <= np.pi / 2 or 3 * np.pi / 2 <= angle <= 2 * np.pi:\n", + " ha = \"left\"\n", + " else:\n", + " ha = \"right\"\n", + "\n", + " ax.text(\n", + " angle, r, label, fontsize=9, color=\"black\", ha=ha, va=\"center\", wrap=True\n", + " )\n", + "\n", + " return None\n", + "\n", + "\n", + "def make_radar(\n", + " ax,\n", + " df: pd.DataFrame,\n", + " feature_col: str,\n", + " title: str,\n", + " global_max: float,\n", + " num_circles: int = 5,\n", + ") -> None:\n", + " \"\"\"\n", + " Draw a radar plot on an existing polar matplotlib axis.\n", + " \"\"\"\n", + " df = df[df[\"ModelID\"].isin(model_ids)].copy()\n", + "\n", + " # Top 5 per model, union of all\n", + " top_by_model = (\n", + " df.groupby(\"ModelID\", group_keys=False)\n", + " .apply(lambda x: x.nlargest(5, score_col))\n", + " .reset_index(drop=True)\n", + " )\n", + " top_features = top_by_model[feature_col].drop_duplicates().tolist()\n", + " n_vars = len(top_features)\n", + " labels = [clean_label(x) for x in top_features]\n", + "\n", + " # Angles\n", + " angles = np.linspace(0, 2 * np.pi, n_vars, endpoint=False).tolist()\n", + " angles += [angles[0]]\n", + "\n", + " # Reference circles\n", + " circle_levels = np.linspace(0, global_max, num_circles + 1)[1:]\n", + " for r in circle_levels:\n", + " circle_vals = [r] * (n_vars + 1)\n", + " ax.plot(\n", + " angles, circle_vals, color=\"grey\", linestyle=\"--\", linewidth=1, zorder=0\n", + " )\n", + "\n", + " # Plot each model\n", + " for mid in model_ids:\n", + " subset = df[df[\"ModelID\"] == mid]\n", + "\n", + " merged = pd.DataFrame({feature_col: top_features}).merge(\n", + " subset[[feature_col, score_col]], on=feature_col, how=\"left\"\n", + " )\n", + "\n", + " values = merged[score_col].fillna(0).tolist()\n", + " values += [values[0]]\n", + "\n", + " ax.plot(angles, values, color=model_colors[mid], linewidth=3, label=mid)\n", + " ax.scatter(\n", + " angles, values, color=model_colors[mid], s=30, edgecolor=\"black\", zorder=5\n", + " )\n", + "\n", + " # Axis styling\n", + " ax.set_ylim(0, global_max * 1.25)\n", + " ax.set_xticks([])\n", + " ax.set_yticks([])\n", + " ax.set_aspect(\"equal\")\n", + "\n", + " # Labels\n", + " label_radius = global_max * 1.4\n", + " place_labels_polar(ax, angles, labels, label_radius)\n", + "\n", + " # Title\n", + " ax.set_title(title, fontsize=18, pad=30, fontweight=\"bold\", y=1)\n", + "\n", + " return None" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "fb8024f8", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
    " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "global_max = 0\n", + "dfs = {}\n", + "for name, file in files.items():\n", + " df = pd.read_parquet(file)\n", + " dfs[name] = df\n", + " if df[score_col].max() > global_max:\n", + " global_max = df[score_col].max()\n", + "\n", + "# --- Create one combined figure ---\n", + "fig, axes = plt.subplots(3, 1, figsize=(18, 12), subplot_kw=dict(polar=True))\n", + "\n", + "for ax, (title, df) in zip(axes, dfs.items()):\n", + " make_radar(ax, df, feature_colnames[title], title, global_max)\n", + "\n", + "# Shared legend (one for all)\n", + "handles, labels = axes[0].get_legend_handles_labels()\n", + "\n", + "fig.legend(\n", + " handles,\n", + " labels,\n", + " loc=\"lower center\",\n", + " ncol=3,\n", + " fontsize=12,\n", + " frameon=False,\n", + " bbox_to_anchor=(0.5, -0.05),\n", + ")\n", + "\n", + "plt.tight_layout(rect=[0, 0, 1, 0.95])\n", + "# plt.savefig(\"visualize/combined_radar_plots.png\", dpi=600,\n", + "# bbox_inches=\"tight\", transparent=True)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "301ec03f", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv (3.13.1)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.1" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/9.webapp/Justfile b/9.webapp/Justfile new file mode 100644 index 0000000..8980fd7 --- /dev/null +++ b/9.webapp/Justfile @@ -0,0 +1,18 @@ +set shell := ["bash", "-eu", "-o", "pipefail", "-c"] + +default: + just --list + +download-data: + python download_data.py + +create-uv-env: + uv venv .venv ; uv sync + +build: + uv run streamlit run app.py + +deploy: + PORT="${PORT:-8501}" uv run streamlit run app.py --server.address 0.0.0.0 --server.headless true --server.port "$PORT" --server.fileWatcherType none + +all: create-uv-env build diff --git a/9.webapp/app.py b/9.webapp/app.py new file mode 100644 index 0000000..8cd52b7 --- /dev/null +++ b/9.webapp/app.py @@ -0,0 +1,305 @@ +""" +Gene Process Dependency Explorer +Streamlit app for exploring DepMap gene dependency latent representations. +Reproduces the analysis pattern from: + - WayScience/gene-process-dependencies 8.shiny-app/1.latent-pcas.ipynb (PCA plots) + - WayScience/gene-process-dependencies 5.drug-dependency/8.spider_plots.ipynb (spider plots) + +Data schema mirrors the real DepMap / BioBombe outputs: + - Models: PCA, ICA, NMF, DAE, VAE, β-VAE, β-TCVAE + - Metadata: primary_disease, lineage, cell_line (CCLE name) + - PCA columns: pca_1, pca_2 (per model + latent_dim) + - Spider columns: mean dependency score per biological process category +""" + +import colorsys +import pathlib +import random +import sys +import textwrap + +import ipywidgets as widgets +import joblib +import matplotlib.pyplot as plt +import numpy as np +import pandas as pd +import plotly.express as px +import plotly.graph_objects as go +import plotly.graph_objs as go +import streamlit as st +from app_utils import ( + clean_label, + generate_random_palette, + latent_load_data, + load_data, + load_model_data, + make_dropdown_pca_with_selection, + make_radar, + place_labels_polar, + single_load_data, + spider_load_data, + truncate_label, +) +from plotly.subplots import make_subplots +from sklearn.decomposition import PCA +from sklearn.preprocessing import StandardScaler + +# ── Page config ─────────────────────────────────────────────────────────────── +st.set_page_config( + page_title="Gene Process Dependency Explorer", + page_icon="🧬", + layout="wide", + initial_sidebar_state="expanded", +) + + +# ── Styling ─────────────────────────────────────────────────────────────────── +st.markdown( + """ + +""", + unsafe_allow_html=True, +) + + +# ── Sidebar controls ────────────────────────────────────────────────────────── +with st.sidebar: + st.markdown("## 🧬 Controls") + st.markdown("---") + reactome_matrix, corum_matrix, drug_matrix = latent_load_data() + # st.markdown("**DISEASE TYPES**") + # selected_diseases = st.multiselect( + # "Primary diseases", + # PRIMARY_DISEASES, + # default=PRIMARY_DISEASES[:8], + # label_visibility="collapsed", + # ) + selected_diseases = st.multiselect( + "Primary diseases", + reactome_matrix["OncotreePrimaryDisease"].unique(), + default=reactome_matrix["OncotreePrimaryDisease"].unique(), + label_visibility="collapsed", + ) + + model_ids = st.multiselect( + "ModelIds (for spider plots)", + ["ACH-000323", "ACH-002083", "ACH-002228"], + default=["ACH-000323", "ACH-002083", "ACH-002228"], + label_visibility="collapsed", + ) + + st.markdown("---") + st.markdown( + 'Data: DepMap synthetic (mirrors WayScience/gene-process-dependencies schema)', + unsafe_allow_html=True, + ) + + +# ── Header ──────────────────────────────────────────────────────────────────── +st.markdown("# Gene Process Dependency Explorer") +st.markdown( + 'DepMap · BioBombe · WayScience', + unsafe_allow_html=True, +) + + +# ── Tabs ────────────────────────────────────────────────────────────────────── +# tab_single = st.tabs( +# tab_single, tab_latent= st.tabs( +(tab_spider,) = st.tabs(["🕷 Spider Plots"]) +# tab_single, = st.tabs(["📍 single dependency plots"]) +# tab_latent, = st.tabs(["📍 latent plots"]) +# tab_single, tab_latent, tab_spider = st.tabs( +# ["📍 single dependency plots", "📍 latent plots", "🕷 Spider Plots"] +# ["📍 single dependency plots", "📍 latent plots", "🕷 Spider Plots"] + + +# # ───────────────────────────────────────────────────────────────────────────── +# # TAB 1: PCA +# # ───────────────────────────────────────────────────────────────────────────── +# with tab_latent: +# st.markdown("### Latent Space PCA Projections") +# st.markdown( +# "PCA projection of latent representations learned by the selected compression model. " +# "Each point is a cancer cell line; clusters indicate similar gene dependency profiles." +# ) + + +# reactome_matrix, corum_matrix, drug_matrix = latent_load_data() +# # add a way to show all diseases or select specific ones + +# reactome_matrix = reactome_matrix[reactome_matrix["OncotreePrimaryDisease"].isin(selected_diseases)] +# corum_matrix = corum_matrix[corum_matrix["OncotreePrimaryDisease"].isin(selected_diseases)] +# drug_matrix = drug_matrix[drug_matrix["OncotreePrimaryDisease"].isin(selected_diseases)] +# # Assuming combined_df is your full dataset +# reactome_fig, reactome_out = make_dropdown_pca_with_selection(reactome_matrix, "PCA: Reactome Subset") +# corum_fig, corum_out = make_dropdown_pca_with_selection(corum_matrix, "PCA: CORUM Subset") +# drug_fig, drug_out = make_dropdown_pca_with_selection(drug_matrix, "PCA: Drug Subset") +# st.plotly_chart(reactome_fig, use_container_width=True) +# st.plotly_chart(corum_fig, use_container_width=True) +# st.plotly_chart(drug_fig, use_container_width=True) + + +# ───────────────────────────────────────────────────────────────────────────── +# TAB 2: PCA single +# ───────────────────────────────────────────────────────────────────────────── +with tab_single: + st.markdown("### Latent Space PCA Projections") + st.markdown( + "PCA projection of latent representations learned by the selected compression model. " + "Each point is a cancer cell line; clusters indicate similar gene dependency profiles." + ) + # st.markdown("**(Placeholder for latent space PCA plots)**") + + combined_df = single_load_data() + combined_df = combined_df[ + combined_df["OncotreePrimaryDisease"].isin(selected_diseases) + ] + gene_cols = combined_df.columns.drop("ModelID") + gene_cols = gene_cols.drop("OncotreePrimaryDisease") + + # Prepare PCA input (excluding non-numeric columns) + pca_input = combined_df[gene_cols].apply(pd.to_numeric, errors="coerce") + pca = PCA(n_components=2, random_state=0) + pca_embedding = pca.fit_transform(pca_input) + + # Add PCA components to the dataframe + combined_df["PCA1"] = pca_embedding[:, 0] + combined_df["PCA2"] = pca_embedding[:, 1] + + # Prepare color map for each cancer type + cancer_types = combined_df["OncotreePrimaryDisease"].unique() + color_map = ( + px.colors.qualitative.Plotly + + px.colors.qualitative.Light24 + + px.colors.qualitative.Dark24 + ) + highlight_color_map = { + cancer: color_map[i % len(color_map)] for i, cancer in enumerate(cancer_types) + } + default_colors = [highlight_color_map[cancer] for cancer in cancer_types] + + # Create one trace per cancer type + traces = [] + for cancer in cancer_types: + df_subset = combined_df[combined_df["OncotreePrimaryDisease"] == cancer] + trace = go.Scatter( + x=df_subset["PCA1"], + y=df_subset["PCA2"], + mode="markers", + name=cancer, + marker=dict(size=7), + text=[f"{cancer} | {model_id}" for model_id in df_subset["ModelID"]], + hoverinfo="text", + ) + traces.append(trace) + import plotly.graph_objects as go + import streamlit as st + + # Create the figure + fig = go.Figure(data=traces) + + # Set default colors + for i, trace in enumerate(fig.data): + trace.marker.color = default_colors[i] + + st.plotly_chart(fig, use_container_width=True) + # fig.write_html("achilles_pca.html") + +# ───────────────────────────────────────────────────────────────────────────── +# TAB 3: Spider / Radar plots +# ───────────────────────────────────────────────────────────────────────────── +with tab_spider: + st.markdown("### Biological Process Dependency Profiles — Spider Plots") + st.markdown( + "Mean dependency score per biological process category for selected diseases. " + "Negative scores indicate stronger dependencies (essential genes). " + "Each axis = one process; the profile shape captures cancer-type-specific vulnerabilities." + ) + + # --- Create one combined figure --- + fig, axes = plt.subplots(3, 1, figsize=(18, 12), subplot_kw=dict(polar=True)) + + for ax, (title, df) in zip(axes, dfs.items()): + df = df[df["ModelID"].isin(model_ids)].copy() + make_radar(ax, df, feature_colnames[title], title, global_max) + + # Shared legend (one for all) + handles, labels = axes[0].get_legend_handles_labels() + + fig.legend( + handles, + labels, + loc="lower center", + ncol=3, + fontsize=12, + frameon=False, + bbox_to_anchor=(0.5, -0.05), + ) + + plt.tight_layout(rect=[0, 0, 1, 0.95]) + st.pyplot(fig) diff --git a/9.webapp/app_utils.py b/9.webapp/app_utils.py new file mode 100644 index 0000000..688a57a --- /dev/null +++ b/9.webapp/app_utils.py @@ -0,0 +1,432 @@ +import colorsys +import pathlib +import random +import textwrap + +import ipywidgets as widgets +import matplotlib.pyplot as plt +import numpy as np +import pandas as pd +import plotly.express as px +import plotly.graph_objs as go +from ipywidgets import widgets +from sklearn.decomposition import PCA + + +# ── Load & filter data ──────────────────────────────────────────────────────── +def load_data(): + # Load dependency data + data_directory = pathlib.Path("../0.data-download/data").resolve() + dependency_file = pathlib.Path( + f"{data_directory}/CRISPRGeneEffect.parquet" + ).resolve() + gene_dict_file = pathlib.Path( + f"{data_directory}/CRISPR_gene_dictionary.parquet" + ).resolve() + dependency_df, gene_dict_df = load_model_data(dependency_file, gene_dict_file) + dependency_df = dependency_df.set_index("ModelID") + cancer_type_input_file = pathlib.Path("../0.data-download/data/Model.parquet") + cancer_type_df = pd.read_parquet(cancer_type_input_file) + + +def latent_load_data(): + # latent space data + cancer_type_input_file = pathlib.Path("../0.data-download/data/Model.parquet") + cancer_type_df = pd.read_parquet(cancer_type_input_file) + + reactome_dims = pathlib.Path( + "../5.drug-dependency/results/all_reactome_results.parquet" + ) + reactome_df = pd.read_parquet(reactome_dims) + + corum_dims = pathlib.Path("../5.drug-dependency/results/all_corum_results.parquet") + corum_df = pd.read_parquet(corum_dims) + + drug_dims = pathlib.Path("../5.drug-dependency/results/all_drug_results.parquet") + drug_df = pd.read_parquet(drug_dims) + # Step 2: Subset based on matching keys + subset_keys = ["model", "latent_dim_total", "init", "z"] + + # Replace latent identifiers with pathway + reactome_df["feature"] = reactome_df["reactome_pathway"] + reactome_df = reactome_df.drop( + columns=["model", "latent_dim_total", "init", "seed", "z", "reactome_pathway"] + ) + + corum_df["feature"] = corum_df["reactome_pathway"] + corum_df = corum_df.drop( + columns=["model", "latent_dim_total", "init", "seed", "z", "reactome_pathway"] + ) + + drug_df["feature"] = drug_df["name"] + drug_df = drug_df.drop( + columns=["model", "latent_dim_total", "init", "seed", "z", "name"] + ) + drug_df_sorted = drug_df.sort_values( + by=["OncotreePrimaryDisease", "ModelID", "feature"], ascending=True + ) + # Create a unique column name by combining feature and source + meta_cols = ["ModelID", "OncotreePrimaryDisease"] + reactome_meta = reactome_df[meta_cols].drop_duplicates() + corum_meta = corum_df[meta_cols].drop_duplicates() + drug_meta = drug_df[meta_cols].drop_duplicates() + + # Pivot to wide format + reactome_matrix = reactome_df.pivot( + index="ModelID", columns="feature", values="latent_score" + ) + corum_matrix = corum_df.pivot( + index="ModelID", columns="feature", values="latent_score" + ) + drug_matrix = drug_df.pivot( + index="ModelID", columns="feature", values="latent_score" + ) + + # Join metadata back to each matrix + reactome_matrix = reactome_matrix.merge(reactome_meta, on="ModelID", how="left") + corum_matrix = corum_matrix.merge(corum_meta, on="ModelID", how="left") + drug_matrix = drug_matrix.merge(drug_meta, on="ModelID", how="left") + + return reactome_matrix, corum_matrix, drug_matrix + + +def single_load_data(): + + # Load dependency data + data_directory = pathlib.Path("../0.data-download/data").resolve() + dependency_file = pathlib.Path( + f"{data_directory}/CRISPRGeneEffect.parquet" + ).resolve() + gene_dict_file = pathlib.Path( + f"{data_directory}/CRISPR_gene_dictionary.parquet" + ).resolve() + dependency_df, gene_dict_df = load_model_data(dependency_file, gene_dict_file) + dependency_df = dependency_df.set_index("ModelID") + cancer_type_input_file = pathlib.Path("../0.data-download/data/Model.parquet") + cancer_type_df = pd.read_parquet(cancer_type_input_file) + combined_df = dependency_df.merge( + cancer_type_df[["ModelID", "OncotreePrimaryDisease"]], on="ModelID", how="left" + ) + return combined_df + + +def spider_load_data(): + # model_ids = ["ACH-000323", "ACH-002083", "ACH-002228"] + files = { + "Reactome Pathways": "../5.drug-dependency/results/all_reactome_results.parquet", + "CORUM Complexes": "../5.drug-dependency/results/all_corum_results.parquet", + "Drug Responses": "../5.drug-dependency/results/all_drug_results.parquet", + } + # Adjust these if your column names differ + feature_colnames = { + "Reactome Pathways": "reactome_pathway", + "CORUM Complexes": "CORUM_pathway", + "Drug Responses": "name", + } + score_col = "pathway_score" + + model_colors = { + "ACH-000323": "#00FFFF", # cyan + "ACH-002083": "#FF69B4", # pink + "ACH-002228": "#800080", # purple + } + + global_max = 0 + dfs = {} + for name, file in files.items(): + df = pd.read_parquet(file) + dfs[name] = df + if df[score_col].max() > global_max: + global_max = df[score_col].max() + + return dfs, global_max + + +def clean_label(x: str) -> str: + """ + Clean or override specific long labels before truncation. + """ + # Polymerase switching + if "Polymerase Switching" in x: + return "Polymerase Switching" + + # Negative MET regulation + if "Negative Regulation Of MET" in x or "Negative Regulation of MET" in x: + return "Negative MET Regulation" + + return truncate_label(x) + + +def truncate_label( + label: str, + max_chars_per_line: int = 22, + max_total_words: int = 4, + max_lines: int = 2, +) -> str: + """ + Truncate a label according to character and line limits. + """ + words = label.split() + short = " ".join(words[:max_total_words]) + + # Wrap + lines = textwrap.wrap(short, width=max_chars_per_line) + + # clamp to max lines + if len(lines) > max_lines: + lines = lines[:max_lines] + + wrapped = "\n".join(lines) + + # Determine if truncated + if len(words) > max_total_words or ( + len(lines) >= max_lines + and len(lines) < len(textwrap.wrap(short, width=max_chars_per_line)) + ): + wrapped += "..." + + return wrapped + + +def place_labels_polar(ax, angles, labels, radius: float) -> None: + """ + Place labels around a polar plot at a given radius. + """ + for angle, label in zip(angles[:-1], labels): + r = radius + + # left / right alignment + if 0 <= angle <= np.pi / 2 or 3 * np.pi / 2 <= angle <= 2 * np.pi: + ha = "left" + else: + ha = "right" + + ax.text( + angle, r, label, fontsize=9, color="black", ha=ha, va="center", wrap=True + ) + + return None + + +def generate_random_palette(num_colors, seed=12): + # Generate random colors with varied lightness and saturation + random.seed(seed) + + colors = [] + + for _ in range(num_colors): + h = random.random() # Random hue between 0 and 1 + l = random.uniform(0.2, 0.8) # Lightness between 0.3 and 0.9 for contrast + s = random.uniform(0.5, 1.0) # Saturation between 0.6 and 1.0 for vivid colors + color = colorsys.hls_to_rgb(h, l, s) # Convert HLS to RGB color + colors.append(color) + + return colors + + +def generate_model_color_map(model_ids, seed=12): + colors = generate_random_palette(len(model_ids), seed) + return {model_id: color for model_id, color in zip(model_ids, colors)} + + +def make_radar( + ax, + df: pd.DataFrame, + feature_col: str, + title: str, + global_max: float, + score_col: str = "pathway_score", + model_ids: list = ["ACH-000323", "ACH-002083", "ACH-002228"], + num_circles: int = 5, +) -> None: + """ + Draw a radar plot on an existing polar matplotlib axis. + """ + model_colors = generate_model_color_map(model_ids, seed=12) + + # Top 5 per model, union of all + top_by_model = ( + df.groupby("ModelID", group_keys=False) + .apply(lambda x: x.nlargest(5, score_col)) + .reset_index(drop=True) + ) + top_features = top_by_model[feature_col].drop_duplicates().tolist() + n_vars = len(top_features) + labels = [clean_label(x) for x in top_features] + + # Angles + angles = np.linspace(0, 2 * np.pi, n_vars, endpoint=False).tolist() + angles += [angles[0]] + + # Reference circles + circle_levels = np.linspace(0, global_max, num_circles + 1)[1:] + for r in circle_levels: + circle_vals = [r] * (n_vars + 1) + ax.plot( + angles, circle_vals, color="grey", linestyle="--", linewidth=1, zorder=0 + ) + # Plot each model + for mid in model_ids: + subset = df[df["ModelID"] == mid] + + merged = pd.DataFrame({feature_col: top_features}).merge( + subset[[feature_col, score_col]], on=feature_col, how="left" + ) + + values = merged[score_col].fillna(0).tolist() + values += [values[0]] + + ax.plot(angles, values, color=model_colors[mid], linewidth=3, label=mid) + ax.scatter( + angles, values, color=model_colors[mid], s=30, edgecolor="black", zorder=5 + ) + + # Axis styling + ax.set_ylim(0, global_max * 1.25) + ax.set_xticks([]) + ax.set_yticks([]) + ax.set_aspect("equal") + + # Labels + label_radius = global_max * 1.4 + place_labels_polar(ax, angles, labels, label_radius) + + # Title + ax.set_title(title, fontsize=18, pad=30, fontweight="bold", y=1) + + return None + + +def make_dropdown_pca_with_selection(df, title="PCA Interactive Plot"): + out = widgets.Output() # Create a fresh output for this plot! + + # Prepare PCA input + pca_input = df.drop( + columns=["OncotreePrimaryDisease", "source", "ModelID"], errors="ignore" + ).fillna(0) + pca = PCA(n_components=2, random_state=0) + embedding = pca.fit_transform(pca_input) + + # Add PCA coordinates to the dataframe + df["PCA1"] = embedding[:, 0] + df["PCA2"] = embedding[:, 1] + + # Prepare color map for each cancer type + cancer_types = df["OncotreePrimaryDisease"].unique() + color_map = ( + px.colors.qualitative.Plotly + + px.colors.qualitative.Light24 + + px.colors.qualitative.Dark24 + ) + highlight_color_map = { + cancer: color_map[i % len(color_map)] for i, cancer in enumerate(cancer_types) + } + + # Create one trace per cancer type + traces = [] + for cancer in cancer_types: + df_subset = df[df["OncotreePrimaryDisease"] == cancer] + trace = go.Scattergl( + x=df_subset["PCA1"], + y=df_subset["PCA2"], + mode="markers", + name=cancer, + marker=dict(size=7, color=highlight_color_map[cancer]), + text=[f"{cancer} | {model_id}" for model_id in df_subset["ModelID"]], + customdata=df_subset["ModelID"], # Attach ModelID to customdata + hoverinfo="text", + ) + traces.append(trace) + + # Dropdown buttons to highlight cancer types + dropdown_buttons = [] + for i, cancer in enumerate(cancer_types): + visibility = [True] * len(cancer_types) + colors = ["lightgrey"] * len(cancer_types) + colors[i] = highlight_color_map[cancer] + + button = dict( + method="update", + label=cancer, + args=[ + { + "visible": visibility, + "marker": [{"color": colors[j]} for j in range(len(cancer_types))], + }, + {"title": f"PCA Highlighted: {cancer}"}, + ], + ) + dropdown_buttons.append(button) + + # Default color button + default_colors = [highlight_color_map[cancer] for cancer in cancer_types] + + fig = go.Figure(data=traces) + + for i, trace in enumerate(fig.data): + trace.marker.color = default_colors[i] + + fig.update_layout( + title=title, + xaxis_title="PCA1", + yaxis_title="PCA2", + updatemenus=[ + { + "direction": "down", + "showactive": True, + "x": 1.15, + "xanchor": "left", + "y": 1.15, + "yanchor": "top", + } + ], + dragmode="lasso", # Ensure Lasso is enabled + width=1500, + height=800, + ) + + return fig, out # Return both the figure and the output widget for selection + + +def load_model_data(dependency_file, gene_dict_file): + """ + Load and preprocess gene dependency data and gene dictionary. + + Parameters: + - dependency_file (str): Path to the gene dependency data file. + - gene_dict_file (str): Path to the gene dictionary file. + + Returns: + - dependency_df (DataFrame): Preprocessed gene dependency data. + - gene_dict_df (DataFrame): Preprocessed gene dictionary. + """ + # Load gene dependency data + dependency_df = pd.read_parquet(dependency_file) + + print(dependency_df.shape) + dependency_df.head(3) + + # Load gene dictionary and filter by QC + gene_dict_df = ( + pd.read_parquet(gene_dict_file).query("qc_pass").reset_index(drop=True) + ) + gene_dict_df.entrez_id = gene_dict_df.entrez_id.astype(str) + + # Recode column names to entrez ids + entrez_genes = [ + x[1].strip(")").strip() + for x in dependency_df.iloc[:, 1:].columns.str.split("(") + ] + entrez_intersection = list( + set(gene_dict_df.entrez_id).intersection(set(entrez_genes)) + ) + + gene_dict_df = gene_dict_df.set_index("entrez_id").reindex(entrez_intersection) + + # Subset dependencies to the genes that passed QC + dependency_df.columns = ["ModelID"] + entrez_genes + dependency_df = dependency_df.loc[:, ["ModelID"] + gene_dict_df.index.tolist()] + dependency_df.columns = ["ModelID"] + gene_dict_df.symbol_id.tolist() + dependency_df = dependency_df.dropna(axis="columns") + + return dependency_df, gene_dict_df diff --git a/9.webapp/pyproject.toml b/9.webapp/pyproject.toml new file mode 100644 index 0000000..2cc26b7 --- /dev/null +++ b/9.webapp/pyproject.toml @@ -0,0 +1,24 @@ +[build-system] +requires = ["setuptools>=68", "wheel"] +build-backend = "setuptools.build_meta" + +[project] +name = "gene-dependency-webapp" +version = "0.1.0" +description = "Interactive Streamlit webapp for exploring gene dependency plots" +requires-python = ">=3.12" +dependencies = [ + "streamlit", + "plotly", + "pandas", + "numpy", + "scikit-learn", + "pyarrow", + "umap-learn", + "matplotlib>=3.10.9", + "ipykernel>=7.2.0", + "ipywidgets>=8.1.8", +] + +[tool.setuptools] +py-modules = ["app", "app_utils"] diff --git a/9.webapp/test_notebook.ipynb b/9.webapp/test_notebook.ipynb new file mode 100644 index 0000000..d525410 --- /dev/null +++ b/9.webapp/test_notebook.ipynb @@ -0,0 +1,87386 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "394ffda4", + "metadata": {}, + "source": [ + "## latent umaps" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "883f1d01", + "metadata": {}, + "outputs": [], + "source": [ + "import pathlib\n", + "import random\n", + "import sys\n", + "\n", + "import joblib\n", + "import numpy as np\n", + "import pandas as pd\n", + "import plotly.express as px\n", + "import plotly.graph_objects as go\n", + "from app_utils import generate_random_palette, load_model_data\n", + "from sklearn.decomposition import PCA\n", + "from sklearn.preprocessing import StandardScaler" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "65bb91f4", + "metadata": {}, + "outputs": [], + "source": [ + "cancer_type_input_file = pathlib.Path(\"../0.data-download/data/Model.parquet\")\n", + "cancer_type_df = pd.read_parquet(cancer_type_input_file)\n", + "\n", + "reactome_dims = pathlib.Path(\n", + " \"../5.drug-dependency/results/all_reactome_results.parquet\"\n", + ")\n", + "reactome_df = pd.read_parquet(reactome_dims)\n", + "\n", + "corum_dims = pathlib.Path(\"../5.drug-dependency/results/all_corum_results.parquet\")\n", + "corum_df = pd.read_parquet(corum_dims)\n", + "\n", + "drug_dims = pathlib.Path(\"../5.drug-dependency/results/all_drug_results.parquet\")\n", + "drug_df = pd.read_parquet(drug_dims)\n", + "# Step 2: Subset based on matching keys\n", + "subset_keys = [\"model\", \"latent_dim_total\", \"init\", \"z\"]\n", + "\n", + "# Replace latent identifiers with pathway\n", + "reactome_df[\"feature\"] = reactome_df[\"reactome_pathway\"]\n", + "reactome_df = reactome_df.drop(\n", + " columns=[\"model\", \"latent_dim_total\", \"init\", \"seed\", \"z\", \"reactome_pathway\"]\n", + ")\n", + "\n", + "corum_df[\"feature\"] = corum_df[\"reactome_pathway\"]\n", + "corum_df = corum_df.drop(\n", + " columns=[\"model\", \"latent_dim_total\", \"init\", \"seed\", \"z\", \"reactome_pathway\"]\n", + ")\n", + "\n", + "drug_df[\"feature\"] = drug_df[\"name\"]\n", + "drug_df = drug_df.drop(\n", + " columns=[\"model\", \"latent_dim_total\", \"init\", \"seed\", \"z\", \"name\"]\n", + ")\n", + "drug_df_sorted = drug_df.sort_values(\n", + " by=[\"OncotreePrimaryDisease\", \"ModelID\", \"feature\"], ascending=True\n", + ")\n", + "# Create a unique column name by combining feature and source\n", + "meta_cols = [\"ModelID\", \"OncotreePrimaryDisease\"]\n", + "reactome_meta = reactome_df[meta_cols].drop_duplicates()\n", + "corum_meta = corum_df[meta_cols].drop_duplicates()\n", + "drug_meta = drug_df[meta_cols].drop_duplicates()\n", + "\n", + "# Pivot to wide format\n", + "reactome_matrix = reactome_df.pivot(\n", + " index=\"ModelID\", columns=\"feature\", values=\"latent_score\"\n", + ")\n", + "corum_matrix = corum_df.pivot(index=\"ModelID\", columns=\"feature\", values=\"latent_score\")\n", + "drug_matrix = drug_df.pivot(index=\"ModelID\", columns=\"feature\", values=\"latent_score\")\n", + "\n", + "# Join metadata back to each matrix\n", + "reactome_matrix = reactome_matrix.merge(reactome_meta, on=\"ModelID\", how=\"left\")\n", + "corum_matrix = corum_matrix.merge(corum_meta, on=\"ModelID\", how=\"left\")\n", + "drug_matrix = drug_matrix.merge(drug_meta, on=\"ModelID\", how=\"left\")" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "a6783a5b", + "metadata": {}, + "outputs": [], + "source": [ + "import colorsys\n", + "import random\n", + "\n", + "\n", + "def generate_random_palette(num_colors, seed=12):\n", + " # Generate random colors with varied lightness and saturation\n", + " random.seed(seed)\n", + "\n", + " colors = []\n", + "\n", + " for _ in range(num_colors):\n", + " h = random.random() # Random hue between 0 and 1\n", + " l = random.uniform(0.2, 0.8) # Lightness between 0.3 and 0.9 for contrast\n", + " s = random.uniform(0.5, 1.0) # Saturation between 0.6 and 1.0 for vivid colors\n", + " color = colorsys.hls_to_rgb(h, l, s) # Convert HLS to RGB color\n", + " colors.append(color)\n", + "\n", + " return colors" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "a6c8bafb", + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'gene_cols' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[31m---------------------------------------------------------------------------\u001b[39m", + "\u001b[31mNameError\u001b[39m Traceback (most recent call last)", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[8]\u001b[39m\u001b[32m, line 7\u001b[39m\n\u001b[32m 3\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m sklearn.decomposition \u001b[38;5;28;01mimport\u001b[39;00m PCA\n\u001b[32m 4\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m sklearn.preprocessing \u001b[38;5;28;01mimport\u001b[39;00m StandardScaler\n\u001b[32m 5\u001b[39m \n\u001b[32m 6\u001b[39m \u001b[38;5;66;03m# Prepare PCA input (excluding non-numeric columns)\u001b[39;00m\n\u001b[32m----> \u001b[39m\u001b[32m7\u001b[39m pca_input = combined_df[gene_cols].apply(pd.to_numeric, errors=\u001b[33m\"coerce\"\u001b[39m)\n\u001b[32m 8\u001b[39m pca = PCA(n_components=\u001b[32m2\u001b[39m, random_state=\u001b[32m0\u001b[39m)\n\u001b[32m 9\u001b[39m pca_embedding = pca.fit_transform(pca_input)\n\u001b[32m 10\u001b[39m \n", + "\u001b[31mNameError\u001b[39m: name 'gene_cols' is not defined" + ] + } + ], + "source": [ + "import plotly.express as px\n", + "import plotly.graph_objects as go\n", + "from sklearn.decomposition import PCA\n", + "from sklearn.preprocessing import StandardScaler\n", + "\n", + "# Prepare PCA input (excluding non-numeric columns)\n", + "pca_input = combined_df[gene_cols].apply(pd.to_numeric, errors=\"coerce\")\n", + "pca = PCA(n_components=2, random_state=0)\n", + "pca_embedding = pca.fit_transform(pca_input)\n", + "\n", + "# Add PCA components to the dataframe\n", + "combined_df[\"PCA1\"] = pca_embedding[:, 0]\n", + "combined_df[\"PCA2\"] = pca_embedding[:, 1]\n", + "\n", + "# Prepare color map for each cancer type\n", + "cancer_types = combined_df[\"OncotreePrimaryDisease\"].unique()\n", + "color_map = (\n", + " px.colors.qualitative.Plotly\n", + " + px.colors.qualitative.Light24\n", + " + px.colors.qualitative.Dark24\n", + ")\n", + "highlight_color_map = {\n", + " cancer: color_map[i % len(color_map)] for i, cancer in enumerate(cancer_types)\n", + "}\n", + "\n", + "# Create one trace per cancer type\n", + "traces = []\n", + "for cancer in cancer_types:\n", + " df_subset = combined_df[combined_df[\"OncotreePrimaryDisease\"] == cancer]\n", + " trace = go.Scatter(\n", + " x=df_subset[\"PCA1\"],\n", + " y=df_subset[\"PCA2\"],\n", + " mode=\"markers\",\n", + " name=cancer,\n", + " marker=dict(size=7),\n", + " text=[f\"{cancer} | {model_id}\" for model_id in df_subset[\"ModelID\"]],\n", + " hoverinfo=\"text\",\n", + " )\n", + " traces.append(trace)\n", + "\n", + "# Create dropdown buttons\n", + "dropdown_buttons = []\n", + "\n", + "for i, cancer in enumerate(cancer_types):\n", + " # Make all grey except the selected one\n", + " visibility = [True] * len(cancer_types)\n", + " colors = [\"lightgrey\"] * len(cancer_types)\n", + " colors[i] = highlight_color_map[cancer]\n", + "\n", + " button = dict(\n", + " method=\"update\",\n", + " label=cancer,\n", + " args=[\n", + " {\n", + " \"visible\": visibility,\n", + " \"marker\": [{\"color\": colors[j]} for j in range(len(cancer_types))],\n", + " },\n", + " {\"title\": f\"PCA Highlighted: {cancer}\"},\n", + " ],\n", + " )\n", + " dropdown_buttons.append(button)\n", + "\n", + "# Add a button to show all with normal colors\n", + "default_colors = [highlight_color_map[cancer] for cancer in cancer_types]\n", + "dropdown_buttons.insert(\n", + " 0,\n", + " dict(\n", + " method=\"update\",\n", + " label=\"Show All\",\n", + " args=[\n", + " {\n", + " \"visible\": [True] * len(cancer_types),\n", + " \"marker\": [\n", + " {\"color\": default_colors[j]} for j in range(len(cancer_types))\n", + " ],\n", + " },\n", + " {\"title\": \"PCA of DepMap Single Gene Data\"},\n", + " ],\n", + " ),\n", + ")\n", + "\n", + "# Create the figure\n", + "fig = go.Figure(data=traces)\n", + "\n", + "# Set default colors\n", + "for i, trace in enumerate(fig.data):\n", + " trace.marker.color = default_colors[i]\n", + "\n", + "fig.update_layout(\n", + " title=\"PCA of DepMap Single Gene Data\",\n", + " xaxis_title=\"PCA1\",\n", + " yaxis_title=\"PCA2\",\n", + " updatemenus=[\n", + " {\n", + " \"buttons\": dropdown_buttons,\n", + " \"direction\": \"down\",\n", + " \"showactive\": True,\n", + " \"x\": 1.15,\n", + " \"xanchor\": \"left\",\n", + " \"y\": 1.15,\n", + " \"yanchor\": \"top\",\n", + " }\n", + " ],\n", + " width=1500,\n", + " height=800,\n", + ")\n", + "\n", + "fig.show()\n", + "fig.write_html(\"achilles_pca.html\")" + ] + }, + { + "cell_type": "markdown", + "id": "5608470d", + "metadata": {}, + "source": [ + "## single-depedency-umaps" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e4f4c4b8", + "metadata": {}, + "outputs": [], + "source": [ + "import colorsys\n", + "import pathlib\n", + "import random\n", + "\n", + "import ipywidgets as widgets\n", + "import pandas as pd\n", + "import plotly.express as px\n", + "import plotly.graph_objs as go\n", + "from sklearn.decomposition import PCA" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "61b1ea35", + "metadata": {}, + "outputs": [], + "source": [ + "cancer_type_input_file = pathlib.Path(\"../0.data-download/data/Model.parquet\")\n", + "cancer_type_df = pd.read_parquet(cancer_type_input_file)\n", + "\n", + "reactome_dims = pathlib.Path(\n", + " \"../5.drug-dependency/results/all_reactome_results.parquet\"\n", + ")\n", + "reactome_df = pd.read_parquet(reactome_dims)\n", + "\n", + "corum_dims = pathlib.Path(\"../5.drug-dependency/results/all_corum_results.parquet\")\n", + "corum_df = pd.read_parquet(corum_dims)\n", + "\n", + "drug_dims = pathlib.Path(\"../5.drug-dependency/results/all_drug_results.parquet\")\n", + "drug_df = pd.read_parquet(drug_dims)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e4d005ac", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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    ModelIDmodellatent_dim_totalinitseedOncotreePrimaryDiseasezlatent_scorereactome_pathwaynes_scorepathway_score
    0ACH-000001betatcvae1641154917792Ovarian Epithelial Tumor10.306144Formation Of Incision Complex In GG-NER R-HSA-...3.2473450.306144
    1ACH-000001betatcvae250501796030Ovarian Epithelial Tumor10.657242Citric Acid (TCA) Cycle And Respiratory Electr...inf0.657242
    2ACH-000001betatcvae9001590696690Ovarian Epithelial Tumor10.455570Polymerase Switching On C-strand Of Telomere R...2.9176800.455570
    3ACH-000001betavae534066919116Ovarian Epithelial Tumor10.000000RHOC GTPase Cycle R-HSA-90131063.1494550.000000
    4ACH-000001betavae1021507182516Ovarian Epithelial Tumor10.159076Nephrin Family Interactions R-HSA-3737532.5826870.159076
    \n", + "
    " + ], + "text/plain": [ + " ModelID model latent_dim_total init seed \\\n", + "0 ACH-000001 betatcvae 16 4 1154917792 \n", + "1 ACH-000001 betatcvae 25 0 501796030 \n", + "2 ACH-000001 betatcvae 90 0 1590696690 \n", + "3 ACH-000001 betavae 5 3 4066919116 \n", + "4 ACH-000001 betavae 10 2 1507182516 \n", + "\n", + " OncotreePrimaryDisease z latent_score \\\n", + "0 Ovarian Epithelial Tumor 1 0.306144 \n", + "1 Ovarian Epithelial Tumor 1 0.657242 \n", + "2 Ovarian Epithelial Tumor 1 0.455570 \n", + "3 Ovarian Epithelial Tumor 1 0.000000 \n", + "4 Ovarian Epithelial Tumor 1 0.159076 \n", + "\n", + " reactome_pathway nes_score pathway_score \n", + "0 Formation Of Incision Complex In GG-NER R-HSA-... 3.247345 0.306144 \n", + "1 Citric Acid (TCA) Cycle And Respiratory Electr... inf 0.657242 \n", + "2 Polymerase Switching On C-strand Of Telomere R... 2.917680 0.455570 \n", + "3 RHOC GTPase Cycle R-HSA-9013106 3.149455 0.000000 \n", + "4 Nephrin Family Interactions R-HSA-373753 2.582687 0.159076 " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "reactome_df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fcc27123", + "metadata": {}, + "outputs": [], + "source": [ + "# Step 2: Subset based on matching keys\n", + "subset_keys = [\"model\", \"latent_dim_total\", \"init\", \"z\"]\n", + "\n", + "# Replace latent identifiers with pathway\n", + "reactome_df[\"feature\"] = reactome_df[\"reactome_pathway\"]\n", + "reactome_df = reactome_df.drop(\n", + " columns=[\"model\", \"latent_dim_total\", \"init\", \"seed\", \"z\", \"reactome_pathway\"]\n", + ")\n", + "\n", + "corum_df[\"feature\"] = corum_df[\"reactome_pathway\"]\n", + "corum_df = corum_df.drop(\n", + " columns=[\"model\", \"latent_dim_total\", \"init\", \"seed\", \"z\", \"reactome_pathway\"]\n", + ")\n", + "\n", + "drug_df[\"feature\"] = drug_df[\"name\"]\n", + "drug_df = drug_df.drop(\n", + " columns=[\"model\", \"latent_dim_total\", \"init\", \"seed\", \"z\", \"name\"]\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b65e2c71", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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    ModelIDOncotreePrimaryDiseaselatent_scorepearson_correlationpathway_scorefeature
    597ACH-000004Acute Myeloid Leukemia0.543216-0.2639620.54321610-deacetylbaccatin
    716ACH-000004Acute Myeloid Leukemia0.740212-0.2529450.7402122,3-DCPE
    457ACH-000004Acute Myeloid Leukemia0.832806-0.2753880.8328063-deazaneplanocin-A
    678ACH-000004Acute Myeloid Leukemia0.641957-0.3206670.6419579-aminoacridine
    444ACH-000004Acute Myeloid Leukemia0.546763-0.2626310.546763ACY-1215
    \n", + "
    " + ], + "text/plain": [ + " ModelID OncotreePrimaryDisease latent_score pearson_correlation \\\n", + "597 ACH-000004 Acute Myeloid Leukemia 0.543216 -0.263962 \n", + "716 ACH-000004 Acute Myeloid Leukemia 0.740212 -0.252945 \n", + "457 ACH-000004 Acute Myeloid Leukemia 0.832806 -0.275388 \n", + "678 ACH-000004 Acute Myeloid Leukemia 0.641957 -0.320667 \n", + "444 ACH-000004 Acute Myeloid Leukemia 0.546763 -0.262631 \n", + "\n", + " pathway_score feature \n", + "597 0.543216 10-deacetylbaccatin \n", + "716 0.740212 2,3-DCPE \n", + "457 0.832806 3-deazaneplanocin-A \n", + "678 0.641957 9-aminoacridine \n", + "444 0.546763 ACY-1215 " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "drug_df_sorted = drug_df.sort_values(\n", + " by=[\"OncotreePrimaryDisease\", \"ModelID\", \"feature\"], ascending=True\n", + ")\n", + "drug_df_sorted.head()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6867f3ee", + "metadata": {}, + "outputs": [], + "source": [ + "# Create a unique column name by combining feature and source\n", + "meta_cols = [\"ModelID\", \"OncotreePrimaryDisease\"]\n", + "reactome_meta = reactome_df[meta_cols].drop_duplicates()\n", + "corum_meta = corum_df[meta_cols].drop_duplicates()\n", + "drug_meta = drug_df[meta_cols].drop_duplicates()\n", + "\n", + "# Pivot to wide format\n", + "reactome_matrix = reactome_df.pivot(\n", + " index=\"ModelID\", columns=\"feature\", values=\"latent_score\"\n", + ")\n", + "corum_matrix = corum_df.pivot(index=\"ModelID\", columns=\"feature\", values=\"latent_score\")\n", + "drug_matrix = drug_df.pivot(index=\"ModelID\", columns=\"feature\", values=\"latent_score\")\n", + "\n", + "# Join metadata back to each matrix\n", + "reactome_matrix = reactome_matrix.merge(reactome_meta, on=\"ModelID\", how=\"left\")\n", + "corum_matrix = corum_matrix.merge(corum_meta, on=\"ModelID\", how=\"left\")\n", + "drug_matrix = drug_matrix.merge(drug_meta, on=\"ModelID\", how=\"left\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "492bc932", + "metadata": {}, + "outputs": [], + "source": [ + "def generate_random_palette(num_colors, seed=12):\n", + " # Generate random colors with varied lightness and saturation\n", + " random.seed(seed)\n", + "\n", + " colors = []\n", + "\n", + " for _ in range(num_colors):\n", + " h = random.random() # Random hue between 0 and 1\n", + " l = random.uniform(0.2, 0.8) # Lightness between 0.3 and 0.9 for contrast\n", + " s = random.uniform(0.5, 1.0) # Saturation between 0.6 and 1.0 for vivid colors\n", + " color = colorsys.hls_to_rgb(h, l, s) # Convert HLS to RGB color\n", + " colors.append(color)\n", + "\n", + " return colors" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5743bc28", + "metadata": {}, + "outputs": [], + "source": [ + "def make_dropdown_pca_with_selection(df, title=\"PCA Interactive Plot\"):\n", + " out = widgets.Output() # Create a fresh output for this plot!\n", + "\n", + " # Prepare PCA input\n", + " pca_input = df.drop(\n", + " columns=[\"OncotreePrimaryDisease\", \"source\", \"ModelID\"], errors=\"ignore\"\n", + " ).fillna(0)\n", + " pca = PCA(n_components=2, random_state=0)\n", + " embedding = pca.fit_transform(pca_input)\n", + "\n", + " # Add PCA coordinates to the dataframe\n", + " df[\"PCA1\"] = embedding[:, 0]\n", + " df[\"PCA2\"] = embedding[:, 1]\n", + "\n", + " # Prepare color map for each cancer type\n", + " cancer_types = df[\"OncotreePrimaryDisease\"].unique()\n", + " color_map = (\n", + " px.colors.qualitative.Plotly\n", + " + px.colors.qualitative.Light24\n", + " + px.colors.qualitative.Dark24\n", + " )\n", + " highlight_color_map = {\n", + " cancer: color_map[i % len(color_map)] for i, cancer in enumerate(cancer_types)\n", + " }\n", + "\n", + " # Create one trace per cancer type\n", + " traces = []\n", + " for cancer in cancer_types:\n", + " df_subset = df[df[\"OncotreePrimaryDisease\"] == cancer]\n", + " trace = go.Scattergl(\n", + " x=df_subset[\"PCA1\"],\n", + " y=df_subset[\"PCA2\"],\n", + " mode=\"markers\",\n", + " name=cancer,\n", + " marker=dict(size=7, color=highlight_color_map[cancer]),\n", + " text=[f\"{cancer} | {model_id}\" for model_id in df_subset[\"ModelID\"]],\n", + " customdata=df_subset[\"ModelID\"], # Attach ModelID to customdata\n", + " hoverinfo=\"text\",\n", + " )\n", + " traces.append(trace)\n", + "\n", + " # Dropdown buttons to highlight cancer types\n", + " dropdown_buttons = []\n", + " for i, cancer in enumerate(cancer_types):\n", + " visibility = [True] * len(cancer_types)\n", + " colors = [\"lightgrey\"] * len(cancer_types)\n", + " colors[i] = highlight_color_map[cancer]\n", + "\n", + " button = dict(\n", + " method=\"update\",\n", + " label=cancer,\n", + " args=[\n", + " {\n", + " \"visible\": visibility,\n", + " \"marker\": [{\"color\": colors[j]} for j in range(len(cancer_types))],\n", + " },\n", + " {\"title\": f\"PCA Highlighted: {cancer}\"},\n", + " ],\n", + " )\n", + " dropdown_buttons.append(button)\n", + "\n", + " # Default color button\n", + " default_colors = [highlight_color_map[cancer] for cancer in cancer_types]\n", + " dropdown_buttons.insert(\n", + " 0,\n", + " dict(\n", + " method=\"update\",\n", + " label=\"Show All\",\n", + " args=[\n", + " {\n", + " \"visible\": [True] * len(cancer_types),\n", + " \"marker\": [\n", + " {\"color\": default_colors[j]} for j in range(len(cancer_types))\n", + " ],\n", + " },\n", + " {\"title\": title},\n", + " ],\n", + " ),\n", + " )\n", + "\n", + " fig = go.Figure(data=traces)\n", + "\n", + " for i, trace in enumerate(fig.data):\n", + " trace.marker.color = default_colors[i]\n", + "\n", + " fig.update_layout(\n", + " title=title,\n", + " xaxis_title=\"PCA1\",\n", + " yaxis_title=\"PCA2\",\n", + " updatemenus=[\n", + " {\n", + " \"buttons\": dropdown_buttons,\n", + " \"direction\": \"down\",\n", + " \"showactive\": True,\n", + " \"x\": 1.15,\n", + " \"xanchor\": \"left\",\n", + " \"y\": 1.15,\n", + " \"yanchor\": \"top\",\n", + " }\n", + " ],\n", + " dragmode=\"lasso\", # Ensure Lasso is enabled\n", + " width=1500,\n", + " height=800,\n", + " )\n", + "\n", + " return fig, out # Return both the figure and the output widget for selection" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "06be719b", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.plotly.v1+json": { + "config": { + "plotlyServerURL": "https://plot.ly" + }, + "data": [ + { + "customdata": [ + "ACH-000001", + "ACH-000013", + "ACH-000048", + "ACH-000103", + "ACH-000116", + "ACH-000123", + "ACH-000132", + "ACH-000237", + "ACH-000256", + "ACH-000278", + "ACH-000280", + "ACH-000291", + "ACH-000308", + "ACH-000324", + "ACH-000430", + "ACH-000460", + "ACH-000520", + "ACH-000524", + "ACH-000527", + "ACH-000542", + "ACH-000584", + "ACH-000608", + "ACH-000646", + "ACH-000657", + "ACH-000663", + "ACH-000688", + "ACH-000696", + "ACH-000701", + "ACH-000704", + "ACH-000713", + "ACH-000719", 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Epithelial Tumor | ACH-000278", + "Ovarian Epithelial Tumor | ACH-000280", + "Ovarian Epithelial Tumor | ACH-000291", + "Ovarian Epithelial Tumor | ACH-000308", + "Ovarian Epithelial Tumor | ACH-000324", + "Ovarian Epithelial Tumor | ACH-000430", + "Ovarian Epithelial Tumor | ACH-000460", + "Ovarian Epithelial Tumor | ACH-000520", + "Ovarian Epithelial Tumor | ACH-000524", + "Ovarian Epithelial Tumor | ACH-000527", + "Ovarian Epithelial Tumor | ACH-000542", + "Ovarian Epithelial Tumor | ACH-000584", + "Ovarian Epithelial Tumor | ACH-000608", + "Ovarian Epithelial Tumor | ACH-000646", + "Ovarian Epithelial Tumor | ACH-000657", + "Ovarian Epithelial Tumor | ACH-000663", + "Ovarian Epithelial Tumor | ACH-000688", + "Ovarian Epithelial Tumor | ACH-000696", + "Ovarian Epithelial Tumor | ACH-000701", + "Ovarian Epithelial Tumor | ACH-000704", + "Ovarian Epithelial Tumor | ACH-000713", + "Ovarian Epithelial Tumor | ACH-000719", + "Ovarian Epithelial Tumor | ACH-000796", + "Ovarian Epithelial Tumor | ACH-000811", + "Ovarian Epithelial Tumor | ACH-000885", + "Ovarian Epithelial Tumor | ACH-000906", + "Ovarian Epithelial Tumor | ACH-000936", + "Ovarian Epithelial Tumor | ACH-000947", + "Ovarian Epithelial Tumor | ACH-000962", + "Ovarian Epithelial Tumor | ACH-000966", + "Ovarian Epithelial Tumor | ACH-001048", + "Ovarian Epithelial Tumor | ACH-001063", + "Ovarian Epithelial Tumor | ACH-001145", + "Ovarian Epithelial Tumor | ACH-001151", + "Ovarian Epithelial Tumor | ACH-001278", + "Ovarian Epithelial Tumor | ACH-001279", + "Ovarian Epithelial Tumor | ACH-001340", + "Ovarian Epithelial Tumor | ACH-001370", + "Ovarian Epithelial Tumor | ACH-001403", + "Ovarian Epithelial Tumor | ACH-001418", + "Ovarian Epithelial Tumor | ACH-001628", + "Ovarian Epithelial Tumor | ACH-001630", + "Ovarian Epithelial Tumor | ACH-001632", + "Ovarian Epithelial Tumor | ACH-001719", + "Ovarian Epithelial Tumor | ACH-001991", + "Ovarian Epithelial Tumor | ACH-002140", + "Ovarian Epithelial Tumor | ACH-002181", + "Ovarian Epithelial Tumor | ACH-002183", + "Ovarian Epithelial Tumor | ACH-002486", + "Ovarian Epithelial Tumor | ACH-002524" + ], + "type": "scattergl", + "x": { + "bdata": "e4r5vXb+GEB3ZKhALgRQvzJvbj+zPJhAjuwfPx0F7r/s1PLAO+TywArKyD9QREE/sscBwMD76j9xNJdAA/IrQO14272HxvLAujMCQKPC8sDw4wNAr9TywI2/H8AMsvLAswDFPnB1pMAiym5AzegdwIiS0D8zZOU+ic/QvkXWZL9RyVPAhGu0QB/Tk0Beduw/74jkQNR3MUCgV+Y/osfywEW/8sDWK0VAzNcXP0e68sDsgZRA/7fywCK+8sAozPLAgK+iP1y98sDew/LAgtrywAni8sDkMKpAqLnywO/O8sAm6PLATQBxQMayjj8=", + "dtype": "f4" + }, + "y": { + "bdata": "up2uvu/orT/bEiK+/2xov8Jb2T8iOVm/OmQPQMi4l0D42aq/Mcuqv5bRO0BrxbA/dRoevryEBEDZ6Rg/b/3WvrOXCUAEdau/7DXjP/k+q7+V/Ba/wHSrv3Pdlj1Qfau/PiokQF6QM0Aafg9AafNoP09yCD+ACR++jcqlP4wGkr6AcEBA0kouP5xabD/5aj+/Y+rsvwkpMz+tetU+H/Sqvz0Jq78g3nw//1PCPxmDq7/vg308a0Krv0Bnq7/5Aau/IhtOv/tfq78i0qq/yraqv6Z5qr/wRQvAUZ2rv4Djqr9FmKq/kqGwP3VBeD4=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000004", + "ACH-000005", + "ACH-000045", + "ACH-000113", + "ACH-000146", + 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| ACH-000387", + "Acute Myeloid Leukemia | ACH-000406", + "Acute Myeloid Leukemia | ACH-000498", + "Acute Myeloid Leukemia | ACH-000557", + "Acute Myeloid Leukemia | ACH-000602", + "Acute Myeloid Leukemia | ACH-000770", + "Acute Myeloid Leukemia | ACH-001036", + "Acute Myeloid Leukemia | ACH-001129", + "Acute Myeloid Leukemia | ACH-001574", + "Acute Myeloid Leukemia | ACH-001577", + "Acute Myeloid Leukemia | ACH-001613", + "Acute Myeloid Leukemia | ACH-001618", + "Acute Myeloid Leukemia | ACH-001647", + "Acute Myeloid Leukemia | ACH-001656" + ], + "type": "scattergl", + "x": { + "bdata": "CJ/fP16jlT6TIrpAinkNQfzmdD6qGBi+C4skQLKkgT+lXzK/dFkmQJUt60Dc5rlAK434P0vczUCLIpk+4IwBwECUFEDt+pNAGDlGQOkUvb37sMRAtpkHQIODlUC0oEJAVFKOQL2JhEA=", + "dtype": "f4" + }, + "y": { + "bdata": "PxwGwL8xqL9U0oXAV4GbwBxNPMDLXgrAdhBnPvxjjb/64PG/C68qwACzkMBSwYXA0JwNwOuhesCgd/Y84oBMwOLsN8B/ZHLAV731vwxmR7/VaHfAJSQDwDgYGsA/xQjAlARnwAezc8A=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000007", + 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"color": "#00CC96", + "size": 7 + }, + "mode": "markers", + "name": "Colorectal Adenocarcinoma", + "text": [ + "Colorectal Adenocarcinoma | ACH-000007", + "Colorectal Adenocarcinoma | ACH-000009", + "Colorectal Adenocarcinoma | ACH-000202", + "Colorectal Adenocarcinoma | ACH-000249", + "Colorectal Adenocarcinoma | ACH-000252", + "Colorectal Adenocarcinoma | ACH-000253", + "Colorectal Adenocarcinoma | ACH-000286", + "Colorectal Adenocarcinoma | ACH-000296", + "Colorectal Adenocarcinoma | ACH-000350", + "Colorectal Adenocarcinoma | ACH-000381", + "Colorectal Adenocarcinoma | ACH-000403", + "Colorectal Adenocarcinoma | ACH-000421", + "Colorectal Adenocarcinoma | ACH-000467", + "Colorectal Adenocarcinoma | ACH-000470", + "Colorectal Adenocarcinoma | ACH-000489", + "Colorectal Adenocarcinoma | ACH-000491", + "Colorectal Adenocarcinoma | ACH-000501", + "Colorectal Adenocarcinoma | ACH-000532", + "Colorectal Adenocarcinoma | ACH-000552", + "Colorectal Adenocarcinoma | ACH-000565", + "Colorectal Adenocarcinoma | ACH-000651", + "Colorectal Adenocarcinoma | ACH-000683", + "Colorectal Adenocarcinoma | ACH-000722", + "Colorectal Adenocarcinoma | ACH-000798", + "Colorectal Adenocarcinoma | ACH-000820", + "Colorectal Adenocarcinoma | ACH-000926", + "Colorectal Adenocarcinoma | ACH-000935", + "Colorectal Adenocarcinoma | ACH-000943", + "Colorectal Adenocarcinoma | ACH-000950", + "Colorectal Adenocarcinoma | ACH-000957", + "Colorectal Adenocarcinoma | ACH-000958", + "Colorectal Adenocarcinoma | ACH-000959", + "Colorectal Adenocarcinoma | ACH-000963", + "Colorectal Adenocarcinoma | ACH-000969", + "Colorectal Adenocarcinoma | ACH-000970", + "Colorectal Adenocarcinoma | ACH-000971", + "Colorectal Adenocarcinoma | ACH-000985", + "Colorectal Adenocarcinoma | ACH-000986", + "Colorectal Adenocarcinoma | ACH-000991", + "Colorectal Adenocarcinoma | ACH-000997", + "Colorectal Adenocarcinoma | ACH-001039", + "Colorectal Adenocarcinoma | ACH-001061", + "Colorectal Adenocarcinoma | ACH-001081", + "Colorectal Adenocarcinoma | ACH-001345", + "Colorectal Adenocarcinoma | ACH-001399", + "Colorectal Adenocarcinoma | ACH-001454", + "Colorectal Adenocarcinoma | ACH-001458", + "Colorectal Adenocarcinoma | ACH-001459", + "Colorectal Adenocarcinoma | ACH-001460", + "Colorectal Adenocarcinoma | ACH-001461", + "Colorectal Adenocarcinoma | ACH-001786", + "Colorectal Adenocarcinoma | ACH-002024", + "Colorectal Adenocarcinoma | ACH-002025", + "Colorectal Adenocarcinoma | ACH-002233", + "Colorectal Adenocarcinoma | ACH-002535", + "Colorectal Adenocarcinoma | ACH-002654", + "Colorectal Adenocarcinoma | ACH-002659", + "Colorectal Adenocarcinoma | ACH-002660", + "Colorectal Adenocarcinoma | ACH-002662", + "Colorectal Adenocarcinoma | ACH-002664", + "Colorectal Adenocarcinoma | ACH-002669" + ], + "type": "scattergl", + "x": { + "bdata": 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"ACH-000741", + "ACH-000753", + "ACH-000802", + "ACH-000834", + "ACH-000862", + "ACH-000896", + "ACH-000905", + "ACH-001183", + "ACH-001407", + "ACH-001409", + "ACH-001412", + "ACH-001413", + "ACH-001414", + "ACH-001415", + "ACH-001416" + ], + "hoverinfo": "text", + "marker": { + "color": "#AB63FA", + "size": 7 + }, + "mode": "markers", + "name": "Bladder Urothelial Carcinoma", + "text": [ + "Bladder Urothelial Carcinoma | ACH-000011", + "Bladder Urothelial Carcinoma | ACH-000018", + "Bladder Urothelial Carcinoma | ACH-000026", + "Bladder Urothelial Carcinoma | ACH-000127", + "Bladder Urothelial Carcinoma | ACH-000142", + "Bladder Urothelial Carcinoma | ACH-000242", + "Bladder Urothelial Carcinoma | ACH-000396", + "Bladder Urothelial Carcinoma | ACH-000473", + "Bladder Urothelial Carcinoma | ACH-000486", + "Bladder Urothelial Carcinoma | ACH-000522", + "Bladder Urothelial Carcinoma | ACH-000545", + "Bladder Urothelial Carcinoma | ACH-000547", + "Bladder Urothelial Carcinoma | ACH-000593", + "Bladder Urothelial Carcinoma | ACH-000720", + "Bladder Urothelial Carcinoma | ACH-000724", + "Bladder Urothelial Carcinoma | ACH-000741", + "Bladder Urothelial Carcinoma | ACH-000753", + "Bladder Urothelial Carcinoma | ACH-000802", + "Bladder Urothelial Carcinoma | ACH-000834", + "Bladder Urothelial Carcinoma | ACH-000862", + "Bladder Urothelial Carcinoma | ACH-000896", + "Bladder Urothelial Carcinoma | ACH-000905", + "Bladder Urothelial Carcinoma | ACH-001183", + "Bladder Urothelial Carcinoma | ACH-001407", + "Bladder Urothelial Carcinoma | ACH-001409", + "Bladder Urothelial Carcinoma | ACH-001412", + "Bladder Urothelial Carcinoma | ACH-001413", + "Bladder Urothelial Carcinoma | ACH-001414", + "Bladder Urothelial Carcinoma | ACH-001415", + "Bladder Urothelial Carcinoma | ACH-001416" + ], + "type": "scattergl", + "x": { + "bdata": 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"ACH-000585", + "ACH-000587", + "ACH-000589", + "ACH-000596", + "ACH-000627", + "ACH-000638", + "ACH-000662", + "ACH-000665", + "ACH-000666", + "ACH-000667", + "ACH-000672", + "ACH-000677", + "ACH-000681", + "ACH-000700", + "ACH-000706", + "ACH-000718", + "ACH-000747", + "ACH-000757", + "ACH-000766", + "ACH-000769", + "ACH-000774", + "ACH-000781", + "ACH-000785", + "ACH-000787", + "ACH-000791", + "ACH-000826", + "ACH-000837", + "ACH-000840", + "ACH-000841", + "ACH-000843", + "ACH-000845", + "ACH-000851", + "ACH-000853", + "ACH-000858", + "ACH-000860", + "ACH-000861", + "ACH-000867", + "ACH-000869", + "ACH-000872", + "ACH-000878", + "ACH-000886", + "ACH-000888", + "ACH-000894", + "ACH-000900", + "ACH-000901", + "ACH-000916", + "ACH-000921", + "ACH-000924", + "ACH-000929", + "ACH-000945", + "ACH-000975", + "ACH-000980", + "ACH-001075", + "ACH-001137", + "ACH-001233", + "ACH-002035", + "ACH-002156", + "ACH-002522", + "ACH-002526", + "ACH-002531", + "ACH-002650", + "ACH-003012" + ], + "hoverinfo": "text", + "marker": { + "color": "#FFA15A", + "size": 7 + }, + "mode": "markers", + "name": "Non-Small Cell Lung Cancer", + "text": [ + "Non-Small Cell Lung Cancer | ACH-000012", + "Non-Small Cell Lung Cancer | ACH-000015", + "Non-Small Cell Lung Cancer | ACH-000021", + "Non-Small Cell Lung Cancer | ACH-000029", + "Non-Small Cell Lung Cancer | ACH-000030", + "Non-Small Cell Lung Cancer | ACH-000035", + "Non-Small Cell Lung Cancer | ACH-000143", + "Non-Small Cell Lung Cancer | ACH-000161", + "Non-Small Cell Lung Cancer | ACH-000176", + "Non-Small Cell Lung Cancer | ACH-000251", + "Non-Small Cell Lung Cancer | ACH-000261", + "Non-Small Cell Lung Cancer | ACH-000264", + "Non-Small Cell Lung Cancer | ACH-000311", + "Non-Small Cell Lung Cancer | ACH-000337", + "Non-Small Cell Lung Cancer | ACH-000339", + "Non-Small Cell Lung Cancer | ACH-000343", + "Non-Small Cell Lung Cancer | ACH-000378", + "Non-Small Cell Lung Cancer | ACH-000390", + "Non-Small Cell Lung Cancer | ACH-000395", + "Non-Small Cell Lung Cancer | ACH-000414", + "Non-Small Cell Lung Cancer | ACH-000416", + "Non-Small Cell Lung Cancer | ACH-000434", + "Non-Small Cell Lung Cancer | ACH-000438", + "Non-Small Cell Lung Cancer | ACH-000442", + "Non-Small Cell Lung Cancer | ACH-000444", + "Non-Small Cell Lung Cancer | ACH-000448", + "Non-Small Cell Lung Cancer | ACH-000454", + "Non-Small Cell Lung Cancer | ACH-000463", + "Non-Small Cell Lung Cancer | ACH-000481", + "Non-Small Cell Lung Cancer | ACH-000496", + "Non-Small Cell Lung Cancer | ACH-000510", + "Non-Small Cell Lung Cancer | ACH-000511", + "Non-Small Cell Lung Cancer | ACH-000521", + "Non-Small Cell Lung Cancer | ACH-000528", + "Non-Small Cell Lung Cancer | ACH-000562", + "Non-Small Cell Lung Cancer | ACH-000563", + "Non-Small Cell Lung Cancer | ACH-000585", + "Non-Small Cell Lung Cancer | ACH-000587", + "Non-Small Cell Lung Cancer | ACH-000589", + "Non-Small Cell Lung Cancer | ACH-000596", + "Non-Small Cell Lung Cancer | ACH-000627", + "Non-Small Cell Lung Cancer | ACH-000638", + "Non-Small Cell Lung Cancer | ACH-000662", + "Non-Small Cell Lung Cancer | ACH-000665", + "Non-Small Cell Lung Cancer | ACH-000666", + "Non-Small Cell Lung Cancer | ACH-000667", + "Non-Small Cell Lung Cancer | ACH-000672", + "Non-Small Cell Lung Cancer | ACH-000677", + "Non-Small Cell Lung Cancer | ACH-000681", + "Non-Small Cell Lung Cancer | ACH-000700", + "Non-Small Cell Lung Cancer | ACH-000706", + "Non-Small Cell Lung Cancer | ACH-000718", + "Non-Small Cell Lung Cancer | ACH-000747", + "Non-Small Cell Lung Cancer | ACH-000757", + "Non-Small Cell Lung Cancer | ACH-000766", + "Non-Small Cell Lung Cancer | ACH-000769", + "Non-Small Cell Lung Cancer | ACH-000774", + "Non-Small Cell Lung Cancer | ACH-000781", + "Non-Small Cell Lung Cancer | ACH-000785", + "Non-Small Cell Lung Cancer | ACH-000787", + "Non-Small Cell Lung Cancer | ACH-000791", + "Non-Small Cell Lung Cancer | ACH-000826", + "Non-Small Cell Lung Cancer | ACH-000837", + "Non-Small Cell Lung Cancer | ACH-000840", + "Non-Small Cell Lung Cancer | ACH-000841", + "Non-Small Cell Lung Cancer | ACH-000843", + "Non-Small Cell Lung Cancer | ACH-000845", + "Non-Small Cell Lung Cancer | ACH-000851", + "Non-Small Cell Lung Cancer | ACH-000853", + "Non-Small Cell Lung Cancer | ACH-000858", + "Non-Small Cell Lung Cancer | ACH-000860", + "Non-Small Cell Lung Cancer | ACH-000861", + "Non-Small Cell Lung Cancer | ACH-000867", + "Non-Small Cell Lung Cancer | ACH-000869", + "Non-Small Cell Lung Cancer | ACH-000872", + "Non-Small Cell Lung Cancer | ACH-000878", + "Non-Small Cell Lung Cancer | ACH-000886", + "Non-Small Cell Lung Cancer | ACH-000888", + "Non-Small Cell Lung Cancer | ACH-000894", + "Non-Small Cell Lung Cancer | ACH-000900", + "Non-Small Cell Lung Cancer | ACH-000901", + "Non-Small Cell Lung Cancer | ACH-000916", + "Non-Small Cell Lung Cancer | ACH-000921", + "Non-Small Cell Lung Cancer | ACH-000924", + "Non-Small Cell Lung Cancer | ACH-000929", + "Non-Small Cell Lung Cancer | ACH-000945", + "Non-Small Cell Lung Cancer | ACH-000975", + "Non-Small Cell Lung Cancer | ACH-000980", + "Non-Small Cell Lung Cancer | ACH-001075", + "Non-Small Cell Lung Cancer | ACH-001137", + "Non-Small Cell Lung Cancer | ACH-001233", + "Non-Small Cell Lung Cancer | ACH-002035", + "Non-Small Cell Lung Cancer | ACH-002156", + "Non-Small Cell Lung Cancer | ACH-002522", + "Non-Small Cell Lung Cancer | ACH-002526", + "Non-Small Cell Lung Cancer | ACH-002531", + "Non-Small Cell Lung Cancer | ACH-002650", + "Non-Small Cell Lung Cancer | ACH-003012" + ], + "type": "scattergl", + "x": { + "bdata": 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"ACH-000827", + "ACH-000881", + "ACH-000882", + "ACH-000884", + "ACH-000899", + "ACH-000915", + "ACH-000968", + "ACH-001041", + "ACH-001190", + "ACH-001239", + "ACH-001522", + "ACH-001563", + "ACH-001566", + "ACH-001567", + "ACH-001568", + "ACH-001570", + "ACH-001645", + "ACH-001970", + "ACH-001972", + "ACH-001973", + "ACH-001975", + "ACH-001982", + "ACH-001986", + "ACH-001990", + "ACH-002001", + "ACH-002002", + "ACH-002003", + "ACH-002004", + "ACH-002005", + "ACH-002084", + "ACH-002143", + "ACH-002458", + "ACH-002460", + "ACH-002461", + "ACH-002508", + "ACH-002510", + "ACH-002511", + "ACH-002512", + "ACH-002847", + "ACH-002928" + ], + "hoverinfo": "text", + "marker": { + "color": "#19D3F3", + "size": 7 + }, + "mode": "markers", + "name": "Melanoma", + "text": [ + "Melanoma | ACH-000014", + "Melanoma | ACH-000219", + "Melanoma | ACH-000274", + "Melanoma | ACH-000304", + "Melanoma | ACH-000322", + "Melanoma | ACH-000348", + "Melanoma | ACH-000401", + "Melanoma | ACH-000404", + "Melanoma | ACH-000425", + "Melanoma | ACH-000441", + "Melanoma | ACH-000450", + "Melanoma | ACH-000458", + "Melanoma | ACH-000477", + "Melanoma | ACH-000550", + "Melanoma | ACH-000579", + "Melanoma | ACH-000580", + "Melanoma | ACH-000614", + "Melanoma | ACH-000632", + "Melanoma | ACH-000661", + "Melanoma | ACH-000765", + "Melanoma | ACH-000788", + "Melanoma | ACH-000799", + "Melanoma | ACH-000801", + "Melanoma | ACH-000805", + "Melanoma | ACH-000810", + "Melanoma | ACH-000822", + "Melanoma | ACH-000827", + "Melanoma | ACH-000881", + "Melanoma | ACH-000882", + "Melanoma | ACH-000884", + "Melanoma | ACH-000899", + "Melanoma | ACH-000915", + "Melanoma | ACH-000968", + "Melanoma | ACH-001041", + "Melanoma | ACH-001190", + "Melanoma | ACH-001239", + "Melanoma | ACH-001522", + "Melanoma | ACH-001563", + "Melanoma | ACH-001566", + "Melanoma | ACH-001567", + "Melanoma | ACH-001568", + "Melanoma | ACH-001570", + "Melanoma | ACH-001645", + "Melanoma | ACH-001970", + "Melanoma | ACH-001972", + "Melanoma | ACH-001973", + "Melanoma | ACH-001975", + "Melanoma | ACH-001982", + "Melanoma | ACH-001986", + "Melanoma | ACH-001990", + "Melanoma | ACH-002001", + "Melanoma | ACH-002002", + "Melanoma | ACH-002003", + "Melanoma | ACH-002004", + "Melanoma | ACH-002005", + "Melanoma | ACH-002084", + "Melanoma | ACH-002143", + "Melanoma | ACH-002458", + "Melanoma | ACH-002460", + "Melanoma | ACH-002461", + "Melanoma | ACH-002508", + "Melanoma | ACH-002510", + "Melanoma | ACH-002511", + "Melanoma | ACH-002512", + "Melanoma | ACH-002847", + "Melanoma | ACH-002928" + ], + "type": "scattergl", + "x": { + "bdata": "7FguQHmL30A+qSDA8ygIPyhld0CrGKS/lgovQOSw8sDf0vLA5OaQQDLM8sDNs/LA9c2LPb0bEsC82/LAty3WvUNfc0BUbh1ANrPywAKysD8wpNE/1uCfvCPZ8sAykL4/dFanPvkxJ8D4G6I/1idpQLe8lkAYiltA1dDywOh/k0CW3YFAJnsiQG6/nL/vi35AYyK1P8/Y8sDq3fLA2OHywEPW8sB4w/LAAW70vX24CEDqtPLA/LvywPfA8sCaEGJALhuHQFgLrEDeeZFAz9DVQG8nC0DmyvLAma1oQP3jDr9cfDnAqgojQNYVFkB+fTU++15nvyDZdEAK217Auim3PktPfb0rfhvA", + "dtype": "f4" + }, + "y": { + "bdata": 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"ACH-001393", + "ACH-001394", + "ACH-001396", + "ACH-001419", + "ACH-001662", + "ACH-001683", + "ACH-001819", + "ACH-002179", + "ACH-002399", + "ACH-002401" + ], + "hoverinfo": "text", + "marker": { + "color": "#FF6692", + "size": 7 + }, + "mode": "markers", + "name": "Invasive Breast Carcinoma", + "text": [ + "Invasive Breast Carcinoma | ACH-000017", + "Invasive Breast Carcinoma | ACH-000019", + "Invasive Breast Carcinoma | ACH-000028", + "Invasive Breast Carcinoma | ACH-000097", + "Invasive Breast Carcinoma | ACH-000111", + "Invasive Breast Carcinoma | ACH-000147", + "Invasive Breast Carcinoma | ACH-000148", + "Invasive Breast Carcinoma | ACH-000212", + "Invasive Breast Carcinoma | ACH-000223", + "Invasive Breast Carcinoma | ACH-000248", + "Invasive Breast Carcinoma | ACH-000258", + "Invasive Breast Carcinoma | ACH-000276", + "Invasive Breast Carcinoma | ACH-000277", + "Invasive Breast Carcinoma | ACH-000288", + "Invasive Breast Carcinoma | ACH-000330", + "Invasive Breast Carcinoma | ACH-000352", + "Invasive Breast Carcinoma | ACH-000374", + "Invasive Breast Carcinoma | ACH-000554", + "Invasive Breast Carcinoma | ACH-000573", + "Invasive Breast Carcinoma | ACH-000621", + "Invasive Breast Carcinoma | ACH-000668", + "Invasive Breast Carcinoma | ACH-000699", + "Invasive Breast Carcinoma | ACH-000711", + "Invasive Breast Carcinoma | ACH-000721", + "Invasive Breast Carcinoma | ACH-000768", + "Invasive Breast Carcinoma | ACH-000783", + "Invasive Breast Carcinoma | ACH-000849", + "Invasive Breast Carcinoma | ACH-000856", + "Invasive Breast Carcinoma | ACH-000876", + "Invasive Breast Carcinoma | ACH-000910", + "Invasive Breast Carcinoma | ACH-000934", + "Invasive Breast Carcinoma | ACH-001065", + "Invasive Breast Carcinoma | ACH-001388", + "Invasive Breast Carcinoma | ACH-001389", + "Invasive Breast Carcinoma | ACH-001390", + "Invasive Breast Carcinoma | ACH-001391", + "Invasive Breast Carcinoma | ACH-001392", + "Invasive Breast Carcinoma | ACH-001393", + "Invasive Breast Carcinoma | ACH-001394", + "Invasive Breast Carcinoma | ACH-001396", + "Invasive Breast Carcinoma | ACH-001419", + "Invasive Breast Carcinoma | ACH-001662", + "Invasive Breast Carcinoma | ACH-001683", + "Invasive Breast Carcinoma | ACH-001819", + "Invasive Breast Carcinoma | ACH-002179", + "Invasive Breast Carcinoma | ACH-002399", + "Invasive Breast Carcinoma | ACH-002401" + ], + "type": "scattergl", + "x": { + "bdata": "rkW1vVsoAEC1uoxAFfaQPyCmQ0DKLFpAbvxLPyOzmz+cVMO/HdnmP3/4gr+78l2/4kURPS1q7z87dn0/WEV5P8gN6z/dOwzAAqDbPxi3YMB1QIq/UP/2v/OVE0B8c05ABCWeP5jKOsAQ9GZA6EPrQCD1eb9wwn1AgExdwCFbr0BMPAvAzsvywIwbxz+MbTPArtLywFrW8sCez/LAeu3ywG3mAz+T0LS+WhW8PonUvb9DUUdA7QmoPxqJEkA=", + "dtype": "f4" + }, + "y": { + "bdata": "2bE+v8uRlr/uW82/IfMhv8F8AcB+tZi/C1nlP9Abtz7lxHy9p5q1v5IsjT5cP4Y/GMIpv20cMkDw29G+SpiMvwIcrb6yKO2/piLDPkJOoj/6oYy/zqSpP1OKkr+gFWi/qcpCvgkCPL9qFEa/gxMJPEUssr/+thPAkVHSv+bVCsAyckg/nJ2qv1hXXT8Xl0k/Ewurv+Oyqr/OFKu/Z7+qv9uNGD7hwHY8PX7uvh4BAL9aYB7AyrsqvkJNu70=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000022", + "ACH-000023", + "ACH-000042", + "ACH-000060", + "ACH-000085", + "ACH-000093", + "ACH-000094", + "ACH-000114", + "ACH-000118", + "ACH-000138", + "ACH-000139", + "ACH-000155", + "ACH-000164", + "ACH-000178", + "ACH-000213", + "ACH-000222", + "ACH-000235", + "ACH-000243", + "ACH-000265", + "ACH-000266", + "ACH-000281", + "ACH-000307", + "ACH-000320", + "ACH-000332", + "ACH-000354", + "ACH-000417", + "ACH-000468", + "ACH-000502", + "ACH-000517", + "ACH-000535", + "ACH-000599", + "ACH-000601", + "ACH-000652", + "ACH-001098", + "ACH-001107", + "ACH-001353", + "ACH-001375", + "ACH-001377", + "ACH-001379", + "ACH-001380", + "ACH-001382", + "ACH-001999", + "ACH-002039", + "ACH-002186", + "ACH-002672" + ], + "hoverinfo": "text", + "marker": { + "color": "#B6E880", + "size": 7 + }, + "mode": "markers", + "name": "Pancreatic Adenocarcinoma", + "text": [ + "Pancreatic Adenocarcinoma | ACH-000022", + "Pancreatic Adenocarcinoma | ACH-000023", + "Pancreatic Adenocarcinoma | ACH-000042", + "Pancreatic Adenocarcinoma | ACH-000060", + "Pancreatic Adenocarcinoma | ACH-000085", + "Pancreatic Adenocarcinoma | ACH-000093", + "Pancreatic Adenocarcinoma | ACH-000094", + "Pancreatic Adenocarcinoma | ACH-000114", + "Pancreatic Adenocarcinoma | ACH-000118", + "Pancreatic Adenocarcinoma | ACH-000138", + "Pancreatic Adenocarcinoma | ACH-000139", + "Pancreatic Adenocarcinoma | ACH-000155", + "Pancreatic Adenocarcinoma | ACH-000164", + "Pancreatic Adenocarcinoma | ACH-000178", + "Pancreatic Adenocarcinoma | ACH-000213", + "Pancreatic Adenocarcinoma | ACH-000222", + "Pancreatic Adenocarcinoma | ACH-000235", + "Pancreatic Adenocarcinoma | ACH-000243", + "Pancreatic Adenocarcinoma | ACH-000265", + "Pancreatic Adenocarcinoma | ACH-000266", + "Pancreatic Adenocarcinoma | ACH-000281", + "Pancreatic Adenocarcinoma | ACH-000307", + "Pancreatic Adenocarcinoma | ACH-000320", + "Pancreatic Adenocarcinoma | ACH-000332", + "Pancreatic Adenocarcinoma | ACH-000354", + "Pancreatic Adenocarcinoma | ACH-000417", + "Pancreatic Adenocarcinoma | ACH-000468", + "Pancreatic Adenocarcinoma | ACH-000502", + "Pancreatic Adenocarcinoma | ACH-000517", + "Pancreatic Adenocarcinoma | ACH-000535", + "Pancreatic Adenocarcinoma | ACH-000599", + "Pancreatic Adenocarcinoma | ACH-000601", + "Pancreatic Adenocarcinoma | ACH-000652", + "Pancreatic Adenocarcinoma | ACH-001098", + "Pancreatic Adenocarcinoma | ACH-001107", + "Pancreatic Adenocarcinoma | ACH-001353", + "Pancreatic Adenocarcinoma | ACH-001375", + "Pancreatic Adenocarcinoma | ACH-001377", + "Pancreatic Adenocarcinoma | ACH-001379", + "Pancreatic Adenocarcinoma | ACH-001380", + "Pancreatic Adenocarcinoma | ACH-001382", + "Pancreatic Adenocarcinoma | ACH-001999", + "Pancreatic Adenocarcinoma | ACH-002039", + "Pancreatic Adenocarcinoma | ACH-002186", + "Pancreatic Adenocarcinoma | ACH-002672" + ], + "type": "scattergl", + "x": { + "bdata": "CDm1P29anEB1KCTAEwm3v+jJoL7n1Aq/uZukv/CL87/F7RVAUe3NP/wdNL8BFSm/l6y4P/rbC0AGF94/djFHwJG/mD57yL0/HILGQJlIWsC+N1i/zdHywELOA0B3tE8+LjHLPsJfob/f5PLAiSQ8Pz1k7r9FMTE/pIdoPjQClkBoG2A/LvHUP13emr44X6W/eriBvxxBMkCxutQ/H+hVQKoQmr/Uv/LAGdPywIPD8sCBrTE/", + "dtype": "f4" + }, + "y": { + "bdata": "rbL+vEFG2T/vqVo/fEijP2FkVD/eBNY/gwyTv4da1T85W0S/zlQJPxzD3D7owTY/tymPPS4Btj5qfJa/A2Swv6m5or7KtZ8/zKSePhpsyT851KI/ebqqv19FEz9m3qA/3p+Tv6vfoL4OyKq/PokiPs70wz8FcaA/iSesvwVzVr9ewlg/QZThviiHvz+Q2b4/a4GNPxiTaD+q9t8+gXJlPYqhC0Aq9aq/N4mqv+mxq7/oBgg/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000024", + "ACH-000106", + "ACH-000124", + "ACH-000167", + "ACH-000183", + "ACH-000204", + "ACH-000271", + "ACH-000315", + "ACH-000334", + "ACH-000346", + "ACH-000363", + "ACH-000365", + "ACH-000371", + "ACH-000398", + "ACH-000402", + "ACH-000405", + "ACH-000426", + "ACH-000436", + "ACH-000512", + "ACH-000541", + "ACH-000567", + "ACH-000576", + "ACH-000588", + "ACH-000653", + "ACH-000654", + "ACH-000656", + "ACH-000660", + "ACH-000697", + "ACH-000714", + "ACH-000763", + "ACH-000817", + "ACH-000821", + "ACH-000829", + "ACH-000838", + "ACH-000889", + "ACH-000914", + "ACH-000944", + "ACH-001450", + "ACH-001498", + "ACH-001533", + "ACH-001539", + "ACH-001616", + "ACH-001634", + "ACH-001639", + "ACH-001677", + "ACH-001707", + "ACH-001709", + "ACH-002055", + "ACH-002062", + "ACH-002214", + "ACH-002215", + "ACH-002478", + "ACH-002485", + "ACH-002500", + "ACH-002677", + "ACH-002678" + ], + "hoverinfo": "text", + "marker": { + "color": "#FF97FF", + "size": 7 + }, + "mode": "markers", + "name": "Mature B-Cell Neoplasms", + "text": [ + "Mature B-Cell Neoplasms | ACH-000024", + "Mature B-Cell Neoplasms | ACH-000106", + "Mature B-Cell Neoplasms | ACH-000124", + "Mature B-Cell Neoplasms | ACH-000167", + "Mature B-Cell Neoplasms | ACH-000183", + "Mature B-Cell Neoplasms | ACH-000204", + "Mature B-Cell Neoplasms | ACH-000271", + "Mature B-Cell Neoplasms | ACH-000315", + "Mature B-Cell Neoplasms | ACH-000334", + "Mature B-Cell Neoplasms | ACH-000346", + "Mature B-Cell Neoplasms | ACH-000363", + "Mature B-Cell Neoplasms | ACH-000365", + "Mature B-Cell Neoplasms | ACH-000371", + "Mature B-Cell Neoplasms | ACH-000398", + "Mature B-Cell Neoplasms | ACH-000402", + "Mature B-Cell Neoplasms | ACH-000405", + "Mature B-Cell Neoplasms | ACH-000426", + "Mature B-Cell Neoplasms | ACH-000436", + "Mature B-Cell Neoplasms | ACH-000512", + "Mature B-Cell Neoplasms | ACH-000541", + "Mature B-Cell Neoplasms | ACH-000567", + "Mature B-Cell Neoplasms | ACH-000576", + "Mature B-Cell Neoplasms | ACH-000588", + "Mature B-Cell Neoplasms | ACH-000653", + "Mature B-Cell Neoplasms | ACH-000654", + "Mature B-Cell Neoplasms | ACH-000656", + "Mature B-Cell Neoplasms | ACH-000660", + "Mature B-Cell Neoplasms | ACH-000697", + "Mature B-Cell Neoplasms | ACH-000714", + "Mature B-Cell Neoplasms | ACH-000763", + "Mature B-Cell Neoplasms | ACH-000817", + "Mature B-Cell Neoplasms | ACH-000821", + "Mature B-Cell Neoplasms | ACH-000829", + "Mature B-Cell Neoplasms | ACH-000838", + "Mature B-Cell Neoplasms | ACH-000889", + "Mature B-Cell Neoplasms | ACH-000914", + "Mature B-Cell Neoplasms | ACH-000944", + "Mature B-Cell Neoplasms | ACH-001450", + "Mature B-Cell Neoplasms | ACH-001498", + "Mature B-Cell Neoplasms | ACH-001533", + "Mature B-Cell Neoplasms | ACH-001539", + "Mature B-Cell Neoplasms | ACH-001616", + "Mature B-Cell Neoplasms | ACH-001634", + "Mature B-Cell Neoplasms | ACH-001639", + "Mature B-Cell Neoplasms | ACH-001677", + "Mature B-Cell Neoplasms | ACH-001707", + "Mature B-Cell Neoplasms | ACH-001709", + "Mature B-Cell Neoplasms | ACH-002055", + "Mature B-Cell Neoplasms | ACH-002062", + "Mature B-Cell Neoplasms | ACH-002214", + "Mature B-Cell Neoplasms | ACH-002215", + "Mature B-Cell Neoplasms | ACH-002478", + "Mature B-Cell Neoplasms | ACH-002485", + "Mature B-Cell Neoplasms | ACH-002500", + "Mature B-Cell Neoplasms | ACH-002677", + "Mature B-Cell Neoplasms | ACH-002678" + ], + "type": "scattergl", + "x": { + "bdata": "t7c4QLlv6z/HxuxAxpkSQLDVsUDIH59AtUsPQeZaD0D/9Zu/peWLQEmVKT6ps7xA9oyGQMmJWEA5xw1APPubQC/Krz3T4/LAeCpTQB254z+1tfLAmnn9PkI7okAJczNAkT0lQP+fBEF5/AVBQ7qEQNSVEkAMDMQ/qvlkQKZ88j/hrPLAxnbGP4d6yEDrAOBA+C6XQIWsg0A9WaFAGtPywD5rzT8HPspARrPywFo4+z+M3PA/JsPywLsb8EB39kxA1UYRQABdz0C/939AwwBAQM31LUDEy7lAeIW8QIZZKkA=", + "dtype": "f4" + }, + "y": { + "bdata": "66ZlwO87kr9NKYLAyH8mwEBRi8DqQJnAT1a/wANvNMCmyj/AQ2hVwBbIZ8DvjJTA3bFvwMSbU8D6BSnAlDhUwCZ4LMCQLqu/bCk1wOQqOcBxeau/UqpCwFT8csDWkGnAO11wwF4loMDNqXfA7VAjwPvWb8CqPj7An25ywPGBNcA1Z6u/dAFVwCWQeMAmNZXAP2dkwJEGicA0/WrAkxurv7NHHMADXq7AIYWrvzooiMClkeW/oeOqv5M/nsBc/1DA8DcVwEF7jsASMzjABUNKwPE2+b86uWbAs2WcwDUbWMA=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000025", + "ACH-001067", + "ACH-002070" + ], + "hoverinfo": "text", + "marker": { + "color": "#FECB52", + "size": 7 + }, + "mode": "markers", + "name": "Meningothelial Tumor", + "text": [ + "Meningothelial Tumor | ACH-000025", + "Meningothelial Tumor | ACH-001067", + "Meningothelial Tumor | ACH-002070" + ], + "type": "scattergl", + "x": { + "bdata": "28RMQHnG8sDmH4I/", + "dtype": "f4" + }, + "y": { + "bdata": "nxIiQJ+aqr9v4ds/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000036", + "ACH-000040", + "ACH-000067", + "ACH-000075", + "ACH-000098", + "ACH-000128", + "ACH-000137", + "ACH-000152", + "ACH-000200", + "ACH-000208", + "ACH-000215", + "ACH-000231", + "ACH-000232", + "ACH-000244", + "ACH-000269", + "ACH-000273", + "ACH-000323", + "ACH-000329", + "ACH-000368", + "ACH-000370", + "ACH-000376", + "ACH-000389", + "ACH-000437", + "ACH-000445", + "ACH-000455", + "ACH-000464", + "ACH-000469", + "ACH-000479", + "ACH-000504", + "ACH-000558", + "ACH-000570", + "ACH-000571", + "ACH-000591", + "ACH-000592", + "ACH-000595", + "ACH-000609", + "ACH-000622", + "ACH-000623", + "ACH-000631", + "ACH-000634", + "ACH-000655", + "ACH-000673", + "ACH-000676", + "ACH-000738", + "ACH-000756", + "ACH-000760", + "ACH-000807", + "ACH-000819", + "ACH-000863", + "ACH-000887", + "ACH-001016", + "ACH-001126", + "ACH-001172", + "ACH-001329", + "ACH-001605", + "ACH-001606", + "ACH-001608", + "ACH-001609", + "ACH-001610", + "ACH-001611", + "ACH-001622", + "ACH-001623", + "ACH-001624", + "ACH-002228", + "ACH-002229", + "ACH-002230", + "ACH-002257", + "ACH-002269", + "ACH-002304", + "ACH-002680" + ], + "hoverinfo": "text", + "marker": { + "color": "#FD3216", + "size": 7 + }, + "mode": "markers", + "name": "Diffuse Glioma", + "text": [ + "Diffuse Glioma | ACH-000036", + "Diffuse Glioma | ACH-000040", + "Diffuse Glioma | ACH-000067", + "Diffuse Glioma | ACH-000075", + "Diffuse Glioma | ACH-000098", + "Diffuse Glioma | ACH-000128", + "Diffuse Glioma | ACH-000137", + "Diffuse Glioma | ACH-000152", + "Diffuse Glioma | ACH-000200", + "Diffuse Glioma | ACH-000208", + "Diffuse Glioma | ACH-000215", + "Diffuse Glioma | ACH-000231", + "Diffuse Glioma | ACH-000232", + "Diffuse Glioma | ACH-000244", + "Diffuse Glioma | ACH-000269", + "Diffuse Glioma | ACH-000273", + "Diffuse Glioma | ACH-000323", + "Diffuse Glioma | ACH-000329", + "Diffuse Glioma | ACH-000368", + "Diffuse Glioma | ACH-000370", + "Diffuse Glioma | ACH-000376", + "Diffuse Glioma | ACH-000389", + "Diffuse Glioma | ACH-000437", + "Diffuse Glioma | ACH-000445", + "Diffuse Glioma | ACH-000455", + "Diffuse Glioma | ACH-000464", + "Diffuse Glioma | ACH-000469", + "Diffuse Glioma | ACH-000479", + "Diffuse Glioma | ACH-000504", + "Diffuse Glioma | ACH-000558", + "Diffuse Glioma | ACH-000570", + "Diffuse Glioma | ACH-000571", + "Diffuse Glioma | ACH-000591", + "Diffuse Glioma | ACH-000592", + "Diffuse Glioma | ACH-000595", + "Diffuse Glioma | ACH-000609", + "Diffuse Glioma | ACH-000622", + "Diffuse Glioma | ACH-000623", + "Diffuse Glioma | ACH-000631", + "Diffuse Glioma | ACH-000634", + "Diffuse Glioma | ACH-000655", + "Diffuse Glioma | ACH-000673", + "Diffuse Glioma | ACH-000676", + "Diffuse Glioma | ACH-000738", + "Diffuse Glioma | ACH-000756", + "Diffuse Glioma | ACH-000760", + "Diffuse Glioma | ACH-000807", + "Diffuse Glioma | ACH-000819", + "Diffuse Glioma | ACH-000863", + "Diffuse Glioma | ACH-000887", + "Diffuse Glioma | ACH-001016", + "Diffuse Glioma | ACH-001126", + "Diffuse Glioma | ACH-001172", + "Diffuse Glioma | ACH-001329", + "Diffuse Glioma | ACH-001605", + "Diffuse Glioma | ACH-001606", + "Diffuse Glioma | ACH-001608", + "Diffuse Glioma | ACH-001609", + "Diffuse Glioma | ACH-001610", + "Diffuse Glioma | ACH-001611", + "Diffuse Glioma | ACH-001622", + "Diffuse Glioma | ACH-001623", + "Diffuse Glioma | ACH-001624", + "Diffuse Glioma | ACH-002228", + "Diffuse Glioma | ACH-002229", + "Diffuse Glioma | ACH-002230", + "Diffuse Glioma | ACH-002257", + "Diffuse Glioma | ACH-002269", + "Diffuse Glioma | ACH-002304", + "Diffuse Glioma | ACH-002680" + ], + "type": "scattergl", + "x": { + "bdata": "mh/hPVQB678x6tS/KOW3v/dpHT8lrPE/mnBjP14Hzb8X1PLASxKsvqTiD0CPJ+Y+wFaLQMRhVMA15j2+W1oSQN3XjD4pmb696Ux9vxwwrb+8bK5Ak16WvrwJTD9vE12/iNCAQBk8N8CVJqc/ykCZPtr/UMAvm8s/rKj4Pw0KJsBXzSs+pyIDwOfulD8KwX69m7I0wKcv17+u7X6/wujBP85Qgj7W0vLAj2OCQL0vhkAApx5AN1NhPxh4uT+L8Dg/l2YiQDfh2z81yARAfLjywGiXmkDAzgDAJaMwvmKG978AIA1ArVWKP8kgOj4SdIw/orEtvwdNHsBZeCG/767ywDrL8sCfwvLA+1m6velSX0CDyfLAASCkPQ==", + "dtype": "f4" + }, + "y": { + "bdata": "dVSBQJ5QkkCBQHhA32Z2QHhKnEBHHlI/EaJaQERHU0CHtaq/YZHkP5dKJEC+4kxAGIGRP1E2mkAg6nM/BXwiQLspF0BZ1bo/MTumQArZhz9JDMQ/LdJSQDadOkDw2mJAlt8vP6CKiECdrU1AM5QXQHcUcEBPAkZAoUttQE/oGkCEOZFAkcBZQDjAOUAl21xAuK7kP6XFfkD2cwlA6TYNQI79xD9ET6u/bqt1vweQoz+BnG1AhVhUP/tYuz70tBZAx7tCQO/Nnj/UBrc/HWSrv29tDT/d0YJAtCkuQNs8HEAaLwRAKf8FQHGeB0Be8hJABWOPQO2ni0Dy3J8/QMGrv1xIq78e8Kq/M7SjQER6uj9Q36q/DzOEQA==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000037" + ], + "hoverinfo": "text", + "marker": { + "color": "#00FE35", + "size": 7 + }, + "mode": "markers", + "name": "Sarcoma, NOS", + "text": [ + "Sarcoma, NOS | ACH-000037" + ], + "type": "scattergl", + "x": { + "bdata": "P0j4vw==", + "dtype": "f4" + }, + "y": { + "bdata": "yalAQA==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000039", + "ACH-000041", + "ACH-000052", + "ACH-000087", + "ACH-000210", + "ACH-000279", + "ACH-000391", + "ACH-000424", + "ACH-000499", + "ACH-001029", + "ACH-001038", + "ACH-001192", + "ACH-001193", + "ACH-001205", + "ACH-001283", + "ACH-001430", + "ACH-001431", + "ACH-002105", + "ACH-002106", + "ACH-002109", + "ACH-002110", + "ACH-002114", + "ACH-002116", + "ACH-002119", + "ACH-002160" + ], + "hoverinfo": "text", + "marker": { + "color": "#6A76FC", + "size": 7 + }, + "mode": "markers", + "name": "Ewing Sarcoma", + "text": [ + "Ewing Sarcoma | ACH-000039", + "Ewing Sarcoma | ACH-000041", + "Ewing Sarcoma | ACH-000052", + "Ewing Sarcoma | ACH-000087", + "Ewing Sarcoma | ACH-000210", + "Ewing Sarcoma | ACH-000279", + "Ewing Sarcoma | ACH-000391", + "Ewing Sarcoma | ACH-000424", + "Ewing Sarcoma | ACH-000499", + "Ewing Sarcoma | ACH-001029", + "Ewing Sarcoma | ACH-001038", + "Ewing Sarcoma | ACH-001192", + "Ewing Sarcoma | ACH-001193", + "Ewing Sarcoma | ACH-001205", + "Ewing Sarcoma | ACH-001283", + "Ewing Sarcoma | ACH-001430", + "Ewing Sarcoma | ACH-001431", + "Ewing Sarcoma | ACH-002105", + "Ewing Sarcoma | ACH-002106", + "Ewing Sarcoma | ACH-002109", + "Ewing Sarcoma | ACH-002110", + "Ewing Sarcoma | ACH-002114", + "Ewing Sarcoma | ACH-002116", + "Ewing Sarcoma | ACH-002119", + "Ewing Sarcoma | ACH-002160" + ], + "type": "scattergl", + "x": { + "bdata": "/wQSv7AlDb3bRMc+yCtKQOPfhT986IZAAj6OQCvLu0AnEVdADYStQHagTUDuKeo/G0GIP47ntz/g1CFAAqWKP1SgBkCcbHU/J7CIQOQ79z8jCM1ALs/ywJ3w8sBIC7FAhNuoQA==", + "dtype": "f4" + }, + "y": { + "bdata": "IXZBP4dmHb4FDwpA7+bKvkKtt75+OHm/UULXPw9Wiz/OXy8/OH50P0YH7b9y5B4/IKjGP47Tpb2pkLI+6oPIPvlNur5i51pA5uLuvzqBhz8Jrtm9eJ+qv/hpqr8LSEc/4wmlvg==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000047", + "ACH-000144", + "ACH-000216", + "ACH-000239", + "ACH-000247", + "ACH-000255", + "ACH-000303", + "ACH-000325", + "ACH-000344", + "ACH-000356", + "ACH-000383", + "ACH-000427", + "ACH-000466", + "ACH-000485", + "ACH-000507", + "ACH-000581", + "ACH-000616", + "ACH-000633", + "ACH-000736", + "ACH-000746", + "ACH-000758", + "ACH-000764", + "ACH-000793", + "ACH-000847", + "ACH-000880", + "ACH-000898", + "ACH-000911", + "ACH-000919", + "ACH-000932", + "ACH-000948", + "ACH-001368", + "ACH-001496", + "ACH-001497", + "ACH-001500", + "ACH-001544", + "ACH-001653", + "ACH-001654", + "ACH-001664", + "ACH-002141", + "ACH-002161", + "ACH-002202", + "ACH-002446", + "ACH-002705", + "ACH-002706" + ], + "hoverinfo": "text", + "marker": { + "color": "#FED4C4", + "size": 7 + }, + "mode": "markers", + "name": "Esophagogastric Adenocarcinoma", + "text": [ + "Esophagogastric Adenocarcinoma | ACH-000047", + "Esophagogastric Adenocarcinoma | ACH-000144", + "Esophagogastric Adenocarcinoma | ACH-000216", + "Esophagogastric Adenocarcinoma | ACH-000239", + "Esophagogastric Adenocarcinoma | ACH-000247", + "Esophagogastric Adenocarcinoma | ACH-000255", + "Esophagogastric Adenocarcinoma | ACH-000303", + "Esophagogastric Adenocarcinoma | ACH-000325", + "Esophagogastric Adenocarcinoma | ACH-000344", + "Esophagogastric Adenocarcinoma | ACH-000356", + "Esophagogastric Adenocarcinoma | ACH-000383", + "Esophagogastric Adenocarcinoma | ACH-000427", + "Esophagogastric Adenocarcinoma | ACH-000466", + "Esophagogastric Adenocarcinoma | ACH-000485", + "Esophagogastric Adenocarcinoma | ACH-000507", + "Esophagogastric Adenocarcinoma | ACH-000581", + "Esophagogastric Adenocarcinoma | ACH-000616", + "Esophagogastric Adenocarcinoma | ACH-000633", + "Esophagogastric Adenocarcinoma | ACH-000736", + "Esophagogastric Adenocarcinoma | ACH-000746", + "Esophagogastric Adenocarcinoma | ACH-000758", + "Esophagogastric Adenocarcinoma | ACH-000764", + "Esophagogastric Adenocarcinoma | ACH-000793", + "Esophagogastric Adenocarcinoma | ACH-000847", + "Esophagogastric Adenocarcinoma | ACH-000880", + "Esophagogastric Adenocarcinoma | ACH-000898", + "Esophagogastric Adenocarcinoma | ACH-000911", + "Esophagogastric Adenocarcinoma | ACH-000919", + "Esophagogastric Adenocarcinoma | ACH-000932", + "Esophagogastric Adenocarcinoma | ACH-000948", + "Esophagogastric Adenocarcinoma | ACH-001368", + "Esophagogastric Adenocarcinoma | ACH-001496", + "Esophagogastric Adenocarcinoma | ACH-001497", + "Esophagogastric Adenocarcinoma | ACH-001500", + "Esophagogastric Adenocarcinoma | ACH-001544", + "Esophagogastric Adenocarcinoma | ACH-001653", + "Esophagogastric Adenocarcinoma | ACH-001654", + "Esophagogastric Adenocarcinoma | ACH-001664", + "Esophagogastric Adenocarcinoma | ACH-002141", + "Esophagogastric Adenocarcinoma | ACH-002161", + "Esophagogastric Adenocarcinoma | ACH-002202", + "Esophagogastric Adenocarcinoma | ACH-002446", + "Esophagogastric Adenocarcinoma | ACH-002705", + "Esophagogastric Adenocarcinoma | ACH-002706" + ], + "type": "scattergl", + "x": { + "bdata": "KoaZQC9qNMBw1tA/jXZwvdRGM0CQRqg/qqQNQHFKaEA+XU0/QySWP2aYA70+vPLA0QapvpPCBEBPEINAa5HKP3I5Bb8/nlNAS45eQJ5Dqj9d00tAUsTywLk9V0ALwvLAwCWMQNPURT/CqHhAbIHPP9eYf0CSKWRAZMUnQGiUdj+6a38/0I5OQJx+8b6tEPs/BXkBQNnFo0C1QKZAcmweQLj4GEC/AEBAIDotQFyygEA=", + "dtype": "f4" + }, + "y": { + "bdata": "AGfAv1HNsT7J2oA/1BMQPfTowL+UAxZA/U0avyNRPsAAwJA/3xu/vqk24r+rcau/4AgrQOu9nb+kqtW/OfgTwMB4B0AdwZW/ZH3+v514H8AyYZK/t6+qv+/uJ8Dj5qq/wtBDvro4/L9y65m/0dqmvq/wCcCEp22/P3IJwCJc6b8WUdy/3156PwCYyr9u+J2/6QsaQJqvSsBhSBHAhFpRv34Rhr407t++hIfGvoyKM78=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000053", + "ACH-000101", + "ACH-000226", + "ACH-000233", + "ACH-000338", + "ACH-000664", + "ACH-000773", + "ACH-001111", + "ACH-001119", + "ACH-001737" + ], + "hoverinfo": "text", + "marker": { + "color": "#FE00CE", + "size": 7 + }, + "mode": "markers", + "name": "Mature T and NK Neoplasms", + "text": [ + "Mature T and NK Neoplasms | ACH-000053", + "Mature T and NK Neoplasms | ACH-000101", + "Mature T and NK Neoplasms | ACH-000226", + "Mature T and NK Neoplasms | ACH-000233", + "Mature T and NK Neoplasms | ACH-000338", + "Mature T and NK Neoplasms | ACH-000664", + "Mature T and NK Neoplasms | ACH-000773", + "Mature T and NK Neoplasms | ACH-001111", + "Mature T and NK Neoplasms | ACH-001119", + "Mature T and NK Neoplasms | ACH-001737" + ], + "type": "scattergl", + "x": { + "bdata": "kZnlP2+nqEBMknFAuvBdQGr/jj9RsuJAmrENQOb/+z++WrK/hmjrPw==", + "dtype": "f4" + }, + "y": { + "bdata": "tmFQwKdKgMAN1j3AB/4hwLk+Or8kLIHAvropwMsj378zGhe/0hKxvg==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000054" + ], + "hoverinfo": "text", + "marker": { + "color": "#0DF9FF", + "size": 7 + }, + "mode": "markers", + "name": "Fibrosarcoma", + "text": [ + "Fibrosarcoma | ACH-000054" + ], + "type": "scattergl", + "x": { + "bdata": "PNxYPw==", + "dtype": "f4" + }, + "y": { + "bdata": "DSHFPw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000055", + "ACH-000095", + "ACH-000160", + "ACH-000211", + "ACH-000776", + "ACH-001020", + "ACH-001028", + "ACH-001031", + "ACH-001033", + "ACH-001053", + "ACH-001054", + "ACH-001232", + "ACH-001289", + "ACH-001670", + "ACH-001711" + ], + "hoverinfo": "text", + "marker": { + "color": "#F6F926", + "size": 7 + }, + "mode": "markers", + "name": "Embryonal Tumor", + "text": [ + "Embryonal Tumor | ACH-000055", + "Embryonal Tumor | ACH-000095", + "Embryonal Tumor | ACH-000160", + "Embryonal Tumor | ACH-000211", + "Embryonal Tumor | ACH-000776", + "Embryonal Tumor | ACH-001020", + "Embryonal Tumor | ACH-001028", + "Embryonal Tumor | ACH-001031", + "Embryonal Tumor | ACH-001033", + "Embryonal Tumor | ACH-001053", + "Embryonal Tumor | ACH-001054", + "Embryonal Tumor | ACH-001232", + "Embryonal Tumor | ACH-001289", + "Embryonal Tumor | ACH-001670", + "Embryonal Tumor | ACH-001711" + ], + "type": "scattergl", + "x": { + "bdata": "ibw6QBroEkA4irRAfyyLPZb46D+ejrw/0uaPQJ17kEBURLY/J0DBP77nl0CjfDe9KxjUP/8xOkCFPRVA", + "dtype": "f4" + }, + "y": { + "bdata": "0WiPvyMvKb8AIUM/ENcrQI1QfT/FTaI/7yUfv9/oYz/PRRE/uqc+vmJit79VYYVAs9OKviGNGT+/kg0/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000070", + "ACH-000151", + "ACH-000782", + "ACH-000922", + "ACH-000938", + "ACH-000960", + "ACH-001484", + "ACH-001520", + "ACH-001669", + "ACH-001735", + "ACH-001736", + "ACH-001993", + "ACH-002059" + ], + "hoverinfo": "text", + "marker": { + "color": "#FF9616", + "size": 7 + }, + "mode": "markers", + "name": "B-Lymphoblastic Leukemia/Lymphoma", + "text": [ + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000070", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000151", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000782", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000922", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000938", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000960", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001484", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001520", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001669", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001735", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001736", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001993", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-002059" + ], + "type": "scattergl", + "x": { + "bdata": "eseKQDzO9j+rn3lALfbDQH0Ko0A+wYpAkSFnQMFolkChZ7tA2M9NQDSNy0Cd//w/hnqAQA==", + "dtype": "f4" + }, + "y": { + "bdata": "so+AwHF9b8AWLHnATSSYwLuiocAAvYrA1lhHwKBpWsBjKIvANv+JwFY3nsDjc0fAuUFAwA==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000074", + "ACH-000076", + "ACH-000198", + "ACH-000295", + "ACH-000326", + "ACH-000551", + "ACH-000604", + "ACH-000920", + "ACH-000983", + "ACH-002061" + ], + "hoverinfo": "text", + "marker": { + "color": "#479B55", + "size": 7 + }, + "mode": "markers", + "name": "Myeloproliferative Neoplasms", + "text": [ + "Myeloproliferative Neoplasms | ACH-000074", + "Myeloproliferative Neoplasms | ACH-000076", + "Myeloproliferative Neoplasms | ACH-000198", + "Myeloproliferative Neoplasms | ACH-000295", + "Myeloproliferative Neoplasms | ACH-000326", + "Myeloproliferative Neoplasms | ACH-000551", + "Myeloproliferative Neoplasms | ACH-000604", + "Myeloproliferative Neoplasms | ACH-000920", + "Myeloproliferative Neoplasms | ACH-000983", + "Myeloproliferative Neoplasms | ACH-002061" + ], + "type": "scattergl", + "x": { + "bdata": "y4VSQKHkfkCcTfFACYRtP2RbjUA2u25AEyctQKPzlD9a4qlAwRBtQA==", + "dtype": "f4" + }, + "y": { + "bdata": "2f9GwOTuL8AlO5zAdLUgwKg8XMC82UjAr2sKwEFHmL/URoXAujoxwA==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000077", + "ACH-000583", + "ACH-001197", + "ACH-001642" + ], + "hoverinfo": "text", + "marker": { + "color": "#EEA6FB", + "size": 7 + }, + "mode": "markers", + "name": "Non-Hodgkin Lymphoma", + "text": [ + "Non-Hodgkin Lymphoma | ACH-000077", + "Non-Hodgkin Lymphoma | ACH-000583", + "Non-Hodgkin Lymphoma | ACH-001197", + "Non-Hodgkin Lymphoma | ACH-001642" + ], + "type": "scattergl", + "x": { + "bdata": "RAV+QLuy8sBfUS1AmUrJPw==", + "dtype": "f4" + }, + "y": { + "bdata": "nuzZv5vMq7/8YULAFh0GwA==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000078", + "ACH-000099", + "ACH-000120", + "ACH-000149", + "ACH-000203", + "ACH-000227", + "ACH-000259", + "ACH-000260", + "ACH-000310", + "ACH-000312", + "ACH-000341", + "ACH-000366", + "ACH-000804", + "ACH-001188", + "ACH-001300", + "ACH-001301", + "ACH-001302", + "ACH-001303", + "ACH-001338", + "ACH-001344", + "ACH-001354", + "ACH-001366", + "ACH-001367", + "ACH-001481", + "ACH-001548", + "ACH-001603", + "ACH-001674", + "ACH-002080", + "ACH-002083", + "ACH-002261", + "ACH-002278", + "ACH-002280", + "ACH-002282", + "ACH-002283", + "ACH-002284", + "ACH-002285", + "ACH-002922" + ], + "hoverinfo": "text", + "marker": { + "color": "#DC587D", + "size": 7 + }, + "mode": "markers", + "name": "Neuroblastoma", + "text": [ + "Neuroblastoma | ACH-000078", + "Neuroblastoma | ACH-000099", + "Neuroblastoma | ACH-000120", + "Neuroblastoma | ACH-000149", + "Neuroblastoma | ACH-000203", + "Neuroblastoma | ACH-000227", + "Neuroblastoma | ACH-000259", + "Neuroblastoma | ACH-000260", + "Neuroblastoma | ACH-000310", + "Neuroblastoma | ACH-000312", + "Neuroblastoma | ACH-000341", + "Neuroblastoma | ACH-000366", + "Neuroblastoma | ACH-000804", + "Neuroblastoma | ACH-001188", + "Neuroblastoma | ACH-001300", + "Neuroblastoma | ACH-001301", + "Neuroblastoma | ACH-001302", + "Neuroblastoma | ACH-001303", + "Neuroblastoma | ACH-001338", + "Neuroblastoma | ACH-001344", + "Neuroblastoma | ACH-001354", + "Neuroblastoma | ACH-001366", + "Neuroblastoma | ACH-001367", + "Neuroblastoma | ACH-001481", + "Neuroblastoma | ACH-001548", + "Neuroblastoma | ACH-001603", + "Neuroblastoma | ACH-001674", + "Neuroblastoma | ACH-002080", + "Neuroblastoma | ACH-002083", + "Neuroblastoma | ACH-002261", + "Neuroblastoma | ACH-002278", + "Neuroblastoma | ACH-002280", + "Neuroblastoma | ACH-002282", + "Neuroblastoma | ACH-002283", + "Neuroblastoma | ACH-002284", + "Neuroblastoma | ACH-002285", + "Neuroblastoma | ACH-002922" + ], + "type": "scattergl", + "x": { + "bdata": "UFyKP4JEekBzgac/o8FAQPj7Kb77VQzAUhuzQJnPHUC9svW/1R/IPx4gbTs0E/o/gnmLQIEiL0B3vHdAjkHHvjGtbj9/mB0+5haEQLW5BD+KJ8U/APQwQG/1VECjwjc9n6V4PiH+JEAEaUpAl8jywFYHpUC0cpxAUqGKQOQFiECHcV1A/XIjQPTd8sAnQQlBSiFVQA==", + "dtype": "f4" + }, + "y": { + "bdata": "hVWhvtdvWr8hXNE/WGtiPyQrFT8T/Ri/tm2fv7sP3z9pcyc+2AmPv0ZyfT/xAyi+6YkPv5cqiT/9Vnq+VaizP1X1Xr6pb0c+yob4v2iexj8lOA29fNvCvouDfL9Saw1AFR4pP8loBD4gwNK/UGirv8a0F0D0g5y/rK+5vv39Zb9aLn++Ldu1P5LOqr/ph/M+WT6Wvw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000082", + "ACH-000359", + "ACH-000364", + "ACH-000410", + "ACH-000748", + "ACH-001001", + "ACH-001526", + "ACH-001715", + "ACH-001814", + "ACH-002067", + "ACH-002069", + "ACH-002471", + "ACH-002834" + ], + "hoverinfo": "text", + "marker": { + "color": "#D626FF", + "size": 7 + }, + "mode": "markers", + "name": "Osteosarcoma", + "text": [ + "Osteosarcoma | ACH-000082", + "Osteosarcoma | ACH-000359", + "Osteosarcoma | ACH-000364", + "Osteosarcoma | ACH-000410", + "Osteosarcoma | ACH-000748", + "Osteosarcoma | ACH-001001", + "Osteosarcoma | ACH-001526", + "Osteosarcoma | ACH-001715", + "Osteosarcoma | ACH-001814", + "Osteosarcoma | ACH-002067", + "Osteosarcoma | ACH-002069", + "Osteosarcoma | ACH-002471", + "Osteosarcoma | ACH-002834" + ], + "type": "scattergl", + "x": { + "bdata": "EnVawMOUMcDiTxpADp+MP5wg7z+jKbNAbqTPvwOL5r9wLgvALquoP1StSr6meHK+RtzywA==", + "dtype": "f4" + }, + "y": { + "bdata": "QxswQIzgH0DaOTlAKN31P82cl0AWuxu/S8kEQNwSFEDOGFtA84k5P90HaEDuvf8/dQ+qvw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000086", + "ACH-000092", + "ACH-000153", + "ACH-000319", + "ACH-000331", + "ACH-000335", + "ACH-000367", + "ACH-000569", + "ACH-000645", + "ACH-000648", + "ACH-001547", + "ACH-001555", + "ACH-001556", + "ACH-001557", + "ACH-001558", + "ACH-001559", + "ACH-001560", + "ACH-001562", + "ACH-001977", + "ACH-001992", + "ACH-002033" + ], + "hoverinfo": "text", + "marker": { + "color": "#6E899C", + "size": 7 + }, + "mode": "markers", + "name": "Pleural Mesothelioma", + "text": [ + "Pleural Mesothelioma | ACH-000086", + "Pleural Mesothelioma | ACH-000092", + "Pleural Mesothelioma | ACH-000153", + "Pleural Mesothelioma | ACH-000319", + "Pleural Mesothelioma | ACH-000331", + "Pleural Mesothelioma | ACH-000335", + "Pleural Mesothelioma | ACH-000367", + "Pleural Mesothelioma | ACH-000569", + "Pleural Mesothelioma | ACH-000645", + "Pleural Mesothelioma | ACH-000648", + "Pleural Mesothelioma | ACH-001547", + "Pleural Mesothelioma | ACH-001555", + "Pleural Mesothelioma | ACH-001556", + "Pleural Mesothelioma | ACH-001557", + "Pleural Mesothelioma | ACH-001558", + "Pleural Mesothelioma | ACH-001559", + "Pleural Mesothelioma | ACH-001560", + "Pleural Mesothelioma | ACH-001562", + "Pleural Mesothelioma | ACH-001977", + "Pleural Mesothelioma | ACH-001992", + "Pleural Mesothelioma | ACH-002033" + ], + "type": "scattergl", + "x": { + "bdata": "ImwZQIuoAcBTe7K/QTeqv+c9OD+dNw5AOMfywPV0TD91Ce2/yq6OP5m5Kr8eA6U97IXOP8afVD+J2fLAgsLywHra8sBIxfLAF79+QAAuQkAv6zbA", + "dtype": "f4" + }, + "y": { + "bdata": "5XcEQIBPJEDI01ZAspNiQOJKGkDeEPs+VP+rv165bz8TVD9AFGYNQG1BfkDfRzVA49qIP+baNEDeyqq/H46qv3ilqr8dnaq/dlcHv35Zej+R9oc/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000090", + "ACH-000115", + "ACH-000956", + "ACH-000977", + "ACH-000979", + "ACH-001422", + "ACH-001627", + "ACH-001648", + "ACH-001649" + ], + "hoverinfo": "text", + "marker": { + "color": "#00B5F7", + "size": 7 + }, + "mode": "markers", + "name": "Prostate Adenocarcinoma", + "text": [ + "Prostate Adenocarcinoma | ACH-000090", + "Prostate Adenocarcinoma | ACH-000115", + "Prostate Adenocarcinoma | ACH-000956", + "Prostate Adenocarcinoma | ACH-000977", + "Prostate Adenocarcinoma | ACH-000979", + "Prostate Adenocarcinoma | ACH-001422", + "Prostate Adenocarcinoma | ACH-001627", + "Prostate Adenocarcinoma | ACH-001648", + "Prostate Adenocarcinoma | ACH-001649" + ], + "type": "scattergl", + "x": { + "bdata": "Qx5RPLnXUsAjDwBAGFSZQBp4mz+jInPAhLrywHHG8sC75fLA", + "dtype": "f4" + }, + "y": { + "bdata": "CzfJP0aODz4te76/ZnG/vxHlbj8DVC+/hC6rv6wSq7/FGau/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000096", + "ACH-000172", + "ACH-000533", + "ACH-000597", + "ACH-001099", + "ACH-001128", + "ACH-001211", + "ACH-001212", + "ACH-001532" + ], + "hoverinfo": "text", + "marker": { + "color": "#B68E00", + "size": 7 + }, + "mode": "markers", + "name": "Rhabdoid Cancer", + "text": [ + "Rhabdoid Cancer | ACH-000096", + "Rhabdoid Cancer | ACH-000172", + "Rhabdoid Cancer | ACH-000533", + "Rhabdoid Cancer | ACH-000597", + "Rhabdoid Cancer | ACH-001099", + "Rhabdoid Cancer | ACH-001128", + "Rhabdoid Cancer | ACH-001211", + "Rhabdoid Cancer | ACH-001212", + "Rhabdoid Cancer | ACH-001532" + ], + "type": "scattergl", + "x": { + "bdata": "KC8dQOZq5T92lqdAPdU+QBx0s0AjmglAIPAaQM3byz+GFZ9A", + "dtype": "f4" + }, + "y": { + "bdata": 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"qXQqQFUJJkC3nuo/NOU5QIYyA7/KMpdAOpZ7QNwtOECMSsU/giAaQOOIFECPO25A37yjQA==", + "dtype": "f4" + }, + "y": { + "bdata": "bPFCvwcwqT1p1Gs/EpI+vhoIfkDJjea+1rBhv2kaMT9o7AY++0vrvp/xsz8YnZS/nOiovg==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000108", + "ACH-000685" + ], + "hoverinfo": "text", + "marker": { + "color": "#FF0092", + "size": 7 + }, + "mode": "markers", + "name": "Adenosquamous Carcinoma of the Pancreas", + "text": [ + "Adenosquamous Carcinoma of the Pancreas | ACH-000108", + "Adenosquamous Carcinoma of the Pancreas | ACH-000685" + ], + "type": "scattergl", + "x": { + "bdata": "lUUdwEgzN0A=", + "dtype": "f4" + }, + "y": { + "bdata": "nnF5P1tXFUA=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000133", + "ACH-001310", + "ACH-001453", + "ACH-002210", + "ACH-002247", + "ACH-002462", + "ACH-002463", + "ACH-002464", + "ACH-002465", + "ACH-002467" + ], + "hoverinfo": "text", + "marker": { + "color": "#22FFA7", + "size": 7 + }, + "mode": "markers", + "name": "Non-Cancerous", + "text": [ + "Non-Cancerous | ACH-000133", + "Non-Cancerous | ACH-001310", + "Non-Cancerous | ACH-001453", + "Non-Cancerous | ACH-002210", + "Non-Cancerous | ACH-002247", + "Non-Cancerous | ACH-002462", + "Non-Cancerous | ACH-002463", + "Non-Cancerous | ACH-002464", + "Non-Cancerous | ACH-002465", + "Non-Cancerous | ACH-002467" + ], + "type": "scattergl", + "x": { + "bdata": "xpyUPBm98sAHz1w/koekQLDJ8sDb3vLA+NnywMPV8sCF1PLAB9/ywA==", + "dtype": "f4" + }, + "y": { + "bdata": "DslqQBMhq7+sQA1A/LdgwGbCqr8mIqu/sUyrv90brL+yi6u/ylOrvw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000141", + "ACH-001607", + "ACH-001619", + "ACH-001850", + "ACH-001861", + "ACH-001961" + ], + "hoverinfo": "text", + "marker": { + "color": "#E3EE9E", + "size": 7 + }, + "mode": "markers", + "name": "Intracholecystic Papillary Neoplasm", + "text": [ + "Intracholecystic Papillary Neoplasm | ACH-000141", + "Intracholecystic Papillary Neoplasm | ACH-001607", + "Intracholecystic Papillary Neoplasm | ACH-001619", + "Intracholecystic Papillary Neoplasm | ACH-001850", + "Intracholecystic Papillary Neoplasm | ACH-001861", + "Intracholecystic Papillary Neoplasm | ACH-001961" + ], + "type": "scattergl", + "x": { + "bdata": "xNbywAldL0DOXdq/eU8xQJ6x8sBfE/s/", + "dtype": "f4" + }, + "y": { + "bdata": "kQmrvzzujL+Vag1AmPI2vuvxqr8/nh6/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000145", + "ACH-000505", + "ACH-002785" + ], + "hoverinfo": "text", + "marker": { + "color": "#86CE00", + "size": 7 + }, + "mode": "markers", + "name": "Leiomyosarcoma", + "text": [ + "Leiomyosarcoma | ACH-000145", + "Leiomyosarcoma | ACH-000505", + "Leiomyosarcoma | ACH-002785" + ], + "type": "scattergl", + "x": { + "bdata": "AiMRwNwxQ8C4Iey/", + "dtype": "f4" + }, + "y": { + "bdata": "GXs6QN11QkAodWw/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000159", + "ACH-000189", + "ACH-000234", + "ACH-000246", + "ACH-000250", + "ACH-000262", + "ACH-000272", + "ACH-000313", + "ACH-000317", + "ACH-000375", + "ACH-000385", + "ACH-000411", + "ACH-000433", + "ACH-000459", + "ACH-000484", + "ACH-000495", + "ACH-000649", + "ACH-000684", + "ACH-000709", + "ACH-000792", + "ACH-000907", + "ACH-001163", + "ACH-001194", + "ACH-001398", + "ACH-001687", + "ACH-001688", + "ACH-002150", + "ACH-002189", + "ACH-002533" + ], + "hoverinfo": "text", + "marker": { + "color": "#BC7196", + "size": 7 + }, + "mode": "markers", + "name": "Renal Cell Carcinoma", + "text": [ + "Renal Cell Carcinoma | ACH-000159", + "Renal Cell Carcinoma | ACH-000189", + "Renal Cell Carcinoma | ACH-000234", + "Renal Cell Carcinoma | ACH-000246", + "Renal Cell Carcinoma | ACH-000250", + "Renal Cell Carcinoma | ACH-000262", + "Renal Cell Carcinoma | ACH-000272", + "Renal Cell Carcinoma | ACH-000313", + "Renal Cell Carcinoma | ACH-000317", + "Renal Cell Carcinoma | ACH-000375", + "Renal Cell Carcinoma | ACH-000385", + "Renal Cell Carcinoma | ACH-000411", + "Renal Cell Carcinoma | ACH-000433", + "Renal Cell Carcinoma | ACH-000459", + "Renal Cell Carcinoma | ACH-000484", + "Renal Cell Carcinoma | ACH-000495", + "Renal Cell Carcinoma | ACH-000649", + "Renal Cell Carcinoma | ACH-000684", + "Renal Cell Carcinoma | ACH-000709", + "Renal Cell Carcinoma | ACH-000792", + "Renal Cell Carcinoma | ACH-000907", + "Renal Cell Carcinoma | ACH-001163", + "Renal Cell Carcinoma | ACH-001194", + "Renal Cell Carcinoma | ACH-001398", + "Renal Cell Carcinoma | ACH-001687", + "Renal Cell Carcinoma | ACH-001688", + "Renal Cell Carcinoma | ACH-002150", + "Renal Cell Carcinoma | ACH-002189", + "Renal Cell Carcinoma | ACH-002533" + ], + "type": "scattergl", + "x": { + "bdata": "iFm1v3ff8sAKpB7Aq8DywNyv8sDQt/LAuc7ywHSHOcC5u/LA1OV1QGs+Sz4ieps/xIBtv98pvMDy3fLAQgjFv3ZD8T+uFQu/i+YkwNTE9T5Kv1XAiGOqPxC88sDIc1e+osTywHTC8sD2wfLAQBpXwKOMQkA=", + "dtype": "f4" + }, + "y": { + "bdata": "OxmZPwgTq7/qY0pAPJCrvwpCq78hFqu/W+mqv9ODC0AUj6u/bEubPN+NCkAVYhNAqhhKQEdNJj/ayaq/Ro4xQGIKEkDuC1NAoYcUQMJHj0BzcXFAY2Wuvzz4qr91Vm8/9E6rv7Owq79U8aq/EakbQH3cXb4=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000163", + "ACH-000181", + "ACH-000188", + "ACH-000207", + "ACH-000228", + "ACH-000238", + "ACH-000415", + "ACH-000472", + "ACH-000500", + "ACH-000503", + "ACH-000518", + "ACH-000546", + "ACH-000548", + "ACH-000549", + "ACH-000606", + "ACH-000618", + "ACH-000619", + "ACH-000630", + "ACH-000682", + "ACH-000732", + "ACH-000735", + "ACH-000740", + "ACH-000762", + "ACH-000771", + "ACH-000778", + "ACH-000794", + "ACH-000832", + "ACH-000836", + "ACH-000846", + "ACH-001228", + "ACH-001229", + "ACH-001331", + "ACH-001332", + "ACH-001346", + "ACH-001347", + "ACH-001385", + "ACH-001509", + "ACH-001510", + "ACH-001511", + "ACH-001542", + "ACH-001543", + "ACH-001625", + "ACH-001626", + "ACH-001641", + "ACH-001675", + "ACH-001690", + "ACH-001691", + "ACH-001692", + "ACH-001694", + "ACH-001695", + "ACH-001696", + "ACH-001698", + "ACH-001699", + "ACH-001701", + "ACH-002029", + "ACH-002030", + "ACH-002042", + "ACH-002043", + "ACH-002044", + "ACH-002045", + "ACH-002212", + "ACH-002249", + "ACH-002250", + "ACH-002251", + "ACH-002265", + "ACH-002294", + "ACH-002295", + "ACH-002296", + "ACH-002297", + "ACH-002298", + "ACH-002305" + ], + "hoverinfo": "text", + "marker": { + "color": "#7E7DCD", + "size": 7 + }, + "mode": "markers", + "name": "Head and Neck Squamous Cell Carcinoma", + "text": [ + "Head and Neck Squamous Cell Carcinoma | ACH-000163", + "Head and Neck Squamous Cell Carcinoma | ACH-000181", + "Head and Neck Squamous Cell Carcinoma | ACH-000188", + "Head and Neck Squamous Cell Carcinoma | ACH-000207", + "Head and Neck Squamous Cell Carcinoma | ACH-000228", + "Head and Neck Squamous Cell Carcinoma | ACH-000238", + "Head and Neck Squamous Cell Carcinoma | ACH-000415", + "Head and Neck Squamous Cell Carcinoma | ACH-000472", + "Head and Neck Squamous Cell Carcinoma | ACH-000500", + "Head and Neck Squamous Cell Carcinoma | ACH-000503", + "Head and Neck Squamous Cell Carcinoma | ACH-000518", + "Head and Neck Squamous Cell Carcinoma | ACH-000546", + "Head and Neck Squamous Cell Carcinoma | ACH-000548", + "Head and Neck Squamous Cell Carcinoma | ACH-000549", + "Head and Neck Squamous Cell Carcinoma | ACH-000606", + "Head and Neck Squamous Cell Carcinoma | ACH-000618", + "Head and Neck Squamous Cell Carcinoma | ACH-000619", + "Head and Neck Squamous Cell Carcinoma | ACH-000630", + "Head and Neck Squamous Cell Carcinoma | ACH-000682", + "Head and Neck Squamous Cell Carcinoma | ACH-000732", + "Head and Neck Squamous Cell Carcinoma | ACH-000735", + "Head and Neck Squamous Cell Carcinoma | ACH-000740", + "Head and Neck Squamous Cell Carcinoma | ACH-000762", + "Head and Neck Squamous Cell Carcinoma | ACH-000771", + "Head and Neck Squamous Cell Carcinoma | ACH-000778", + "Head and Neck Squamous Cell Carcinoma | ACH-000794", + "Head and Neck Squamous Cell Carcinoma | ACH-000832", + "Head and Neck Squamous Cell Carcinoma | ACH-000836", + "Head and Neck Squamous Cell Carcinoma | ACH-000846", + "Head and Neck Squamous Cell Carcinoma | ACH-001228", + "Head and Neck Squamous Cell Carcinoma | ACH-001229", + "Head and Neck Squamous Cell Carcinoma | ACH-001331", + "Head and Neck Squamous Cell Carcinoma | ACH-001332", + "Head and Neck Squamous Cell Carcinoma | ACH-001346", + "Head and Neck Squamous Cell Carcinoma | ACH-001347", + "Head and Neck Squamous Cell Carcinoma | ACH-001385", + "Head and Neck Squamous Cell Carcinoma | ACH-001509", + "Head and Neck Squamous Cell Carcinoma | ACH-001510", + "Head and Neck Squamous Cell Carcinoma | ACH-001511", + "Head and Neck Squamous Cell Carcinoma | ACH-001542", + "Head and Neck Squamous Cell Carcinoma | ACH-001543", + "Head and Neck Squamous Cell Carcinoma | ACH-001625", + "Head and Neck Squamous Cell Carcinoma | ACH-001626", + "Head and Neck Squamous Cell Carcinoma | ACH-001641", + "Head and Neck Squamous Cell Carcinoma | ACH-001675", + "Head and Neck Squamous Cell Carcinoma | ACH-001690", + "Head and Neck Squamous Cell Carcinoma | ACH-001691", + "Head and Neck Squamous Cell Carcinoma | ACH-001692", + "Head and Neck Squamous Cell Carcinoma | ACH-001694", + "Head and Neck Squamous Cell Carcinoma | ACH-001695", + "Head and Neck Squamous Cell Carcinoma | ACH-001696", + "Head and Neck Squamous Cell Carcinoma | ACH-001698", + "Head and Neck Squamous Cell Carcinoma | ACH-001699", + "Head and Neck Squamous Cell Carcinoma | ACH-001701", + "Head and Neck Squamous Cell Carcinoma | ACH-002029", + "Head and Neck Squamous Cell Carcinoma | ACH-002030", + "Head and Neck Squamous Cell Carcinoma | ACH-002042", + "Head and Neck Squamous Cell Carcinoma | ACH-002043", + "Head and Neck Squamous Cell Carcinoma | ACH-002044", + "Head and Neck Squamous Cell Carcinoma | ACH-002045", + "Head and Neck Squamous Cell Carcinoma | ACH-002212", + "Head and Neck Squamous Cell Carcinoma | ACH-002249", + "Head and Neck Squamous Cell Carcinoma | ACH-002250", + "Head and Neck Squamous Cell Carcinoma | ACH-002251", + "Head and Neck Squamous Cell Carcinoma | ACH-002265", + "Head and Neck Squamous Cell Carcinoma | ACH-002294", + "Head and Neck Squamous Cell Carcinoma | ACH-002295", + "Head and Neck Squamous Cell Carcinoma | ACH-002296", + "Head and Neck Squamous Cell Carcinoma | ACH-002297", + "Head and Neck Squamous Cell Carcinoma | ACH-002298", + "Head and Neck Squamous Cell Carcinoma | ACH-002305" + ], + "type": "scattergl", + "x": { + "bdata": "IlGvvfQ1rj/+Wb4/CczywC3o8sDUZmg/Fc/ywNEWkL8miAq/gLzywGasUEBEnixAWAGtv2w/8j+UJCZA63GiQIxzOEBWUhFAuCM8QB6qiD8oYVA/biaNP3cUQD8GvfLAjmXHv2QIBEATP6lAaVzUP4N3dEB7Kay/Ir0FQHDX8sBG1PLAd6DTP/Zj4T/pHsFAiDIYv4mo0T89dJi/E8WIQOim4D9Z8h7AReAgwDTR8sCmq8M/wLBMQP6TZL6D24ZA7bUoQNzz3T/Olt0/WO3fP1LDr0DlxilAERaaQFm9WkDcLt6/dAYmQAUmw0AugRdA0crywJVHQUAtz5Y/7nsMQKnM8sAlGvA/7RfwvQ99o0A2/UBAYQNrQOfe8sA=", + "dtype": "f4" + }, + "y": { + "bdata": 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ACH-002041" + ], + "type": "scattergl", + "x": { + "bdata": "Jcs/P0u0kz+XX2K/r5sPwM9wZsACtIc9nYvUvg==", + "dtype": "f4" + }, + "y": { + "bdata": "HsMGQOEBA0BZpnZA/JHSP1cDWj8AVPA/VXRpQA==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000182", + "ACH-000377", + "ACH-001862", + "ACH-002023" + ], + "hoverinfo": "text", + "marker": { + "color": "#E48F72", + "size": 7 + }, + "mode": "markers", + "name": "Ampullary Carcinoma", + "text": [ + "Ampullary Carcinoma | ACH-000182", + "Ampullary Carcinoma | ACH-000377", + "Ampullary Carcinoma | ACH-001862", + "Ampullary Carcinoma | ACH-002023" + ], + "type": "scattergl", + "x": { + "bdata": "4szywHC08sArakG/uNjiPw==", + "dtype": "f4" + }, + "y": { + "bdata": "Ceuqv1E3q7+AyuM+Zu6Dvw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000187", + "ACH-000257", + "ACH-000290", + "ACH-000292", + "ACH-000355", + "ACH-000431", + "ACH-000514", + "ACH-000515", + "ACH-000525", + "ACH-000559", + "ACH-000639", + "ACH-000695", + "ACH-000698", + "ACH-000749", + "ACH-000767", + "ACH-000775", + "ACH-000790", + "ACH-000800", + "ACH-000866", + "ACH-000871", + "ACH-000890", + "ACH-000912", + "ACH-001386", + "ACH-001549", + "ACH-002051", + "ACH-002052", + "ACH-002077" + ], + "hoverinfo": "text", + "marker": { + "color": "#2E91E5", + "size": 7 + }, + "mode": "markers", + "name": "Lung Neuroendocrine Tumor", + "text": [ + "Lung Neuroendocrine Tumor | ACH-000187", + "Lung Neuroendocrine Tumor | ACH-000257", + "Lung Neuroendocrine Tumor | ACH-000290", + "Lung Neuroendocrine Tumor | ACH-000292", + "Lung Neuroendocrine Tumor | ACH-000355", + "Lung Neuroendocrine Tumor | ACH-000431", + "Lung Neuroendocrine Tumor | ACH-000514", + "Lung Neuroendocrine Tumor | ACH-000515", + "Lung Neuroendocrine Tumor | ACH-000525", + "Lung Neuroendocrine Tumor | ACH-000559", + "Lung Neuroendocrine Tumor | ACH-000639", + "Lung Neuroendocrine Tumor | ACH-000695", + "Lung Neuroendocrine Tumor | ACH-000698", + "Lung Neuroendocrine Tumor | ACH-000749", + "Lung Neuroendocrine Tumor | ACH-000767", + "Lung Neuroendocrine Tumor | ACH-000775", + "Lung Neuroendocrine Tumor | ACH-000790", + "Lung Neuroendocrine Tumor | ACH-000800", + "Lung Neuroendocrine Tumor | ACH-000866", + "Lung Neuroendocrine Tumor | ACH-000871", + "Lung Neuroendocrine Tumor | ACH-000890", + "Lung Neuroendocrine Tumor | ACH-000912", + "Lung Neuroendocrine Tumor | ACH-001386", + "Lung Neuroendocrine Tumor | ACH-001549", + "Lung Neuroendocrine Tumor | ACH-002051", + "Lung Neuroendocrine Tumor | ACH-002052", + "Lung Neuroendocrine Tumor | ACH-002077" + ], + "type": "scattergl", + "x": { + "bdata": "uHgBQAA+jr25G9s/tuWaQBpOk0BCgcM+JtRXv3mmDECGrrc/IOyMvxmujEDMhaO/eYg2QEhLLEDDtoS/S00RQOwqP0D1SdI/T2iUQGJriUCh/FK/rjcYQMKIzj6R3zE/vd0ewNk42L50XLe/", + "dtype": "f4" + }, + "y": { + "bdata": "2GMzwLV+lr8WegjA9hkIP+jXQb9Q0ia/0HCvvx2Utr8ybai/ljV2v/K0Q8CgKEm/OjIswHEVb77S1dm/n1qwvnGvzb+q0pc/qrHdvw+Bo7/PY0JASD81PwcNr7/nd6S/lxyhv3Xs0L/LuB2/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000192", + "ACH-000293", + "ACH-000302", + "ACH-000397", + "ACH-000407", + "ACH-000435", + "ACH-000831", + "ACH-000864", + "ACH-000879", + "ACH-000928", + "ACH-000941", + "ACH-000946", + "ACH-000961", + "ACH-000965", + "ACH-000972", + "ACH-000974", + "ACH-000978", + "ACH-000984", + "ACH-000988", + "ACH-000993", + "ACH-000994", + "ACH-000996", + "ACH-001495", + "ACH-001517", + "ACH-001518", + "ACH-002026", + "ACH-002027", + "ACH-002046" + ], + "hoverinfo": "text", + "marker": { + "color": "#E15F99", + "size": 7 + }, + "mode": "markers", + "name": "Endometrial Carcinoma", + "text": [ + "Endometrial Carcinoma | ACH-000192", + "Endometrial Carcinoma | ACH-000293", + "Endometrial Carcinoma | ACH-000302", + "Endometrial Carcinoma | ACH-000397", + "Endometrial Carcinoma | ACH-000407", + "Endometrial Carcinoma | ACH-000435", + "Endometrial Carcinoma | ACH-000831", + "Endometrial Carcinoma | ACH-000864", + "Endometrial Carcinoma | ACH-000879", + "Endometrial Carcinoma | ACH-000928", + "Endometrial Carcinoma | ACH-000941", + "Endometrial Carcinoma | ACH-000946", + "Endometrial Carcinoma | ACH-000961", + "Endometrial Carcinoma | ACH-000965", + "Endometrial Carcinoma | ACH-000972", + "Endometrial Carcinoma | ACH-000974", + "Endometrial Carcinoma | ACH-000978", + "Endometrial Carcinoma | ACH-000984", + "Endometrial Carcinoma | ACH-000988", + "Endometrial Carcinoma | ACH-000993", + "Endometrial Carcinoma | ACH-000994", + "Endometrial Carcinoma | ACH-000996", + "Endometrial Carcinoma | ACH-001495", + "Endometrial Carcinoma | ACH-001517", + "Endometrial Carcinoma | ACH-001518", + "Endometrial Carcinoma | ACH-002026", + "Endometrial Carcinoma | ACH-002027", + "Endometrial Carcinoma | ACH-002046" + ], + "type": "scattergl", + "x": { + "bdata": "ZTcuwCzRLsDBcVu8TuEAv6aAtT6YD3W/drbywG21EEDZ3V5AYZFaQApj+L+P3RtA+REyQJp7sUCL2PLA+pRWQPJwzT7YVuW/uXrFve9fMT6uyPLAnf2dviX/wr8mBHHAIuHywKrySUDSLbQ/gCDwvg==", + "dtype": "f4" + }, + "y": { + "bdata": 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ACH-001538", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001673", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001834", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001835", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001836", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001838", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001839", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001841", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001842", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001843", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001844", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001848", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001849", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001852", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001856", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001857", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001858", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001863", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001864", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001959", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001960", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001997", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-002647" + ], + "type": "scattergl", + "x": { + "bdata": "ZMDywAfM8sBKwvLADe+SvmLwqz4XkTI/RcdRPxyIZ0Dx4fLAmN7ywJ3W8sBY2PLABdTywD7H8sAkF9C+I9TywCbF8sC20PLA4dDywE4jjEBZWJc/X6zxP2OY5j/Lz/LAeBorP/twtEDSSwZADKvywBTK8j8=", + "dtype": "f4" + }, + "y": { + "bdata": "s1qrv2/Xqr+SB6u/GzU/P067pj/+rilAUp4iQGwmJcCdZKq/KLaqv6b7qr+V7aq/cwqrv08Aq79vQg5A4CurvzmHq7/Za6u/swerv9PDxz6JI+Y/7ATPPddm1z1Zuqq/leADvndMBb91KwRAjLWrv41Kxj8=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000217", + "ACH-000221", + "ACH-000316", + "ACH-000361", + 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Carcinoma | ACH-000493", + "Hepatocellular Carcinoma | ACH-000537", + "Hepatocellular Carcinoma | ACH-000577", + "Hepatocellular Carcinoma | ACH-000620", + "Hepatocellular Carcinoma | ACH-000734", + "Hepatocellular Carcinoma | ACH-000848", + "Hepatocellular Carcinoma | ACH-001318", + "Hepatocellular Carcinoma | ACH-002523" + ], + "type": "scattergl", + "x": { + "bdata": "C8IYQLSbnEDLQwM/r8ouP+Q1TcCdpbq/DVD+P7pqHj4X2yxANUxjv0J6rb/+zlVAXTfFv25pzD3xjsU/7iBvwPY/4T8dmIlAexSEQA6oE0Bx5sM/", + "dtype": "f4" + }, + "y": { + "bdata": "+cqaPv8JDr9wwItAC26nP0F4U0AfMS9AdtCGQP6lSEDZxE0+olJoP7t6OkAF5ck/AaBSQDY4N0D/ygJAuZ4eQCMOyzviuRK/DDxpv71zDD/7PpdA", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000305", + "ACH-000318", + "ACH-000408", + "ACH-000452", + "ACH-000488", + "ACH-000544", + "ACH-000561", + "ACH-000605", + "ACH-000637", + "ACH-000647", + "ACH-000693", + "ACH-000694", + "ACH-000717", + "ACH-000777", + "ACH-000784", + "ACH-000809", + "ACH-000823", + "ACH-000824", + "ACH-000855", + 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Squamous Cell Carcinoma | ACH-000784", + "Esophageal Squamous Cell Carcinoma | ACH-000809", + "Esophageal Squamous Cell Carcinoma | ACH-000823", + "Esophageal Squamous Cell Carcinoma | ACH-000824", + "Esophageal Squamous Cell Carcinoma | ACH-000855", + "Esophageal Squamous Cell Carcinoma | ACH-000865", + "Esophageal Squamous Cell Carcinoma | ACH-000873", + "Esophageal Squamous Cell Carcinoma | ACH-000917", + "Esophageal Squamous Cell Carcinoma | ACH-002243", + "Esophageal Squamous Cell Carcinoma | ACH-002263" + ], + "type": "scattergl", + "x": { + "bdata": "ApApP+4tBEA2dR1A6dCDvErrtEDU7yxAeWvtP8TxlT+nhmM+eqbqviH4sEA8uShAkQIsPCHEF0ASU1pARmB7QEn/VkA62qs/VtxSQEpAPUA7GURAE9Y+QD/G9D8/4CJA", + "dtype": "f4" + }, + "y": { + "bdata": "mT2SPxgRJj+bFio/Yj31P5jeLb9vaaw/NxiGvbg1oD+0YQxAX34GP5Z9sz6CQk0/XYjcP+1QYj8JJBI/TxfQvqSHD70Yrak/KBlHP16K9T9/oBa/E4ghv5xF4j9DLd6+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000456" + ], + "hoverinfo": "text", + "marker": { + "color": "#B68100", + "size": 7 + }, + "mode": "markers", + "name": "Poorly Differentiated Thyroid Cancer", + "text": [ + "Poorly Differentiated Thyroid Cancer | ACH-000456" + ], + "type": "scattergl", + "x": { + "bdata": "nIl3QA==", + "dtype": "f4" + }, + "y": { + "bdata": "2VjDPw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000487" + ], + "hoverinfo": "text", + "marker": { + "color": "#750D86", + "size": 7 + }, + "mode": "markers", + "name": "Myelodysplastic Syndromes", + "text": [ + "Myelodysplastic Syndromes | ACH-000487" + ], + "type": "scattergl", + "x": { + "bdata": "rGq5QA==", + "dtype": "f4" + }, + "y": { + "bdata": "BrWFwA==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000490", + "ACH-000556", + "ACH-001333", + "ACH-001334", + "ACH-001335", + "ACH-001336", + "ACH-001360", + "ACH-001402", + "ACH-001451", + "ACH-001515", + "ACH-001651", + "ACH-001652", + "ACH-002020" + ], + "hoverinfo": "text", + "marker": { + "color": "#EB663B", + "size": 7 + }, + "mode": "markers", + "name": "Cervical Squamous Cell Carcinoma", + "text": [ + "Cervical Squamous Cell Carcinoma | ACH-000490", + "Cervical Squamous Cell Carcinoma | ACH-000556", + "Cervical Squamous Cell Carcinoma | ACH-001333", + "Cervical Squamous Cell Carcinoma | ACH-001334", + "Cervical Squamous Cell Carcinoma | ACH-001335", + "Cervical Squamous Cell Carcinoma | ACH-001336", + "Cervical Squamous Cell Carcinoma | ACH-001360", + "Cervical Squamous Cell Carcinoma | ACH-001402", + "Cervical Squamous Cell Carcinoma | ACH-001451", + "Cervical Squamous Cell Carcinoma | ACH-001515", + "Cervical Squamous Cell Carcinoma | ACH-001651", + "Cervical Squamous Cell Carcinoma | ACH-001652", + "Cervical Squamous Cell Carcinoma | ACH-002020" + ], + "type": "scattergl", + "x": { + "bdata": "B5f2P2pOGT+EsDxATgaiQCSpDEBchKc/GaKtwDv4jkC20fLAii1XPgVSicCURY4/l5ESvg==", + "dtype": "f4" + }, + "y": { + "bdata": "/tQJQBUDUr9ZPTA/43edv3antj7vgIU/8cQjPZvjnb+gFqu/qgDYvrDJEr9TNcI/Ay7KPQ==", + "dtype": "f4" + } + }, + { + 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7 + }, + "mode": "markers", + "name": "Hepatoblastoma", + "text": [ + "Hepatoblastoma | ACH-000671", + "Hepatoblastoma | ACH-000739" + ], + "type": "scattergl", + "x": { + "bdata": "li6PQKDngz8=", + "dtype": "f4" + }, + "y": { + "bdata": "UBloPzV9XL0=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000702", + "ACH-000754", + "ACH-001685" + ], + "hoverinfo": "text", + "marker": { + "color": "#FC0080", + "size": 7 + }, + "mode": "markers", + "name": "Hodgkin Lymphoma", + "text": [ + "Hodgkin Lymphoma | ACH-000702", + "Hodgkin Lymphoma | ACH-000754", + "Hodgkin Lymphoma | ACH-001685" + ], + "type": "scattergl", + "x": { + "bdata": "2a2yPvcujD+LipC/", + "dtype": "f4" + }, + "y": { + "bdata": "Icz9v9uCN8A6VBbA", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000716", + "ACH-000903", + "ACH-001528" + ], + "hoverinfo": "text", + "marker": { + "color": "#B2828D", + "size": 7 + }, + "mode": "markers", + "name": "Well-Differentiated Thyroid Cancer", + "text": [ + 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ACH-001279", + "Ovarian Epithelial Tumor | ACH-001340", + "Ovarian Epithelial Tumor | ACH-001370", + "Ovarian Epithelial Tumor | ACH-001403", + "Ovarian Epithelial Tumor | ACH-001418", + "Ovarian Epithelial Tumor | ACH-001628", + "Ovarian Epithelial Tumor | ACH-001630", + "Ovarian Epithelial Tumor | ACH-001632", + "Ovarian Epithelial Tumor | ACH-001719", + "Ovarian Epithelial Tumor | ACH-001991", + "Ovarian Epithelial Tumor | ACH-002140", + "Ovarian Epithelial Tumor | ACH-002181", + "Ovarian Epithelial Tumor | ACH-002183", + "Ovarian Epithelial Tumor | ACH-002486", + "Ovarian Epithelial Tumor | ACH-002524" + ], + "type": "scattergl", + "x": { + "bdata": "g5SPPYArWj+gudY/1jelvT6A2T5ba8Q/2qRVPgnTEr+HAzzAalU5wGyEEz/R0Yw+6zkAv+1vGj/EPrw/QxlwP1iZMz2PjDXAP2A3PxdHM8DIkUo/hs5AwHBaOL8r4izAVf4qPqKV4r+Xipc/Sg0wv3n3Lz+lS5M+iz2lvQuhBr6zHIi/91neP7B+uz/GJCk/oh8QQJe1eD/PDjc/IGI3wI5uNcBQeHM/2u+SPkZeL8Dzarg/0r8ywGNxNcDxtDrAc1gIP1JBNcAdDC/Amf03wHZGOMCuGt4/gakzwKsnNMDqFzLAoaSWP4Dm+j4=", + "dtype": "f4" + 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"Acute Myeloid Leukemia | ACH-000005", + "Acute Myeloid Leukemia | ACH-000045", + "Acute Myeloid Leukemia | ACH-000113", + "Acute Myeloid Leukemia | ACH-000146", + "Acute Myeloid Leukemia | ACH-000168", + "Acute Myeloid Leukemia | ACH-000190", + "Acute Myeloid Leukemia | ACH-000195", + "Acute Myeloid Leukemia | ACH-000263", + "Acute Myeloid Leukemia | ACH-000294", + "Acute Myeloid Leukemia | ACH-000336", + "Acute Myeloid Leukemia | ACH-000362", + "Acute Myeloid Leukemia | ACH-000387", + "Acute Myeloid Leukemia | ACH-000406", + "Acute Myeloid Leukemia | ACH-000498", + "Acute Myeloid Leukemia | ACH-000557", + "Acute Myeloid Leukemia | ACH-000602", + "Acute Myeloid Leukemia | ACH-000770", + "Acute Myeloid Leukemia | ACH-001036", + "Acute Myeloid Leukemia | ACH-001129", + "Acute Myeloid Leukemia | ACH-001574", + "Acute Myeloid Leukemia | ACH-001577", + "Acute Myeloid Leukemia | ACH-001613", + "Acute Myeloid Leukemia | ACH-001618", + "Acute Myeloid Leukemia | ACH-001647", + "Acute Myeloid Leukemia | ACH-001656" + ], + "type": "scattergl", + "x": { + "bdata": "+rUtP7CYfz5NbAJAteo1QOzUmz4B0Y0+5V1pP/Gv5D5HgAA9LuCBP36kG0DGEPo/fyxAP3IIBUABT0c+xvPLvrMdaT/0gtQ/sLqMP+z03j3cfgFAwiVjP4xd1T9NRpA/p8zGP66bvj8=", + "dtype": "f4" + }, + "y": { + "bdata": "fSqVvoqDgj4Dgpy/juD3v1/Pzj1XiaI+4ZrAvd0ht7yWIi0/lm4VvyHyxL+S/MC/SSGivmv4s7/snhI/AwyDP6EKuL4dhI6/Ze8Bv2mSGT877p+/GyJAvgI7YL/braG+3WqFv/SBYr8=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000007", + "ACH-000009", + "ACH-000202", + "ACH-000249", + "ACH-000252", + "ACH-000253", + "ACH-000286", + "ACH-000296", + "ACH-000350", + "ACH-000381", + "ACH-000403", + "ACH-000421", + "ACH-000467", + "ACH-000470", + "ACH-000489", + "ACH-000491", + "ACH-000501", + "ACH-000532", + "ACH-000552", + "ACH-000565", + "ACH-000651", + "ACH-000683", + "ACH-000722", + "ACH-000798", + "ACH-000820", + "ACH-000926", + "ACH-000935", + "ACH-000943", + "ACH-000950", + "ACH-000957", + "ACH-000958", + "ACH-000959", + "ACH-000963", + "ACH-000969", + "ACH-000970", + "ACH-000971", + "ACH-000985", + "ACH-000986", + "ACH-000991", + "ACH-000997", + "ACH-001039", + "ACH-001061", + "ACH-001081", + "ACH-001345", + "ACH-001399", + "ACH-001454", + "ACH-001458", + "ACH-001459", + "ACH-001460", + "ACH-001461", + "ACH-001786", + "ACH-002024", + "ACH-002025", + "ACH-002233", + "ACH-002535", + "ACH-002654", + "ACH-002659", + "ACH-002660", + "ACH-002662", + "ACH-002664", + "ACH-002669" + ], + "hoverinfo": "text", + "marker": { + "color": "#00CC96", + "size": 7 + }, + "mode": "markers", + "name": "Colorectal Adenocarcinoma", + "text": [ + "Colorectal Adenocarcinoma | ACH-000007", + "Colorectal Adenocarcinoma | ACH-000009", + "Colorectal Adenocarcinoma | ACH-000202", + "Colorectal Adenocarcinoma | ACH-000249", + "Colorectal Adenocarcinoma | ACH-000252", + "Colorectal Adenocarcinoma | ACH-000253", + "Colorectal Adenocarcinoma | ACH-000286", + "Colorectal Adenocarcinoma | ACH-000296", + "Colorectal Adenocarcinoma | ACH-000350", + "Colorectal Adenocarcinoma | ACH-000381", + "Colorectal Adenocarcinoma | ACH-000403", + "Colorectal Adenocarcinoma | ACH-000421", + "Colorectal Adenocarcinoma | ACH-000467", + "Colorectal Adenocarcinoma | ACH-000470", + "Colorectal Adenocarcinoma | ACH-000489", + "Colorectal Adenocarcinoma | ACH-000491", + "Colorectal Adenocarcinoma | ACH-000501", + "Colorectal Adenocarcinoma | ACH-000532", + "Colorectal Adenocarcinoma | ACH-000552", + "Colorectal Adenocarcinoma | ACH-000565", + "Colorectal Adenocarcinoma | ACH-000651", + "Colorectal Adenocarcinoma | ACH-000683", + "Colorectal Adenocarcinoma | ACH-000722", + "Colorectal Adenocarcinoma | ACH-000798", + "Colorectal Adenocarcinoma | ACH-000820", + "Colorectal Adenocarcinoma | ACH-000926", + "Colorectal Adenocarcinoma | ACH-000935", + "Colorectal Adenocarcinoma | ACH-000943", + "Colorectal Adenocarcinoma | ACH-000950", + "Colorectal Adenocarcinoma | ACH-000957", + "Colorectal Adenocarcinoma | ACH-000958", + "Colorectal Adenocarcinoma | ACH-000959", + "Colorectal Adenocarcinoma | ACH-000963", + "Colorectal Adenocarcinoma | ACH-000969", + "Colorectal Adenocarcinoma | ACH-000970", + "Colorectal Adenocarcinoma | ACH-000971", + "Colorectal Adenocarcinoma | ACH-000985", + "Colorectal Adenocarcinoma | ACH-000986", + "Colorectal Adenocarcinoma | ACH-000991", + "Colorectal Adenocarcinoma | ACH-000997", + "Colorectal Adenocarcinoma | ACH-001039", + "Colorectal Adenocarcinoma | ACH-001061", + "Colorectal Adenocarcinoma | ACH-001081", + "Colorectal Adenocarcinoma | ACH-001345", + "Colorectal Adenocarcinoma | ACH-001399", + "Colorectal Adenocarcinoma | ACH-001454", + "Colorectal Adenocarcinoma | ACH-001458", + "Colorectal Adenocarcinoma | ACH-001459", + "Colorectal Adenocarcinoma | ACH-001460", + "Colorectal Adenocarcinoma | ACH-001461", + "Colorectal Adenocarcinoma | ACH-001786", + "Colorectal Adenocarcinoma | ACH-002024", + "Colorectal Adenocarcinoma | ACH-002025", + "Colorectal Adenocarcinoma | ACH-002233", + "Colorectal Adenocarcinoma | ACH-002535", + "Colorectal Adenocarcinoma | ACH-002654", + "Colorectal Adenocarcinoma | ACH-002659", + "Colorectal Adenocarcinoma | ACH-002660", + "Colorectal Adenocarcinoma | ACH-002662", + "Colorectal Adenocarcinoma | ACH-002664", + "Colorectal Adenocarcinoma | ACH-002669" + ], + "type": "scattergl", + "x": { + "bdata": "PymxP45Yoz4BxwM/+201wGAqhj7ijvY+bYa7PnhHzT42tje/GhldP3uN1b6scWO+6iEywOTrkr7E8pc+ucK/PBi9LL71Hrs+WTVAP4WQBz+njIs/vx4uvmFcWj+Q5DXA6R1VPpc7NsCDETLA+EQowPHLnj/msLA/tzE3P5gddT9pEAS/fCk1wIRqBT8dDgA/u+EQP4yBMMA/+s8+T5+qPwnFgj9ZgN0/ISs4wNjFiz+9cdo+2CUGvwKQ8D6RKPs+fDmjP6ATPr81wMy8TwDPPuztMMDLObw+4EHJPoJMmb2/xKA/lYO0Psb+pD8FHWY/po1qPw==", + "dtype": "f4" + }, + "y": { + "bdata": 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Carcinoma", + "text": [ + "Bladder Urothelial Carcinoma | ACH-000011", + "Bladder Urothelial Carcinoma | ACH-000018", + "Bladder Urothelial Carcinoma | ACH-000026", + "Bladder Urothelial Carcinoma | ACH-000127", + "Bladder Urothelial Carcinoma | ACH-000142", + "Bladder Urothelial Carcinoma | ACH-000242", + "Bladder Urothelial Carcinoma | ACH-000396", + "Bladder Urothelial Carcinoma | ACH-000473", + "Bladder Urothelial Carcinoma | ACH-000486", + "Bladder Urothelial Carcinoma | ACH-000522", + "Bladder Urothelial Carcinoma | ACH-000545", + "Bladder Urothelial Carcinoma | ACH-000547", + "Bladder Urothelial Carcinoma | ACH-000593", + "Bladder Urothelial Carcinoma | ACH-000720", + "Bladder Urothelial Carcinoma | ACH-000724", + "Bladder Urothelial Carcinoma | ACH-000741", + "Bladder Urothelial Carcinoma | ACH-000753", + "Bladder Urothelial Carcinoma | ACH-000802", + "Bladder Urothelial Carcinoma | ACH-000834", + "Bladder Urothelial Carcinoma | ACH-000862", + "Bladder Urothelial Carcinoma | ACH-000896", + "Bladder Urothelial Carcinoma | ACH-000905", + "Bladder Urothelial Carcinoma | ACH-001183", + "Bladder Urothelial Carcinoma | ACH-001407", + "Bladder Urothelial Carcinoma | ACH-001409", + "Bladder Urothelial Carcinoma | ACH-001412", + "Bladder Urothelial Carcinoma | ACH-001413", + "Bladder Urothelial Carcinoma | ACH-001414", + "Bladder Urothelial Carcinoma | ACH-001415", + "Bladder Urothelial Carcinoma | ACH-001416" + ], + "type": "scattergl", + "x": { + "bdata": "a2SrPrsmbT434gA/Qaa4P1Xo/D4Llu8+CH/EvjAUNcCJSoQ/qZ0xwDF4NMARPDg/xVvqPuCvGz8/dia/19TnPp5AqT+pI4E/LESYP1jkNsB/cws/wgE8P8iyMsDVYDDAB1Y4wDj+OMB5/TTAWjQxwFA5PMCxYjjA", + "dtype": "f4" + }, + "y": { + "bdata": "b7urPpHvAT/Xy4k+JvUqv/EiTj4zFbQ+qLeXPzyRQL9XeIi+DA1jv4KJS79VsTk+JwS+PkJSXj7bj60/AvspPqV3Br+9eyS+icPhvtheKL/TSyw+/WKyO/p0Yb+cn4O/4Tkcv+jiCb/SOUG/1sd5v+zryr53hxu/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000012", + "ACH-000015", + "ACH-000021", + "ACH-000029", + "ACH-000030", + "ACH-000035", + "ACH-000143", + "ACH-000161", + "ACH-000176", + "ACH-000251", + "ACH-000261", + "ACH-000264", + "ACH-000311", + "ACH-000337", + "ACH-000339", + "ACH-000343", + "ACH-000378", + "ACH-000390", + "ACH-000395", + "ACH-000414", + "ACH-000416", + "ACH-000434", + "ACH-000438", + "ACH-000442", + "ACH-000444", + "ACH-000448", + "ACH-000454", + "ACH-000463", + "ACH-000481", + "ACH-000496", + "ACH-000510", + "ACH-000511", + "ACH-000521", + "ACH-000528", + "ACH-000562", + "ACH-000563", + "ACH-000585", + "ACH-000587", + "ACH-000589", + "ACH-000596", + "ACH-000627", + "ACH-000638", + "ACH-000662", + "ACH-000665", + "ACH-000666", + "ACH-000667", + "ACH-000672", + "ACH-000677", + "ACH-000681", + "ACH-000700", + "ACH-000706", + "ACH-000718", + "ACH-000747", + "ACH-000757", + "ACH-000766", + "ACH-000769", + "ACH-000774", + "ACH-000781", + "ACH-000785", + "ACH-000787", + "ACH-000791", + "ACH-000826", + "ACH-000837", + "ACH-000840", + "ACH-000841", + "ACH-000843", + "ACH-000845", + "ACH-000851", + "ACH-000853", + "ACH-000858", + "ACH-000860", + "ACH-000861", + "ACH-000867", + "ACH-000869", + "ACH-000872", + "ACH-000878", + "ACH-000886", + "ACH-000888", + "ACH-000894", + "ACH-000900", + "ACH-000901", + "ACH-000916", + "ACH-000921", + "ACH-000924", + "ACH-000929", + "ACH-000945", + "ACH-000975", + "ACH-000980", + "ACH-001075", + "ACH-001137", + "ACH-001233", + "ACH-002035", + "ACH-002156", + "ACH-002522", + "ACH-002526", + "ACH-002531", + "ACH-002650", + "ACH-003012" + ], + "hoverinfo": "text", + "marker": { + "color": "#FFA15A", + "size": 7 + }, + "mode": "markers", + "name": "Non-Small Cell Lung Cancer", + "text": [ + "Non-Small Cell Lung Cancer | ACH-000012", + "Non-Small Cell Lung Cancer | ACH-000015", + "Non-Small Cell Lung Cancer | ACH-000021", + "Non-Small Cell Lung Cancer | ACH-000029", + "Non-Small Cell Lung Cancer | ACH-000030", + "Non-Small Cell Lung Cancer | ACH-000035", + "Non-Small Cell Lung Cancer | ACH-000143", + "Non-Small Cell Lung Cancer | ACH-000161", + "Non-Small Cell Lung Cancer | ACH-000176", + "Non-Small Cell Lung Cancer | ACH-000251", + "Non-Small Cell Lung Cancer | ACH-000261", + "Non-Small Cell Lung Cancer | ACH-000264", + "Non-Small Cell Lung Cancer | ACH-000311", + "Non-Small Cell Lung Cancer | ACH-000337", + "Non-Small Cell Lung Cancer | ACH-000339", + "Non-Small Cell Lung Cancer | ACH-000343", + "Non-Small Cell Lung Cancer | ACH-000378", + "Non-Small Cell Lung Cancer | ACH-000390", + "Non-Small Cell Lung Cancer | ACH-000395", + "Non-Small Cell Lung Cancer | ACH-000414", + "Non-Small Cell Lung Cancer | ACH-000416", + "Non-Small Cell Lung Cancer | ACH-000434", + "Non-Small Cell Lung Cancer | ACH-000438", + "Non-Small Cell Lung Cancer | ACH-000442", + "Non-Small Cell Lung Cancer | ACH-000444", + "Non-Small Cell Lung Cancer | ACH-000448", + "Non-Small Cell Lung Cancer | ACH-000454", + "Non-Small Cell Lung Cancer | ACH-000463", + "Non-Small Cell Lung Cancer | ACH-000481", + "Non-Small Cell Lung Cancer | ACH-000496", + "Non-Small Cell Lung Cancer | ACH-000510", + "Non-Small Cell Lung Cancer | ACH-000511", + "Non-Small Cell Lung Cancer | ACH-000521", + "Non-Small Cell Lung Cancer | ACH-000528", + "Non-Small Cell Lung Cancer | ACH-000562", + "Non-Small Cell Lung Cancer | ACH-000563", + "Non-Small Cell Lung Cancer | ACH-000585", + "Non-Small Cell Lung Cancer | ACH-000587", + "Non-Small Cell Lung Cancer | ACH-000589", + "Non-Small Cell Lung Cancer | ACH-000596", + "Non-Small Cell Lung Cancer | ACH-000627", + "Non-Small Cell Lung Cancer | ACH-000638", + "Non-Small Cell Lung Cancer | ACH-000662", + "Non-Small Cell Lung Cancer | ACH-000665", + "Non-Small Cell Lung Cancer | ACH-000666", + "Non-Small Cell Lung Cancer | ACH-000667", + "Non-Small Cell Lung Cancer | ACH-000672", + "Non-Small Cell Lung Cancer | ACH-000677", + "Non-Small Cell Lung Cancer | ACH-000681", + "Non-Small Cell Lung Cancer | ACH-000700", + "Non-Small Cell Lung Cancer | ACH-000706", + "Non-Small Cell Lung Cancer | ACH-000718", + "Non-Small Cell Lung Cancer | ACH-000747", + "Non-Small Cell Lung Cancer | ACH-000757", + "Non-Small Cell Lung Cancer | ACH-000766", + "Non-Small Cell Lung Cancer | ACH-000769", + "Non-Small Cell Lung Cancer | ACH-000774", + "Non-Small Cell Lung Cancer | ACH-000781", + "Non-Small Cell Lung Cancer | ACH-000785", + "Non-Small Cell Lung Cancer | ACH-000787", + "Non-Small Cell Lung Cancer | ACH-000791", + "Non-Small Cell Lung Cancer | ACH-000826", + "Non-Small Cell Lung Cancer | ACH-000837", + "Non-Small Cell Lung Cancer | ACH-000840", + "Non-Small Cell Lung Cancer | ACH-000841", + "Non-Small Cell Lung Cancer | ACH-000843", + "Non-Small Cell Lung Cancer | ACH-000845", + "Non-Small Cell Lung Cancer | ACH-000851", + "Non-Small Cell Lung Cancer | ACH-000853", + "Non-Small Cell Lung Cancer | ACH-000858", + "Non-Small Cell Lung Cancer | ACH-000860", + "Non-Small Cell Lung Cancer | ACH-000861", + "Non-Small Cell Lung Cancer | ACH-000867", + "Non-Small Cell Lung Cancer | ACH-000869", + "Non-Small Cell Lung Cancer | ACH-000872", + "Non-Small Cell Lung Cancer | ACH-000878", + "Non-Small Cell Lung Cancer | ACH-000886", + "Non-Small Cell Lung Cancer | ACH-000888", + "Non-Small Cell Lung Cancer | ACH-000894", + "Non-Small Cell Lung Cancer | ACH-000900", + "Non-Small Cell Lung Cancer | ACH-000901", + "Non-Small Cell Lung Cancer | ACH-000916", + "Non-Small Cell Lung Cancer | ACH-000921", + "Non-Small Cell Lung Cancer | ACH-000924", + "Non-Small Cell Lung Cancer | ACH-000929", + "Non-Small Cell Lung Cancer | ACH-000945", + "Non-Small Cell Lung Cancer | ACH-000975", + "Non-Small Cell Lung Cancer | ACH-000980", + "Non-Small Cell Lung Cancer | ACH-001075", + "Non-Small Cell Lung Cancer | ACH-001137", + "Non-Small Cell Lung Cancer | ACH-001233", + "Non-Small Cell Lung Cancer | ACH-002035", + "Non-Small Cell Lung Cancer | ACH-002156", + "Non-Small Cell Lung Cancer | ACH-002522", + "Non-Small Cell Lung Cancer | ACH-002526", + "Non-Small Cell Lung Cancer | ACH-002531", + "Non-Small Cell Lung Cancer | ACH-002650", + "Non-Small Cell Lung Cancer | ACH-003012" + ], + "type": "scattergl", + "x": { + "bdata": "vVWLP0CDoT9DbJ6+03NVPybWYD/BZh090sVmP56PM8BOW2q/t/PovYdGN8AjwBe/CImuPooDNsCo9/c+jJF/PopzBj/7zZq7l8s1wCHMLT+B4Rw9v20fvzIx+j2LmMw+4lQ4P4ajQr4PxWw/z6o1wPgmOsBKwro90m0pP/4p3b75lDvA8cGNPwfURj9AXV0/DD8HvpI0NMCRQYo/DDfTPtxyzj6z1kg/rr5iP+dVA7/zhRC+Y29NPyBpf74Nr60+oyB8PxQRHr65RjLAbko6wJ5VsD+GxSw+m69JvuRztD/DHj3AQc96P2tZK78imIg/sZstv2bnNMDEf4E/gD8hv1xgoz2gUp0/AOkEP53SMsAD0oY/X4pHP4KKNcApyIQ+hzmWPZuwLL/esZe9IO20vpweXz9T7RY/VhlIvtWpsT/xEwm/Ocm0videeD+rGjDAGnU3wEZbO8DClas+7F2vP9PNKz9BLgy/A3AzwC6kij/LxFE/20sbP7IRRj76v9Q9dcWxvk3NBT8=", + "dtype": "f4" + }, + "y": { + "bdata": 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"ACH-000827", + "ACH-000881", + "ACH-000882", + "ACH-000884", + "ACH-000899", + "ACH-000915", + "ACH-000968", + "ACH-001041", + "ACH-001190", + "ACH-001239", + "ACH-001522", + "ACH-001563", + "ACH-001566", + "ACH-001567", + "ACH-001568", + "ACH-001570", + "ACH-001645", + "ACH-001970", + "ACH-001972", + "ACH-001973", + "ACH-001975", + "ACH-001982", + "ACH-001986", + "ACH-001990", + "ACH-002001", + "ACH-002002", + "ACH-002003", + "ACH-002004", + "ACH-002005", + "ACH-002084", + "ACH-002143", + "ACH-002458", + "ACH-002460", + "ACH-002461", + "ACH-002508", + "ACH-002510", + "ACH-002511", + "ACH-002512", + "ACH-002847", + "ACH-002928" + ], + "hoverinfo": "text", + "marker": { + "color": "#19D3F3", + "size": 7 + }, + "mode": "markers", + "name": "Melanoma", + "text": [ + "Melanoma | ACH-000014", + "Melanoma | ACH-000219", + "Melanoma | ACH-000274", + "Melanoma | ACH-000304", + "Melanoma | ACH-000322", + "Melanoma | ACH-000348", + "Melanoma | ACH-000401", + "Melanoma | ACH-000404", + "Melanoma | ACH-000425", + "Melanoma | ACH-000441", + "Melanoma | ACH-000450", + "Melanoma | ACH-000458", + "Melanoma | ACH-000477", + "Melanoma | ACH-000550", + "Melanoma | ACH-000579", + "Melanoma | ACH-000580", + "Melanoma | ACH-000614", + "Melanoma | ACH-000632", + "Melanoma | ACH-000661", + "Melanoma | ACH-000765", + "Melanoma | ACH-000788", + "Melanoma | ACH-000799", + "Melanoma | ACH-000801", + "Melanoma | ACH-000805", + "Melanoma | ACH-000810", + "Melanoma | ACH-000822", + "Melanoma | ACH-000827", + "Melanoma | ACH-000881", + "Melanoma | ACH-000882", + "Melanoma | ACH-000884", + "Melanoma | ACH-000899", + "Melanoma | ACH-000915", + "Melanoma | ACH-000968", + "Melanoma | ACH-001041", + "Melanoma | ACH-001190", + "Melanoma | ACH-001239", + "Melanoma | ACH-001522", + "Melanoma | ACH-001563", + "Melanoma | ACH-001566", + "Melanoma | ACH-001567", + "Melanoma | ACH-001568", + "Melanoma | ACH-001570", + "Melanoma | ACH-001645", + "Melanoma | ACH-001970", + "Melanoma | ACH-001972", + "Melanoma | ACH-001973", + "Melanoma | ACH-001975", + "Melanoma | ACH-001982", + "Melanoma | ACH-001986", + "Melanoma | ACH-001990", + "Melanoma | ACH-002001", + "Melanoma | ACH-002002", + "Melanoma | ACH-002003", + "Melanoma | ACH-002004", + "Melanoma | ACH-002005", + "Melanoma | ACH-002084", + "Melanoma | ACH-002143", + "Melanoma | ACH-002458", + "Melanoma | ACH-002460", + "Melanoma | ACH-002461", + "Melanoma | ACH-002508", + "Melanoma | ACH-002510", + "Melanoma | ACH-002511", + "Melanoma | ACH-002512", + "Melanoma | ACH-002847", + "Melanoma | ACH-002928" + ], + "type": "scattergl", + "x": { + "bdata": "wIZwPwrOCUCZ4C6/IkRkPknklz+lRba+GRFjP70HM8ChWDTAD8S2P2WHMMApJDPAxRvdPQ4HLb9umDbA2HjgPZLpnj/KWE4/6rMwwLF6CD+hPgQ/agByPeDZMsD2ExU/fql2PrH1S7/AbQM/yHCfP0Djyj9SMo8/rjkwwM/cuz+22KE/q09PP06whb53SaA/iiwFP/XxM8BTXTPAdxw0wJYwNsCtMTDAkv8aPtl4PD9OxCrAOuMxwOYoLsBDp5M/ZNOyP0OEzT81d7s/pPQHQJBsQj9ekjTAj4qTP1Bahr2KFoO/GqlfP/GyWj+PEDQ9yrKcvs6dnD/lyne/WH4OPhGo5zvh/D+/", + "dtype": "f4" + }, + "y": { + "bdata": 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"ACH-001393", + "ACH-001394", + "ACH-001396", + "ACH-001419", + "ACH-001662", + "ACH-001683", + "ACH-001819", + "ACH-002179", + "ACH-002399", + "ACH-002401" + ], + "hoverinfo": "text", + "marker": { + "color": "#FF6692", + "size": 7 + }, + "mode": "markers", + "name": "Invasive Breast Carcinoma", + "text": [ + "Invasive Breast Carcinoma | ACH-000017", + "Invasive Breast Carcinoma | ACH-000019", + "Invasive Breast Carcinoma | ACH-000028", + "Invasive Breast Carcinoma | ACH-000097", + "Invasive Breast Carcinoma | ACH-000111", + "Invasive Breast Carcinoma | ACH-000147", + "Invasive Breast Carcinoma | ACH-000148", + "Invasive Breast Carcinoma | ACH-000212", + "Invasive Breast Carcinoma | ACH-000223", + "Invasive Breast Carcinoma | ACH-000248", + "Invasive Breast Carcinoma | ACH-000258", + "Invasive Breast Carcinoma | ACH-000276", + "Invasive Breast Carcinoma | ACH-000277", + "Invasive Breast Carcinoma | ACH-000288", + "Invasive Breast Carcinoma | ACH-000330", + "Invasive Breast Carcinoma | ACH-000352", + "Invasive Breast Carcinoma | ACH-000374", + "Invasive Breast Carcinoma | ACH-000554", + "Invasive Breast Carcinoma | ACH-000573", + "Invasive Breast Carcinoma | ACH-000621", + "Invasive Breast Carcinoma | ACH-000668", + "Invasive Breast Carcinoma | ACH-000699", + "Invasive Breast Carcinoma | ACH-000711", + "Invasive Breast Carcinoma | ACH-000721", + "Invasive Breast Carcinoma | ACH-000768", + "Invasive Breast Carcinoma | ACH-000783", + "Invasive Breast Carcinoma | ACH-000849", + "Invasive Breast Carcinoma | ACH-000856", + "Invasive Breast Carcinoma | ACH-000876", + "Invasive Breast Carcinoma | ACH-000910", + "Invasive Breast Carcinoma | ACH-000934", + "Invasive Breast Carcinoma | ACH-001065", + "Invasive Breast Carcinoma | ACH-001388", + "Invasive Breast Carcinoma | ACH-001389", + "Invasive Breast Carcinoma | ACH-001390", + "Invasive Breast Carcinoma | ACH-001391", + "Invasive Breast Carcinoma | ACH-001392", + "Invasive Breast Carcinoma | ACH-001393", + "Invasive Breast Carcinoma | ACH-001394", + "Invasive Breast Carcinoma | ACH-001396", + "Invasive Breast Carcinoma | ACH-001419", + "Invasive Breast Carcinoma | ACH-001662", + "Invasive Breast Carcinoma | ACH-001683", + "Invasive Breast Carcinoma | ACH-001819", + "Invasive Breast Carcinoma | ACH-002179", + "Invasive Breast Carcinoma | ACH-002399", + "Invasive Breast Carcinoma | ACH-002401" + ], + "type": "scattergl", + "x": { + "bdata": "ty4IPkG2SD8wkr8/Ryr7PkxfkD9HrpU/IPKMPqLb2T4Fr8O+ytY0P0QcMb7ZmfC9A2nIPaU9CT9dRwM/j3f1Pn+ZQD+I5xW/Au0TP5Rfg7+4vfa98V0Rv7zDQD+lpYw/NtbjPg4COb+uRZk/opENQJd7OL6hX68/WUptv2iQ5D/GtQ2/EwUxwISDFz/XVEq/CU45wIwoM8CkKDjAlWA6wIppcj4a2PO8CDtuPg4osr78rY8/dS78PqoWUj8=", + "dtype": "f4" + }, + "y": { + "bdata": "Pn1sPuZ3PLzIXkW/BV3lPYBms76TddK+pDbtPq6BCD7e5zU/fnWpvY1JPT/QlUY/rZikPsJqtj7nbsy8ZuQNO2XTj70nfpI/EuTkOwR9vj8NS1I/TsFmP8s+qr4YUuS+RFMePkBkij/VOJu+WTSav+K/Uz+AuBu/Ny/YP9ZqV79KupE/Up58v/OMmD6NHKg/2BIHv5xSYr+PRCG/j23ZvhyXpT4rOfE+mKyxPsvJJD+q0uS+/zWcPseZIL4=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000022", + "ACH-000023", + "ACH-000042", + "ACH-000060", + "ACH-000085", + "ACH-000093", + "ACH-000094", + "ACH-000114", + "ACH-000118", + "ACH-000138", + "ACH-000139", + "ACH-000155", + "ACH-000164", + "ACH-000178", + "ACH-000213", + "ACH-000222", + "ACH-000235", + "ACH-000243", + "ACH-000265", + "ACH-000266", + "ACH-000281", + "ACH-000307", + "ACH-000320", + "ACH-000332", + "ACH-000354", + "ACH-000417", + "ACH-000468", + "ACH-000502", + "ACH-000517", + "ACH-000535", + "ACH-000599", + "ACH-000601", + "ACH-000652", + "ACH-001098", + "ACH-001107", + "ACH-001353", + "ACH-001375", + "ACH-001377", + "ACH-001379", + "ACH-001380", + "ACH-001382", + "ACH-001999", + "ACH-002039", + "ACH-002186", + "ACH-002672" + ], + "hoverinfo": "text", + "marker": { + "color": "#B6E880", + "size": 7 + }, + "mode": "markers", + "name": "Pancreatic Adenocarcinoma", + "text": [ + "Pancreatic Adenocarcinoma | ACH-000022", + "Pancreatic Adenocarcinoma | ACH-000023", + "Pancreatic Adenocarcinoma | ACH-000042", + "Pancreatic Adenocarcinoma | ACH-000060", + "Pancreatic Adenocarcinoma | ACH-000085", + "Pancreatic Adenocarcinoma | ACH-000093", + "Pancreatic Adenocarcinoma | ACH-000094", + "Pancreatic Adenocarcinoma | ACH-000114", + "Pancreatic Adenocarcinoma | ACH-000118", + "Pancreatic Adenocarcinoma | ACH-000138", + "Pancreatic Adenocarcinoma | ACH-000139", + "Pancreatic Adenocarcinoma | ACH-000155", + "Pancreatic Adenocarcinoma | ACH-000164", + "Pancreatic Adenocarcinoma | ACH-000178", + "Pancreatic Adenocarcinoma | ACH-000213", + "Pancreatic Adenocarcinoma | ACH-000222", + "Pancreatic Adenocarcinoma | ACH-000235", + "Pancreatic Adenocarcinoma | ACH-000243", + "Pancreatic Adenocarcinoma | ACH-000265", + "Pancreatic Adenocarcinoma | ACH-000266", + "Pancreatic Adenocarcinoma | ACH-000281", + "Pancreatic Adenocarcinoma | ACH-000307", + "Pancreatic Adenocarcinoma | ACH-000320", + "Pancreatic Adenocarcinoma | ACH-000332", + "Pancreatic Adenocarcinoma | ACH-000354", + "Pancreatic Adenocarcinoma | ACH-000417", + "Pancreatic Adenocarcinoma | ACH-000468", + "Pancreatic Adenocarcinoma | ACH-000502", + "Pancreatic Adenocarcinoma | ACH-000517", + "Pancreatic Adenocarcinoma | ACH-000535", + "Pancreatic Adenocarcinoma | ACH-000599", + "Pancreatic Adenocarcinoma | ACH-000601", + "Pancreatic Adenocarcinoma | ACH-000652", + "Pancreatic Adenocarcinoma | ACH-001098", + "Pancreatic Adenocarcinoma | ACH-001107", + "Pancreatic Adenocarcinoma | ACH-001353", + "Pancreatic Adenocarcinoma | ACH-001375", + "Pancreatic Adenocarcinoma | ACH-001377", + "Pancreatic Adenocarcinoma | ACH-001379", + "Pancreatic Adenocarcinoma | ACH-001380", + "Pancreatic Adenocarcinoma | ACH-001382", + "Pancreatic Adenocarcinoma | ACH-001999", + "Pancreatic Adenocarcinoma | ACH-002039", + "Pancreatic Adenocarcinoma | ACH-002186", + "Pancreatic Adenocarcinoma | ACH-002672" + ], + "type": "scattergl", + "x": { + "bdata": 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"ACH-000660", + "ACH-000697", + "ACH-000714", + "ACH-000763", + "ACH-000817", + "ACH-000821", + "ACH-000829", + "ACH-000838", + "ACH-000889", + "ACH-000914", + "ACH-000944", + "ACH-001450", + "ACH-001498", + "ACH-001533", + "ACH-001539", + "ACH-001616", + "ACH-001634", + "ACH-001639", + "ACH-001677", + "ACH-001707", + "ACH-001709", + "ACH-002055", + "ACH-002062", + "ACH-002214", + "ACH-002215", + "ACH-002478", + "ACH-002485", + "ACH-002500", + "ACH-002677", + "ACH-002678" + ], + "hoverinfo": "text", + "marker": { + "color": "#FF97FF", + "size": 7 + }, + "mode": "markers", + "name": "Mature B-Cell Neoplasms", + "text": [ + "Mature B-Cell Neoplasms | ACH-000024", + "Mature B-Cell Neoplasms | ACH-000106", + "Mature B-Cell Neoplasms | ACH-000124", + "Mature B-Cell Neoplasms | ACH-000167", + "Mature B-Cell Neoplasms | ACH-000183", + "Mature B-Cell Neoplasms | ACH-000204", + "Mature B-Cell Neoplasms | ACH-000271", + "Mature B-Cell Neoplasms | ACH-000315", + "Mature B-Cell Neoplasms | ACH-000334", + "Mature B-Cell Neoplasms | ACH-000346", + "Mature B-Cell Neoplasms | ACH-000363", + "Mature B-Cell Neoplasms | ACH-000365", + "Mature B-Cell Neoplasms | ACH-000371", + "Mature B-Cell Neoplasms | ACH-000398", + "Mature B-Cell Neoplasms | ACH-000402", + "Mature B-Cell Neoplasms | ACH-000405", + "Mature B-Cell Neoplasms | ACH-000426", + "Mature B-Cell Neoplasms | ACH-000436", + "Mature B-Cell Neoplasms | ACH-000512", + "Mature B-Cell Neoplasms | ACH-000541", + "Mature B-Cell Neoplasms | ACH-000567", + "Mature B-Cell Neoplasms | ACH-000576", + "Mature B-Cell Neoplasms | ACH-000588", + "Mature B-Cell Neoplasms | ACH-000653", + "Mature B-Cell Neoplasms | ACH-000654", + "Mature B-Cell Neoplasms | ACH-000656", + "Mature B-Cell Neoplasms | ACH-000660", + "Mature B-Cell Neoplasms | ACH-000697", + "Mature B-Cell Neoplasms | ACH-000714", + "Mature B-Cell Neoplasms | ACH-000763", + "Mature B-Cell Neoplasms | ACH-000817", + "Mature B-Cell Neoplasms | ACH-000821", + "Mature B-Cell Neoplasms | ACH-000829", + "Mature B-Cell Neoplasms | ACH-000838", + "Mature B-Cell Neoplasms | ACH-000889", + "Mature B-Cell Neoplasms | ACH-000914", + "Mature B-Cell Neoplasms | ACH-000944", + "Mature B-Cell Neoplasms | ACH-001450", + "Mature B-Cell Neoplasms | ACH-001498", + "Mature B-Cell Neoplasms | ACH-001533", + "Mature B-Cell Neoplasms | ACH-001539", + "Mature B-Cell Neoplasms | ACH-001616", + "Mature B-Cell Neoplasms | ACH-001634", + "Mature B-Cell Neoplasms | ACH-001639", + "Mature B-Cell Neoplasms | ACH-001677", + "Mature B-Cell Neoplasms | ACH-001707", + "Mature B-Cell Neoplasms | ACH-001709", + "Mature B-Cell Neoplasms | ACH-002055", + "Mature B-Cell Neoplasms | ACH-002062", + "Mature B-Cell Neoplasms | ACH-002214", + "Mature B-Cell Neoplasms | ACH-002215", + "Mature B-Cell Neoplasms | ACH-002478", + "Mature B-Cell Neoplasms | ACH-002485", + "Mature B-Cell Neoplasms | ACH-002500", + "Mature B-Cell Neoplasms | ACH-002677", + "Mature B-Cell Neoplasms | ACH-002678" + ], + "type": "scattergl", + "x": { + "bdata": "NsiSPwC+Pz8hXiFABlJxP3Eq7T/SW9w/wAEzQDOXaT8lb8+9VWLKP+b6mD4RNvc/jpa5P+24oT8SvVk/qZLSPxK1kj5r8TPAToyeP3xcVj+ROC7AL+zwPrdI3z/84ow/YJ+QP87RJ0BuqyBAn+e0P16xhj9EaDE/8datP0xhTz/h4S/ApqBKPz5uAUBjWQtA2ZPRP09ozj+RT9w/3ZYwwGjeLj88OAlAn04zwNlVij9apT8/KyAzwKiWGEDihJo/73FbP1dxBkDYKbM/TdyaPxqUiT+tY/w/kr4BQMyihT8=", + "dtype": "f4" + }, + "y": { + "bdata": "nU04v2ntF7x+Wb6/1RnFvqnEvL8mYpG/ojLzv8Sm4r6b9gU/fwQyv2iwj70GBra/J1RXv9XTD79vsFq+L5iLvy7FAb6XtVi/nFQev/6UXL66OI2/rKsivv3Nnr+ZayO/yzoRv4pO0L9PWMC/DLdev6XoJb9aGq2+dYxSv1ido74nqYq/hW7qvv5avb+cScK/JX5xv/xuWb+IfYi/Jid/vyQiOr7xoNm/D7ZUvyfjOr7MuxO+DY1jv2qC3r+FuCK/vQJjvmPjp7/JZ1e/n8k3v0jHBb9J+ai/FxLDv+Sg8r4=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000025", + "ACH-001067", + "ACH-002070" + ], + "hoverinfo": "text", + "marker": { + "color": "#FECB52", + "size": 7 + }, + "mode": "markers", + "name": "Meningothelial Tumor", + "text": [ + "Meningothelial Tumor | ACH-000025", + "Meningothelial Tumor | ACH-001067", + "Meningothelial Tumor | ACH-002070" + ], + "type": "scattergl", + "x": { + "bdata": "BkN0P2IBL8BrNME+", + "dtype": "f4" + }, + "y": { + "bdata": "dSz3vbf5iL9jX7k+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000036", + "ACH-000040", + "ACH-000067", + "ACH-000075", + "ACH-000098", + "ACH-000128", + "ACH-000137", + "ACH-000152", + "ACH-000200", + "ACH-000208", + "ACH-000215", + "ACH-000231", + "ACH-000232", + "ACH-000244", + "ACH-000269", + "ACH-000273", + "ACH-000323", + "ACH-000329", + "ACH-000368", + "ACH-000370", + "ACH-000376", + "ACH-000389", + "ACH-000437", + "ACH-000445", + "ACH-000455", + "ACH-000464", + "ACH-000469", + "ACH-000479", + "ACH-000504", + "ACH-000558", + "ACH-000570", + "ACH-000571", + "ACH-000591", + "ACH-000592", + "ACH-000595", + "ACH-000609", + "ACH-000622", + "ACH-000623", + "ACH-000631", + "ACH-000634", + "ACH-000655", + "ACH-000673", + "ACH-000676", + "ACH-000738", + "ACH-000756", + "ACH-000760", + "ACH-000807", + "ACH-000819", + "ACH-000863", + "ACH-000887", + "ACH-001016", + "ACH-001126", + "ACH-001172", + "ACH-001329", + "ACH-001605", + "ACH-001606", + "ACH-001608", + "ACH-001609", + "ACH-001610", + "ACH-001611", + "ACH-001622", + "ACH-001623", + "ACH-001624", + "ACH-002228", + "ACH-002229", + "ACH-002230", + "ACH-002257", + "ACH-002269", + "ACH-002304", + "ACH-002680" + ], + "hoverinfo": "text", + "marker": { + "color": "#FD3216", + "size": 7 + }, + "mode": "markers", + "name": "Diffuse Glioma", + "text": [ + "Diffuse Glioma | ACH-000036", + "Diffuse Glioma | ACH-000040", + "Diffuse Glioma | ACH-000067", + "Diffuse Glioma | ACH-000075", + "Diffuse Glioma | ACH-000098", + "Diffuse Glioma | ACH-000128", + "Diffuse Glioma | ACH-000137", + "Diffuse Glioma | ACH-000152", + "Diffuse Glioma | ACH-000200", + "Diffuse Glioma | ACH-000208", + "Diffuse Glioma | ACH-000215", + "Diffuse Glioma | ACH-000231", + "Diffuse Glioma | ACH-000232", + "Diffuse Glioma | ACH-000244", + "Diffuse Glioma | ACH-000269", + "Diffuse Glioma | ACH-000273", + "Diffuse Glioma | ACH-000323", + "Diffuse Glioma | ACH-000329", + "Diffuse Glioma | ACH-000368", + "Diffuse Glioma | ACH-000370", + "Diffuse Glioma | ACH-000376", + "Diffuse Glioma | ACH-000389", + "Diffuse Glioma | ACH-000437", + "Diffuse Glioma | ACH-000445", + "Diffuse Glioma | ACH-000455", + "Diffuse Glioma | ACH-000464", + "Diffuse Glioma | ACH-000469", + "Diffuse Glioma | ACH-000479", + "Diffuse Glioma | ACH-000504", + "Diffuse Glioma | ACH-000558", + "Diffuse Glioma | ACH-000570", + "Diffuse Glioma | ACH-000571", + "Diffuse Glioma | ACH-000591", + "Diffuse Glioma | ACH-000592", + "Diffuse Glioma | ACH-000595", + "Diffuse Glioma | ACH-000609", + "Diffuse Glioma | ACH-000622", + "Diffuse Glioma | ACH-000623", + "Diffuse Glioma | ACH-000631", + "Diffuse Glioma | ACH-000634", + "Diffuse Glioma | ACH-000655", + "Diffuse Glioma | ACH-000673", + "Diffuse Glioma | ACH-000676", + "Diffuse Glioma | ACH-000738", + "Diffuse Glioma | ACH-000756", + "Diffuse Glioma | ACH-000760", + "Diffuse Glioma | ACH-000807", + "Diffuse Glioma | ACH-000819", + "Diffuse Glioma | ACH-000863", + "Diffuse Glioma | ACH-000887", + "Diffuse Glioma | ACH-001016", + "Diffuse Glioma | ACH-001126", + "Diffuse Glioma | ACH-001172", + "Diffuse Glioma | ACH-001329", + "Diffuse Glioma | ACH-001605", + "Diffuse Glioma | ACH-001606", + "Diffuse Glioma | ACH-001608", + "Diffuse Glioma | ACH-001609", + "Diffuse Glioma | ACH-001610", + "Diffuse Glioma | ACH-001611", + "Diffuse Glioma | ACH-001622", + "Diffuse Glioma | ACH-001623", + "Diffuse Glioma | ACH-001624", + "Diffuse Glioma | ACH-002228", + "Diffuse Glioma | ACH-002229", + "Diffuse Glioma | ACH-002230", + "Diffuse Glioma | ACH-002257", + "Diffuse Glioma | ACH-002269", + "Diffuse Glioma | ACH-002304", + "Diffuse Glioma | ACH-002680" + ], + "type": "scattergl", + "x": { + "bdata": 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[ + "Sarcoma, NOS | ACH-000037" + ], + "type": "scattergl", + "x": { + "bdata": "YKEUvw==", + "dtype": "f4" + }, + "y": { + "bdata": "DF+/Pw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000039", + "ACH-000041", + "ACH-000052", + "ACH-000087", + "ACH-000210", + "ACH-000279", + "ACH-000391", + "ACH-000424", + "ACH-000499", + "ACH-001029", + "ACH-001038", + "ACH-001192", + "ACH-001193", + "ACH-001205", + "ACH-001283", + "ACH-001430", + "ACH-001431", + "ACH-002105", + "ACH-002106", + "ACH-002109", + "ACH-002110", + "ACH-002114", + "ACH-002116", + "ACH-002119", + "ACH-002160" + ], + "hoverinfo": "text", + "marker": { + "color": "#6A76FC", + "size": 7 + }, + "mode": "markers", + "name": "Ewing Sarcoma", + "text": [ + "Ewing Sarcoma | ACH-000039", + "Ewing Sarcoma | ACH-000041", + "Ewing Sarcoma | ACH-000052", + "Ewing Sarcoma | ACH-000087", + "Ewing Sarcoma | ACH-000210", + "Ewing Sarcoma | ACH-000279", + "Ewing Sarcoma | ACH-000391", + "Ewing Sarcoma | ACH-000424", + "Ewing Sarcoma | ACH-000499", + "Ewing Sarcoma | ACH-001029", + "Ewing Sarcoma | ACH-001038", + "Ewing Sarcoma | ACH-001192", + "Ewing Sarcoma | ACH-001193", + "Ewing Sarcoma | ACH-001205", + "Ewing Sarcoma | ACH-001283", + "Ewing Sarcoma | ACH-001430", + "Ewing Sarcoma | ACH-001431", + "Ewing Sarcoma | ACH-002105", + "Ewing Sarcoma | ACH-002106", + "Ewing Sarcoma | ACH-002109", + "Ewing Sarcoma | ACH-002110", + "Ewing Sarcoma | ACH-002114", + "Ewing Sarcoma | ACH-002116", + "Ewing Sarcoma | ACH-002119", + "Ewing Sarcoma | ACH-002160" + ], + "type": "scattergl", + "x": { + "bdata": "5HyQve9fPT7rWWM+IvSFP54S8D4hQq4/A7vCPxxv8j+INpA/RBjTPx75kT+FYCY/TIzSPuAKID+2OWw/3FzoPtVdTj/netk+fujFPwDMQD/M+QBARHo1wD8pNcC+ouQ/VZDcPw==", + "dtype": "f4" + }, + "y": { + "bdata": "/ERmPwqqKz8gjiY/q2bgvaov5j4OhwK/nx10vpMNGr8AyXC+O3MgvzoEqb4/uoE+jpa9PmD2KT1J0K29hzjDPnaf5L0K2Dc/ZLUgv94Haj57XF2/cgY+v/J1Pb/Ctii/7+4Svw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000047", + "ACH-000144", + "ACH-000216", + "ACH-000239", + "ACH-000247", + "ACH-000255", + "ACH-000303", + "ACH-000325", + "ACH-000344", + "ACH-000356", + "ACH-000383", + "ACH-000427", + "ACH-000466", + "ACH-000485", + "ACH-000507", + "ACH-000581", + "ACH-000616", + "ACH-000633", + "ACH-000736", + "ACH-000746", + "ACH-000758", + "ACH-000764", + "ACH-000793", + "ACH-000847", + "ACH-000880", + "ACH-000898", + "ACH-000911", + "ACH-000919", + "ACH-000932", + "ACH-000948", + "ACH-001368", + "ACH-001496", + "ACH-001497", + "ACH-001500", + "ACH-001544", + "ACH-001653", + "ACH-001654", + "ACH-001664", + "ACH-002141", + "ACH-002161", + "ACH-002202", + "ACH-002446", + "ACH-002705", + "ACH-002706" + ], + "hoverinfo": "text", + "marker": { + "color": "#FED4C4", + "size": 7 + }, + "mode": "markers", + "name": "Esophagogastric Adenocarcinoma", + "text": [ + "Esophagogastric Adenocarcinoma | ACH-000047", + "Esophagogastric Adenocarcinoma | ACH-000144", + "Esophagogastric Adenocarcinoma | ACH-000216", + "Esophagogastric Adenocarcinoma | ACH-000239", + "Esophagogastric Adenocarcinoma | ACH-000247", + "Esophagogastric Adenocarcinoma | ACH-000255", + "Esophagogastric Adenocarcinoma | ACH-000303", + "Esophagogastric Adenocarcinoma | ACH-000325", + "Esophagogastric Adenocarcinoma | ACH-000344", + "Esophagogastric Adenocarcinoma | ACH-000356", + "Esophagogastric Adenocarcinoma | ACH-000383", + "Esophagogastric Adenocarcinoma | ACH-000427", + "Esophagogastric Adenocarcinoma | ACH-000466", + "Esophagogastric Adenocarcinoma | ACH-000485", + "Esophagogastric Adenocarcinoma | ACH-000507", + "Esophagogastric Adenocarcinoma | ACH-000581", + "Esophagogastric Adenocarcinoma | ACH-000616", + "Esophagogastric Adenocarcinoma | ACH-000633", + "Esophagogastric Adenocarcinoma | ACH-000736", + "Esophagogastric Adenocarcinoma | ACH-000746", + "Esophagogastric Adenocarcinoma | ACH-000758", + "Esophagogastric Adenocarcinoma | ACH-000764", + "Esophagogastric Adenocarcinoma | ACH-000793", + "Esophagogastric Adenocarcinoma | ACH-000847", + "Esophagogastric Adenocarcinoma | ACH-000880", + "Esophagogastric Adenocarcinoma | ACH-000898", + "Esophagogastric Adenocarcinoma | ACH-000911", + "Esophagogastric Adenocarcinoma | ACH-000919", + "Esophagogastric Adenocarcinoma | ACH-000932", + "Esophagogastric Adenocarcinoma | ACH-000948", + "Esophagogastric Adenocarcinoma | ACH-001368", + "Esophagogastric Adenocarcinoma | ACH-001496", + "Esophagogastric Adenocarcinoma | ACH-001497", + "Esophagogastric Adenocarcinoma | ACH-001500", + "Esophagogastric Adenocarcinoma | ACH-001544", + "Esophagogastric Adenocarcinoma | ACH-001653", + "Esophagogastric Adenocarcinoma | ACH-001654", + "Esophagogastric Adenocarcinoma | ACH-001664", + "Esophagogastric Adenocarcinoma | ACH-002141", + "Esophagogastric Adenocarcinoma | ACH-002161", + "Esophagogastric Adenocarcinoma | ACH-002202", + "Esophagogastric Adenocarcinoma | ACH-002446", + "Esophagogastric Adenocarcinoma | ACH-002705", + "Esophagogastric Adenocarcinoma | ACH-002706" + ], + "type": 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+ "Mature T and NK Neoplasms | ACH-000226", + "Mature T and NK Neoplasms | ACH-000233", + "Mature T and NK Neoplasms | ACH-000338", + "Mature T and NK Neoplasms | ACH-000664", + "Mature T and NK Neoplasms | ACH-000773", + "Mature T and NK Neoplasms | ACH-001111", + "Mature T and NK Neoplasms | ACH-001119", + "Mature T and NK Neoplasms | ACH-001737" + ], + "type": "scattergl", + "x": { + "bdata": "w/RRP0TM5j9x3Lc/5rKhP7Xy/D5hARJAzPhuPxnvNz/1NZ++yX8zPw==", + "dtype": "f4" + }, + "y": { + "bdata": "CX/IvjNkh78QJlS/lw0iv6BQyT4pp62/yj3Zvoh6Cz3D43I/75TxPQ==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000054" + ], + "hoverinfo": "text", + "marker": { + "color": "#0DF9FF", + "size": 7 + }, + "mode": "markers", + "name": "Fibrosarcoma", + "text": [ + "Fibrosarcoma | ACH-000054" + ], + "type": "scattergl", + "x": { + "bdata": "Xb2cPg==", + "dtype": "f4" + }, + "y": { + "bdata": "2PABPw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000055", + "ACH-000095", + "ACH-000160", + "ACH-000211", + "ACH-000776", + "ACH-001020", + "ACH-001028", + "ACH-001031", + "ACH-001033", + "ACH-001053", + "ACH-001054", + "ACH-001232", + "ACH-001289", + "ACH-001670", + "ACH-001711" + ], + "hoverinfo": "text", + "marker": { + "color": "#F6F926", + "size": 7 + }, + "mode": "markers", + "name": "Embryonal Tumor", + "text": [ + "Embryonal Tumor | ACH-000055", + "Embryonal Tumor | ACH-000095", + "Embryonal Tumor | ACH-000160", + "Embryonal Tumor | ACH-000211", + "Embryonal Tumor | ACH-000776", + "Embryonal Tumor | ACH-001020", + "Embryonal Tumor | ACH-001028", + "Embryonal Tumor | ACH-001031", + "Embryonal Tumor | ACH-001033", + "Embryonal Tumor | ACH-001053", + "Embryonal Tumor | ACH-001054", + "Embryonal Tumor | ACH-001232", + "Embryonal Tumor | ACH-001289", + "Embryonal Tumor | ACH-001670", + "Embryonal Tumor | ACH-001711" + ], + "type": "scattergl", + "x": { + "bdata": "J8WEP0P6Xz//2OA/5R6aPSWYIT+tPQY//We+P+DJvj/qpyU/l18bP7Ziyz8j2AA9uvk0P14NgT+i1Eo/", + "dtype": "f4" + }, + "y": { + "bdata": "CwenvkQ2Lr5OaFu/WsE7PySRKj7i35g+uEIXvyqTFb8zmE8+mSwJPU8nUr/zUIs/ofHDPekKPb6OtoY+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000070", + "ACH-000151", + "ACH-000782", + "ACH-000922", + "ACH-000938", + "ACH-000960", + "ACH-001484", + "ACH-001520", + "ACH-001669", + "ACH-001735", + "ACH-001736", + "ACH-001993", + "ACH-002059" + ], + "hoverinfo": "text", + "marker": { + "color": "#FF9616", + "size": 7 + }, + "mode": "markers", + "name": "B-Lymphoblastic Leukemia/Lymphoma", + "text": [ + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000070", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000151", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000782", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000922", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000938", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000960", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001484", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001520", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001669", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001735", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001736", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001993", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-002059" + ], + "type": "scattergl", + "x": { + "bdata": "zSnTPzVNcz8uvbk/E4gKQGpV8j+lytg/BXGlP1VYzj/+fP8/H+OjPymGCUA5A2k/MN+7Pw==", + "dtype": "f4" + }, + "y": { + "bdata": "xTR/vxyTAr+8Ekq/TKrJv/jokL/9A2y/jZ4zvzMNa78I/6W//So6vyh6tb+YgbG+cUZQvw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000074", + "ACH-000076", + "ACH-000198", + "ACH-000295", + "ACH-000326", + "ACH-000551", + "ACH-000604", + "ACH-000920", + "ACH-000983", + "ACH-002061" + ], + "hoverinfo": "text", + "marker": { + "color": "#479B55", + "size": 7 + }, + "mode": "markers", + "name": "Myeloproliferative Neoplasms", + "text": [ + "Myeloproliferative Neoplasms | ACH-000074", + "Myeloproliferative Neoplasms | ACH-000076", + "Myeloproliferative Neoplasms | ACH-000198", + "Myeloproliferative Neoplasms | ACH-000295", + "Myeloproliferative Neoplasms | ACH-000326", + "Myeloproliferative Neoplasms | ACH-000551", + "Myeloproliferative Neoplasms | ACH-000604", + "Myeloproliferative Neoplasms | ACH-000920", + "Myeloproliferative Neoplasms | ACH-000983", + "Myeloproliferative Neoplasms | ACH-002061" + ], + "type": "scattergl", + "x": { + "bdata": "sTGYPxZyqj/zjR1ATKYGPzTrwj+qiak/eXpjP73FAz8B8+c/QSymPw==", + "dtype": "f4" + }, + "y": { + "bdata": "fh4hv2Z8Kb8ddN2/YQOTPdfsfL/O4Bm/QXJYvrfEPT5FRpi/R6YDvw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000077", + "ACH-000583", + "ACH-001197", + "ACH-001642" + ], + "hoverinfo": "text", + "marker": { + "color": "#EEA6FB", + "size": 7 + }, + "mode": "markers", + "name": "Non-Hodgkin Lymphoma", + "text": [ + "Non-Hodgkin Lymphoma | ACH-000077", + "Non-Hodgkin Lymphoma | ACH-000583", + "Non-Hodgkin Lymphoma | ACH-001197", + "Non-Hodgkin Lymphoma | ACH-001642" + ], + "type": "scattergl", + "x": { + "bdata": "OgKzPwCyI8CdJ48/JesyPw==", + "dtype": "f4" + }, + "y": { + "bdata": "/9oovw5V0r+ougS/V/CsvA==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000078", + "ACH-000099", + "ACH-000120", + "ACH-000149", + "ACH-000203", + "ACH-000227", + "ACH-000259", + "ACH-000260", + "ACH-000310", + "ACH-000312", + "ACH-000341", + "ACH-000366", + "ACH-000804", + "ACH-001188", + "ACH-001300", + "ACH-001301", + "ACH-001302", + "ACH-001303", + "ACH-001338", + "ACH-001344", + "ACH-001354", + "ACH-001366", + "ACH-001367", + "ACH-001481", + "ACH-001548", + "ACH-001603", + "ACH-001674", + "ACH-002080", + "ACH-002083", + "ACH-002261", + "ACH-002278", + "ACH-002280", + "ACH-002282", + "ACH-002283", + "ACH-002284", + "ACH-002285", + "ACH-002922" + ], + "hoverinfo": "text", + "marker": { + "color": "#DC587D", + "size": 7 + }, + "mode": "markers", + "name": "Neuroblastoma", + "text": [ + "Neuroblastoma | ACH-000078", + "Neuroblastoma | ACH-000099", + "Neuroblastoma | ACH-000120", + "Neuroblastoma | ACH-000149", + "Neuroblastoma | ACH-000203", + "Neuroblastoma | ACH-000227", + "Neuroblastoma | ACH-000259", + "Neuroblastoma | ACH-000260", + "Neuroblastoma | ACH-000310", + "Neuroblastoma | ACH-000312", + "Neuroblastoma | ACH-000341", + "Neuroblastoma | ACH-000366", + "Neuroblastoma | ACH-000804", + "Neuroblastoma | ACH-001188", + "Neuroblastoma | ACH-001300", + "Neuroblastoma | ACH-001301", + "Neuroblastoma | ACH-001302", + "Neuroblastoma | ACH-001303", + "Neuroblastoma | ACH-001338", + "Neuroblastoma | ACH-001344", + "Neuroblastoma | ACH-001354", + "Neuroblastoma | ACH-001366", + "Neuroblastoma | ACH-001367", + "Neuroblastoma | ACH-001481", + "Neuroblastoma | ACH-001548", + "Neuroblastoma | ACH-001603", + "Neuroblastoma | ACH-001674", + "Neuroblastoma | ACH-002080", + "Neuroblastoma | ACH-002083", + "Neuroblastoma | ACH-002261", + "Neuroblastoma | ACH-002278", + "Neuroblastoma | ACH-002280", + "Neuroblastoma | ACH-002282", + "Neuroblastoma | ACH-002283", + "Neuroblastoma | ACH-002284", + "Neuroblastoma | ACH-002285", + "Neuroblastoma | ACH-002922" + ], + "type": "scattergl", + "x": { + "bdata": "m1kbP34SqD9tt+k+wRKDP57ogT0vgsu+5AnmP4aRZz91B8++cVg3P95kWj2qlT0/lnK3P0SWdD8FI6g/vs0SvMan8D5qo2I+LrK5P259kj6XTSA/4p9qPzEmlT85EA4+pMkWPhP/eT8srJM/3aMywO+Jzj/DrNk/G0fQP7ejzD/sp6Q/E+ZaP5NgM8DlfyFAwZCWPw==", + "dtype": "f4" + }, + "y": { + "bdata": "BQ2OPmMv/b4UQXU+99mcvDTAKD856qA/tFZ3v18FLb6ca5c/09sgPZ++Aj/NFRE9OUcwvwTpcr6hKeC+/ZRCPxQWyj4uUQk/X1kEv7UK+T6tdDY+JpBFvj7PxL4+kAk/NK4YP+I25b3K1vy+EFxSv+TQvL5BPkq/Sy8Vv3VJAL//c+S+IYgcvXtIUr9ENpK/UX7jvg==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000082", + "ACH-000359", + "ACH-000364", + "ACH-000410", + "ACH-000748", + "ACH-001001", + "ACH-001526", + "ACH-001715", + "ACH-001814", + "ACH-002067", + "ACH-002069", + "ACH-002471", + "ACH-002834" + ], + "hoverinfo": "text", + "marker": { + "color": "#D626FF", + "size": 7 + }, + "mode": "markers", + "name": "Osteosarcoma", + "text": [ + "Osteosarcoma | ACH-000082", + "Osteosarcoma | ACH-000359", + "Osteosarcoma | ACH-000364", + "Osteosarcoma | ACH-000410", + "Osteosarcoma | ACH-000748", + "Osteosarcoma | ACH-001001", + "Osteosarcoma | ACH-001526", + "Osteosarcoma | ACH-001715", + "Osteosarcoma | ACH-001814", + "Osteosarcoma | ACH-002067", + "Osteosarcoma | ACH-002069", + "Osteosarcoma | ACH-002471", + "Osteosarcoma | ACH-002834" + ], + "type": "scattergl", + "x": { + "bdata": "iIiEv+/OTb/Yl0c/yCXgPsQFND+4+OE/EprBvpuiB78lsSq/ZUTdPrrhNr2ve5C7aVM4wA==", + "dtype": "f4" + }, + "y": { + "bdata": "O5zRP+sHrT8CqIo9GdyvPp1FAj/SXAa/rROPP13Mhz8Zq8E/rV+GPhWMQT9HzGc/fiYavw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000086", + "ACH-000092", + "ACH-000153", + "ACH-000319", + "ACH-000331", + "ACH-000335", + "ACH-000367", + "ACH-000569", + "ACH-000645", + "ACH-000648", + "ACH-001547", + "ACH-001555", + "ACH-001556", + "ACH-001557", + "ACH-001558", + "ACH-001559", + "ACH-001560", + "ACH-001562", + "ACH-001977", + "ACH-001992", + "ACH-002033" + ], + "hoverinfo": "text", + "marker": { + "color": "#6E899C", + "size": 7 + }, + "mode": "markers", + "name": "Pleural Mesothelioma", + "text": [ + "Pleural Mesothelioma | ACH-000086", + "Pleural Mesothelioma | ACH-000092", + "Pleural Mesothelioma | ACH-000153", + "Pleural Mesothelioma | ACH-000319", + "Pleural Mesothelioma | ACH-000331", + "Pleural Mesothelioma | ACH-000335", + "Pleural Mesothelioma | ACH-000367", + "Pleural Mesothelioma | ACH-000569", + "Pleural Mesothelioma | ACH-000645", + "Pleural Mesothelioma | ACH-000648", + "Pleural Mesothelioma | ACH-001547", + "Pleural Mesothelioma | ACH-001555", + "Pleural Mesothelioma | ACH-001556", + "Pleural Mesothelioma | ACH-001557", + "Pleural Mesothelioma | ACH-001558", + "Pleural Mesothelioma | ACH-001559", + "Pleural Mesothelioma | ACH-001560", + "Pleural Mesothelioma | ACH-001562", + "Pleural Mesothelioma | ACH-001977", + "Pleural Mesothelioma | ACH-001992", + "Pleural Mesothelioma | ACH-002033" + ], + "type": "scattergl", + "x": { + "bdata": "h88/P0wYCr/maMS+Xl61vgigiz6T7U0/GCk5wM3GqT7FFPy+jRPNPnShcb6/dn89WugUP0dBij4OczrA0/s2wKY5NMBN6zDA1G+jPwiEcT+wSUq/", + "dtype": "f4" + }, + "y": { + "bdata": "jfPtPUJbnj8D45Y/ty2SPyCD0T6nzRE+z2gGv6coAj+7N6A/Qgq7Pj9yRj+iOhk//gSHPvaPGj/HUf++ChExvychV7+ta4C/5kERvwwDKb5wOL8/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000090", + "ACH-000115", + "ACH-000956", + "ACH-000977", + "ACH-000979", + "ACH-001422", + "ACH-001627", + "ACH-001648", + "ACH-001649" + ], + "hoverinfo": "text", + "marker": { + "color": "#00B5F7", + "size": 7 + }, + "mode": "markers", + "name": "Prostate Adenocarcinoma", + "text": [ + "Prostate Adenocarcinoma | ACH-000090", + "Prostate Adenocarcinoma | ACH-000115", + "Prostate Adenocarcinoma | ACH-000956", + "Prostate Adenocarcinoma | ACH-000977", + "Prostate Adenocarcinoma | ACH-000979", + "Prostate Adenocarcinoma | ACH-001422", + "Prostate Adenocarcinoma | ACH-001627", + "Prostate Adenocarcinoma | ACH-001648", + "Prostate Adenocarcinoma | ACH-001649" + ], + "type": "scattergl", + "x": { + "bdata": "aZDAPF8mXb8lu1M/6fbKPxuS6D7/ZoK/a0IswDp6LcAZojbA", + "dtype": "f4" + }, + "y": { + "bdata": "fb4gPwLimT+eLEu9xFtTv6K0Sj5qAso/MySav9AHlL8X8SW/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000096", + "ACH-000172", + "ACH-000533", + "ACH-000597", + "ACH-001099", + "ACH-001128", + "ACH-001211", + "ACH-001212", + "ACH-001532" + ], + "hoverinfo": "text", + "marker": { + "color": "#B68E00", + "size": 7 + }, + "mode": "markers", + "name": "Rhabdoid Cancer", + "text": [ + "Rhabdoid Cancer | ACH-000096", + "Rhabdoid Cancer | ACH-000172", + "Rhabdoid Cancer | ACH-000533", + "Rhabdoid Cancer | ACH-000597", + "Rhabdoid Cancer | ACH-001099", + "Rhabdoid Cancer | ACH-001128", + "Rhabdoid Cancer | ACH-001211", + "Rhabdoid Cancer | ACH-001212", + "Rhabdoid Cancer | ACH-001532" + ], + "type": "scattergl", + "x": { + "bdata": "BFprPyOAHz/qLtI/X6h9Pz2v2j9ULD8/HMBjP3B/GT8+FM8/", + "dtype": "f4" + }, + "y": { + "bdata": "So8FPSP5mD4e9Tm/pBJBvoR+Rr8MpZi6Nekyvtl5iT5pYWW/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000100", + "ACH-000169", + "ACH-000607", + "ACH-000833", + "ACH-001050", + "ACH-001096", + "ACH-001184", + "ACH-001196", + "ACH-001740", + "ACH-001745", + "ACH-001750", + "ACH-001765", + "ACH-002048" + ], + "hoverinfo": "text", + "marker": { + "color": "#C9FBE5", + "size": 7 + }, + "mode": "markers", + "name": "Rhabdomyosarcoma", + "text": [ + "Rhabdomyosarcoma | ACH-000100", + "Rhabdomyosarcoma | ACH-000169", + "Rhabdomyosarcoma | ACH-000607", + "Rhabdomyosarcoma | ACH-000833", + "Rhabdomyosarcoma | ACH-001050", + "Rhabdomyosarcoma | ACH-001096", + "Rhabdomyosarcoma | ACH-001184", + "Rhabdomyosarcoma | ACH-001196", + "Rhabdomyosarcoma | ACH-001740", + "Rhabdomyosarcoma | ACH-001745", + "Rhabdomyosarcoma | ACH-001750", + "Rhabdomyosarcoma | ACH-001765", + "Rhabdomyosarcoma | ACH-002048" + ], + "type": "scattergl", + "x": { + "bdata": "wPV0P5vxbD8mlCY/0gCBP0xqk72jI80/tUKsP998cz8DFB4/eelmP+7uVT/a8aY/YmnTPw==", + "dtype": "f4" + }, + "y": { + "bdata": "QLjSvH6p+70UzwI+f1slvgtZPj8iN1G/w0Iev5fhsL562HA9YLuDvr4AET4DafO+BiBTvw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000108", + "ACH-000685" + ], + "hoverinfo": "text", + "marker": { + "color": "#FF0092", + "size": 7 + }, + "mode": "markers", + "name": "Adenosquamous Carcinoma of the Pancreas", + "text": [ + "Adenosquamous Carcinoma of the Pancreas | ACH-000108", + "Adenosquamous Carcinoma of the Pancreas | ACH-000685" + ], + "type": "scattergl", + "x": { + "bdata": "Fy0zv7paYj8=", + "dtype": "f4" + }, + "y": { + "bdata": "QiSGPyPcpD0=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000133", + "ACH-001310", + "ACH-001453", + "ACH-002210", + "ACH-002247", + "ACH-002462", + "ACH-002463", + "ACH-002464", + "ACH-002465", + "ACH-002467" + ], + "hoverinfo": "text", + "marker": { + "color": "#22FFA7", + "size": 7 + }, + "mode": "markers", + "name": "Non-Cancerous", + "text": [ + "Non-Cancerous | ACH-000133", + "Non-Cancerous | ACH-001310", + "Non-Cancerous | ACH-001453", + "Non-Cancerous | ACH-002210", + "Non-Cancerous | ACH-002247", + "Non-Cancerous | ACH-002462", + "Non-Cancerous | ACH-002463", + "Non-Cancerous | ACH-002464", + "Non-Cancerous | ACH-002465", + "Non-Cancerous | ACH-002467" + ], + "type": "scattergl", + "x": { + "bdata": "JhcjPXM/MsC1s5o+rurhP1gZNsBN1zTAsqU3wHZuPMBl9jHAnOg2wA==", + "dtype": "f4" + }, + "y": { + "bdata": "/Wk5P4COZ78Rx7I++RuVvz2fPb965Ei/+FQfv73xyL5Vo2+/pNAtvw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000141", + "ACH-001607", + "ACH-001619", + "ACH-001850", + "ACH-001861", + "ACH-001961" + ], + "hoverinfo": "text", + "marker": { + "color": "#E3EE9E", + "size": 7 + }, + "mode": "markers", + "name": "Intracholecystic Papillary Neoplasm", + "text": [ + "Intracholecystic Papillary Neoplasm | ACH-000141", + "Intracholecystic Papillary Neoplasm | ACH-001607", + "Intracholecystic Papillary Neoplasm | ACH-001619", + "Intracholecystic Papillary Neoplasm | ACH-001850", + "Intracholecystic Papillary Neoplasm | ACH-001861", + "Intracholecystic Papillary Neoplasm | ACH-001961" + ], + "type": "scattergl", + "x": { + "bdata": "MJ45wJ7+cj8S3/a+1jtqP/MLMMAOAyw/", + "dtype": "f4" + }, + "y": { + "bdata": "B8ABv0adib6RoJo/keaTvpd3hr8pXLy8", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000145", + "ACH-000505", + "ACH-002785" + ], + "hoverinfo": "text", + "marker": { + "color": "#86CE00", + "size": 7 + }, + "mode": "markers", + "name": "Leiomyosarcoma", + "text": [ + "Leiomyosarcoma | ACH-000145", + "Leiomyosarcoma | ACH-000505", + "Leiomyosarcoma | ACH-002785" + ], + "type": "scattergl", + "x": { + "bdata": "atgmv5foZr+U+tK+", + "dtype": "f4" + }, + "y": { + "bdata": "oT+zP0oCyz8Zl6Y/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000159", + "ACH-000189", + "ACH-000234", + "ACH-000246", + "ACH-000250", + "ACH-000262", + "ACH-000272", + "ACH-000313", + "ACH-000317", + "ACH-000375", + "ACH-000385", + "ACH-000411", + "ACH-000433", + "ACH-000459", + "ACH-000484", + "ACH-000495", + "ACH-000649", + "ACH-000684", + "ACH-000709", + "ACH-000792", + "ACH-000907", + "ACH-001163", + "ACH-001194", + "ACH-001398", + "ACH-001687", + "ACH-001688", + "ACH-002150", + "ACH-002189", + "ACH-002533" + ], + "hoverinfo": "text", + "marker": { + "color": "#BC7196", + "size": 7 + }, + "mode": "markers", + "name": "Renal Cell Carcinoma", + "text": [ + "Renal Cell Carcinoma | ACH-000159", + "Renal Cell Carcinoma | ACH-000189", + "Renal Cell Carcinoma | ACH-000234", + "Renal Cell Carcinoma | ACH-000246", + "Renal Cell Carcinoma | ACH-000250", + "Renal Cell Carcinoma | ACH-000262", + "Renal Cell Carcinoma | ACH-000272", + "Renal Cell Carcinoma | ACH-000313", + "Renal Cell Carcinoma | ACH-000317", + "Renal Cell Carcinoma | ACH-000375", + "Renal Cell Carcinoma | ACH-000385", + "Renal Cell Carcinoma | ACH-000411", + "Renal Cell Carcinoma | ACH-000433", + "Renal Cell Carcinoma | ACH-000459", + "Renal Cell Carcinoma | ACH-000484", + "Renal Cell Carcinoma | ACH-000495", + "Renal Cell Carcinoma | ACH-000649", + "Renal Cell Carcinoma | ACH-000684", + "Renal Cell Carcinoma | ACH-000709", + "Renal Cell Carcinoma | ACH-000792", + "Renal Cell Carcinoma | ACH-000907", + "Renal Cell Carcinoma | ACH-001163", + "Renal Cell Carcinoma | ACH-001194", + "Renal Cell Carcinoma | ACH-001398", + "Renal Cell Carcinoma | ACH-001687", + "Renal Cell Carcinoma | ACH-001688", + "Renal Cell Carcinoma | ACH-002150", + "Renal Cell Carcinoma | ACH-002189", + "Renal Cell Carcinoma | ACH-002533" + ], + "type": "scattergl", + "x": { + "bdata": "ORHTvlekN8DrbDq/io4wwB8PNsB+wzTAwg04wITiYL/oQjPAzf2kP3oNwjxO+cs+XS6GvtRIB8ByOTzARZTLvkMLHT/0ok69XFhCvwqJMz7pYIa/gkcSP14HPsCzxsG8gpwzwEL1OsBrrjLAyaKSv5x2gj8=", + "dtype": "f4" + }, + "y": { + "bdata": 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"ACH-001695", + "ACH-001696", + "ACH-001698", + "ACH-001699", + "ACH-001701", + "ACH-002029", + "ACH-002030", + "ACH-002042", + "ACH-002043", + "ACH-002044", + "ACH-002045", + "ACH-002212", + "ACH-002249", + "ACH-002250", + "ACH-002251", + "ACH-002265", + "ACH-002294", + "ACH-002295", + "ACH-002296", + "ACH-002297", + "ACH-002298", + "ACH-002305" + ], + "hoverinfo": "text", + "marker": { + "color": "#7E7DCD", + "size": 7 + }, + "mode": "markers", + "name": "Head and Neck Squamous Cell Carcinoma", + "text": [ + "Head and Neck Squamous Cell Carcinoma | ACH-000163", + "Head and Neck Squamous Cell Carcinoma | ACH-000181", + "Head and Neck Squamous Cell Carcinoma | ACH-000188", + "Head and Neck Squamous Cell Carcinoma | ACH-000207", + "Head and Neck Squamous Cell Carcinoma | ACH-000228", + "Head and Neck Squamous Cell Carcinoma | ACH-000238", + "Head and Neck Squamous Cell Carcinoma | ACH-000415", + "Head and Neck Squamous Cell Carcinoma | ACH-000472", + "Head and Neck Squamous Cell Carcinoma | ACH-000500", + "Head and Neck Squamous Cell Carcinoma | ACH-000503", + "Head and Neck Squamous Cell Carcinoma | ACH-000518", + "Head and Neck Squamous Cell Carcinoma | ACH-000546", + "Head and Neck Squamous Cell Carcinoma | ACH-000548", + "Head and Neck Squamous Cell Carcinoma | ACH-000549", + "Head and Neck Squamous Cell Carcinoma | ACH-000606", + "Head and Neck Squamous Cell Carcinoma | ACH-000618", + "Head and Neck Squamous Cell Carcinoma | ACH-000619", + "Head and Neck Squamous Cell Carcinoma | ACH-000630", + "Head and Neck Squamous Cell Carcinoma | ACH-000682", + "Head and Neck Squamous Cell Carcinoma | ACH-000732", + "Head and Neck Squamous Cell Carcinoma | ACH-000735", + "Head and Neck Squamous Cell Carcinoma | ACH-000740", + "Head and Neck Squamous Cell Carcinoma | ACH-000762", + "Head and Neck Squamous Cell Carcinoma | ACH-000771", + "Head and Neck Squamous Cell Carcinoma | ACH-000778", + "Head and Neck Squamous Cell Carcinoma | ACH-000794", + "Head and Neck Squamous Cell Carcinoma | ACH-000832", + "Head and Neck Squamous Cell Carcinoma | ACH-000836", + "Head and Neck Squamous Cell Carcinoma | ACH-000846", + "Head and Neck Squamous Cell Carcinoma | ACH-001228", + "Head and Neck Squamous Cell Carcinoma | ACH-001229", + "Head and Neck Squamous Cell Carcinoma | ACH-001331", + "Head and Neck Squamous Cell Carcinoma | ACH-001332", + "Head and Neck Squamous Cell Carcinoma | ACH-001346", + "Head and Neck Squamous Cell Carcinoma | ACH-001347", + "Head and Neck Squamous Cell Carcinoma | ACH-001385", + "Head and Neck Squamous Cell Carcinoma | ACH-001509", + "Head and Neck Squamous Cell Carcinoma | ACH-001510", + "Head and Neck Squamous Cell Carcinoma | ACH-001511", + "Head and Neck Squamous Cell Carcinoma | ACH-001542", + "Head and Neck Squamous Cell Carcinoma | ACH-001543", + "Head and Neck Squamous Cell Carcinoma | ACH-001625", + "Head and Neck Squamous Cell Carcinoma | ACH-001626", + "Head and Neck Squamous Cell Carcinoma | ACH-001641", + "Head and Neck Squamous Cell Carcinoma | ACH-001675", + "Head and Neck Squamous Cell Carcinoma | ACH-001690", + "Head and Neck Squamous Cell Carcinoma | ACH-001691", + "Head and Neck Squamous Cell Carcinoma | ACH-001692", + "Head and Neck Squamous Cell Carcinoma | ACH-001694", + "Head and Neck Squamous Cell Carcinoma | ACH-001695", + "Head and Neck Squamous Cell Carcinoma | ACH-001696", + "Head and Neck Squamous Cell Carcinoma | ACH-001698", + "Head and Neck Squamous Cell Carcinoma | ACH-001699", + "Head and Neck Squamous Cell Carcinoma | ACH-001701", + "Head and Neck Squamous Cell Carcinoma | ACH-002029", + "Head and Neck Squamous Cell Carcinoma | ACH-002030", + "Head and Neck Squamous Cell Carcinoma | ACH-002042", + "Head and Neck Squamous Cell Carcinoma | ACH-002043", + "Head and Neck Squamous Cell Carcinoma | ACH-002044", + "Head and Neck Squamous Cell Carcinoma | ACH-002045", + "Head and Neck Squamous Cell Carcinoma | ACH-002212", + "Head and Neck Squamous Cell Carcinoma | ACH-002249", 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ACH-002041" + ], + "type": "scattergl", + "x": { + "bdata": "lJeCPmle0j5yIm++pZYkvzOQir9QapY93yx1vQ==", + "dtype": "f4" + }, + "y": { + "bdata": "6zIaP/PbSz6CgZQ/qry2PzWAwD/Qnzk/PPqKPw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000182", + "ACH-000377", + "ACH-001862", + "ACH-002023" + ], + "hoverinfo": "text", + "marker": { + "color": "#E48F72", + "size": 7 + }, + "mode": "markers", + "name": "Ampullary Carcinoma", + "text": [ + "Ampullary Carcinoma | ACH-000182", + "Ampullary Carcinoma | ACH-000377", + "Ampullary Carcinoma | ACH-001862", + "Ampullary Carcinoma | ACH-002023" + ], + "type": "scattergl", + "x": { + "bdata": "Tog0wNMTNcAYF4G+U+kxPw==", + "dtype": "f4" + }, + "y": { + "bdata": "RolKv+WfSL/Cvio/tRZVvg==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000187", + "ACH-000257", + "ACH-000290", + "ACH-000292", + "ACH-000355", + "ACH-000431", + "ACH-000514", + "ACH-000515", + "ACH-000525", + "ACH-000559", + "ACH-000639", + "ACH-000695", + "ACH-000698", + 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Neuroendocrine Tumor | ACH-000767", + "Lung Neuroendocrine Tumor | ACH-000775", + "Lung Neuroendocrine Tumor | ACH-000790", + "Lung Neuroendocrine Tumor | ACH-000800", + "Lung Neuroendocrine Tumor | ACH-000866", + "Lung Neuroendocrine Tumor | ACH-000871", + "Lung Neuroendocrine Tumor | ACH-000890", + "Lung Neuroendocrine Tumor | ACH-000912", + "Lung Neuroendocrine Tumor | ACH-001386", + "Lung Neuroendocrine Tumor | ACH-001549", + "Lung Neuroendocrine Tumor | ACH-002051", + "Lung Neuroendocrine Tumor | ACH-002052", + "Lung Neuroendocrine Tumor | ACH-002077" + ], + "type": "scattergl", + "x": { + "bdata": "3m1kP4zVBj6sLEI/fS/AP2PatT/JI6g+q9CtvTreUD9fDzQ/in4mvhq+wj9VFl++CkmMPyB9Zj8Q/KO8w25RP4C3hj+sexY/RULEP2nWtT+g6la+a95YPw0usT4dwec+5TEDv7SulD1U/qa+", + "dtype": "f4" + }, + "y": { + "bdata": "DZuUvVxOKz/C8pe9cvQdv4j1NL+oEgE/Q7pHP/2UXL7UV668RrEpP+6yfL9pV2w//lQEv1iEHr6kjVQ/0w5WvmdsOr7vonA+eb5Pv8YnGL87pWs/CZ26vc0AnD5/DLw+RFSlP0p1ND+a8n4/", + "dtype": "f4" + } + }, + { + "customdata": [ + 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"Endometrial Carcinoma | ACH-000941", + "Endometrial Carcinoma | ACH-000946", + "Endometrial Carcinoma | ACH-000961", + "Endometrial Carcinoma | ACH-000965", + "Endometrial Carcinoma | ACH-000972", + "Endometrial Carcinoma | ACH-000974", + "Endometrial Carcinoma | ACH-000978", + "Endometrial Carcinoma | ACH-000984", + "Endometrial Carcinoma | ACH-000988", + "Endometrial Carcinoma | ACH-000993", + "Endometrial Carcinoma | ACH-000994", + "Endometrial Carcinoma | ACH-000996", + "Endometrial Carcinoma | ACH-001495", + "Endometrial Carcinoma | ACH-001517", + "Endometrial Carcinoma | ACH-001518", + "Endometrial Carcinoma | ACH-002026", + "Endometrial Carcinoma | ACH-002027", + "Endometrial Carcinoma | ACH-002046" + ], + "type": "scattergl", + "x": { + "bdata": "cZ9Yvyr4Ub/BCrI8bRaavUkyCz4LzWq+KC4xwBdZVz9w9Zc/Nx2TPzhpEL9AdmY/UAhgP5bI2T8D7jjARYqNP36mLz4JTd6+p3EIPY367z1uRTPADhwCPfRctr6uIIy/dJA9wDk8kT+qNws/YpqqvQ==", + "dtype": "f4" + }, + "y": { + "bdata": 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ACH-001538", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001673", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001834", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001835", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001836", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001838", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001839", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001841", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001842", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001843", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001844", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001848", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001849", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001852", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001856", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001857", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001858", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001863", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001864", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001959", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001960", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001997", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-002647" + ], + "type": "scattergl", + "x": { + "bdata": "U1Q3wLMgOMCBbzPAnjI3PAuiPj5MGIQ+xQ2XPhBjqD+QXznAHoszwNrONsA9eTzA04g2wLWMMsAwmYW9HYc2wOTsM8DqzTPAcy00wG36rD/h/NM+/sUlP416HT9aiDrAPE6aPoBB4z9EmDQ/Xao3wMigIT8=", + "dtype": "f4" + }, + "y": { + "bdata": "1OMjvwzWEb/Dsk+/VqEQP75c6D6azvw+7UD6PonjNL/Dyg6/6lxTv/oANL/tkLy+eeQsv9+HbL+f8lg/Ipsvv84HVr8/ele/y+RIv37HGL+odoc+MQwHPmNVMb4mSwO/toywPZmofr+JoEs+fTckv6tlUj4=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000217", + "ACH-000221", + "ACH-000316", + "ACH-000361", + 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Carcinoma | ACH-000493", + "Hepatocellular Carcinoma | ACH-000537", + "Hepatocellular Carcinoma | ACH-000577", + "Hepatocellular Carcinoma | ACH-000620", + "Hepatocellular Carcinoma | ACH-000734", + "Hepatocellular Carcinoma | ACH-000848", + "Hepatocellular Carcinoma | ACH-001318", + "Hepatocellular Carcinoma | ACH-002523" + ], + "type": "scattergl", + "x": { + "bdata": "1flGP2aUzT8A3D0+QYqePnKVfr+S/N2+2iASP708kLxdxlw/JmSSvoa0v74M6og/hF/1vhMvmj24PgI/0JmOv/GlIT/TUa0/aiOoP0Q2PD8Wcfc+", + "dtype": "f4" + }, + "y": { + "bdata": "5fBDvdbs/75YxEk/5K8BP0+P6T8joJQ/phWDPhXoHj/lpgq9bwBuP6Cnfz8yhFe+esWQP+rvOT+Vz8o9vDzgP1KS2r3powW/Vf4Jv8nBhT1xP+E+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000305", + "ACH-000318", + "ACH-000408", + "ACH-000452", + "ACH-000488", + "ACH-000544", + "ACH-000561", + "ACH-000605", + "ACH-000637", + "ACH-000647", + "ACH-000693", + "ACH-000694", + "ACH-000717", + "ACH-000777", + "ACH-000784", + "ACH-000809", + "ACH-000823", + "ACH-000824", + "ACH-000855", + 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Squamous Cell Carcinoma | ACH-000784", + "Esophageal Squamous Cell Carcinoma | ACH-000809", + "Esophageal Squamous Cell Carcinoma | ACH-000823", + "Esophageal Squamous Cell Carcinoma | ACH-000824", + "Esophageal Squamous Cell Carcinoma | ACH-000855", + "Esophageal Squamous Cell Carcinoma | ACH-000865", + "Esophageal Squamous Cell Carcinoma | ACH-000873", + "Esophageal Squamous Cell Carcinoma | ACH-000917", + "Esophageal Squamous Cell Carcinoma | ACH-002243", + "Esophageal Squamous Cell Carcinoma | ACH-002263" + ], + "type": "scattergl", + "x": { + "bdata": "x7SYPmRgSD/+Lkg/oEaDPWYX5j+BEVo/IdY0PzCP9T7loQs+Kl/yvX7O5D9Bm2Q/ZBhePbaxTj/awoo/nHWkPxsHkD8UhhM/GumGP/T6dz/1wII/sGKAP2Z+ND+1dVo/", + "dtype": "f4" + }, + "y": { + "bdata": "Y7+4PmXuBjy9vJY7DGEQP9EbXb97m7a9n6fOvKPdoT67sis/y981P3SdLL/K3Ri+B4kZPxjeYr55squ+NNQJv+I1jr7edp0+lMbAvQZBKr1oC1m+FjKcvs1uVz7YYXW+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000456" + ], + "hoverinfo": "text", + "marker": { + "color": "#B68100", + 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"name": "Cervical Squamous Cell Carcinoma", + "text": [ + "Cervical Squamous Cell Carcinoma | ACH-000490", + "Cervical Squamous Cell Carcinoma | ACH-000556", + "Cervical Squamous Cell Carcinoma | ACH-001333", + "Cervical Squamous Cell Carcinoma | ACH-001334", + "Cervical Squamous Cell Carcinoma | ACH-001335", + "Cervical Squamous Cell Carcinoma | ACH-001336", + "Cervical Squamous Cell Carcinoma | ACH-001360", + "Cervical Squamous Cell Carcinoma | ACH-001402", + "Cervical Squamous Cell Carcinoma | ACH-001451", + "Cervical Squamous Cell Carcinoma | ACH-001515", + "Cervical Squamous Cell Carcinoma | ACH-001651", + "Cervical Squamous Cell Carcinoma | ACH-001652", + "Cervical Squamous Cell Carcinoma | ACH-002020" + ], + "type": "scattergl", + "x": { + "bdata": "Ty0rPxIomj6HkXQ/+/HPPzAVUT9fqwM/eGjOv1oqsz/tTTjAXfVePuvXrb/gReo+8WgGPA==", + "dtype": "f4" + }, + "y": { + "bdata": "KFORPjjf1j6WjKq9/UNSv1GltTymq44+kygWQK7Y3b46hiK/kz8XP1j7AkBUyqc+qdcWPw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000516" + ], + "hoverinfo": "text", + "marker": { + "color": "#511CFB", + "size": 7 + }, + "mode": "markers", + "name": "Chondrosarcoma", + "text": [ + "Chondrosarcoma | ACH-000516" + ], + "type": "scattergl", + "x": { + "bdata": "TGNovw==", + "dtype": "f4" + }, + "y": { + "bdata": "KXTYPw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000624", + "ACH-000725", + "ACH-000859" + ], + "hoverinfo": "text", + "marker": { + "color": "#00A08B", + "size": 7 + }, + "mode": "markers", + "name": "Breast Ductal Carcinoma In Situ", + "text": [ + "Breast Ductal Carcinoma In Situ | ACH-000624", + "Breast Ductal Carcinoma In Situ | ACH-000725", + "Breast Ductal Carcinoma In Situ | ACH-000859" + ], + "type": "scattergl", + "x": { + "bdata": "EXLqPuNdPr8BHNK6", + "dtype": "f4" + }, + "y": { + "bdata": "x617vRUBrD+J/Ak/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000671", + "ACH-000739" + ], + "hoverinfo": "text", + "marker": { + "color": "#FB00D1", + "size": 7 + }, + "mode": "markers", + "name": "Hepatoblastoma", + "text": [ + "Hepatoblastoma | ACH-000671", + "Hepatoblastoma | ACH-000739" + ], + "type": "scattergl", + "x": { + "bdata": "R96vP/gruz4=", + "dtype": "f4" + }, + "y": { + "bdata": "UHgBvwhVpj4=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000702", + "ACH-000754", + "ACH-001685" + ], + "hoverinfo": "text", + "marker": { + "color": "#FC0080", + "size": 7 + }, + "mode": "markers", + "name": "Hodgkin Lymphoma", + "text": [ + "Hodgkin Lymphoma | ACH-000702", + "Hodgkin Lymphoma | ACH-000754", + "Hodgkin Lymphoma | ACH-001685" + ], + "type": "scattergl", + "x": { + "bdata": "ArigPoiJHD+My4a7", + "dtype": "f4" + }, + "y": { + "bdata": "7FBdPiHBDj4pHxE/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000716", + "ACH-000903", + "ACH-001528" + ], + "hoverinfo": "text", + "marker": { + "color": "#B2828D", + "size": 7 + }, + "mode": "markers", + "name": "Well-Differentiated Thyroid Cancer", + "text": [ + 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Cell Carcinoma | ACH-001551", + "Merkel Cell Carcinoma | ACH-001552" + ], + "type": "scattergl", + "x": { + "bdata": "H9emvh0RpT/zzya/", + "dtype": "f4" + }, + "y": { + "bdata": "9V2XPyJBwL7oaMg/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-001554", + "ACH-002014", + "ACH-002015", + "ACH-002016", + "ACH-002018", + "ACH-002687", + "ACH-002925", + "ACH-002926" + ], + "hoverinfo": "text", + "marker": { + "color": "#FF6692", + "size": 7 + }, + "mode": "markers", + "name": "Ocular Melanoma", + "text": [ + "Ocular Melanoma | ACH-001554", + "Ocular Melanoma | ACH-002014", + "Ocular Melanoma | ACH-002015", + "Ocular Melanoma | ACH-002016", + "Ocular Melanoma | ACH-002018", + "Ocular Melanoma | ACH-002687", + "Ocular Melanoma | ACH-002925", + "Ocular Melanoma | ACH-002926" + ], + "type": "scattergl", + "x": { + "bdata": "xoQvwPh2+z6A5Kg+NnIev6p0Pj9x5DHA9OAxwL4PLcA=", + "dtype": "f4" + }, + "y": { + "bdata": "/IaIv+eVhj5pUP0+wI+ZP8o7Tr6yi2e/K8yAv/lRmb8=", + "dtype": "f4" + } + }, + { 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"ACH-000985", + "ACH-000986", + "ACH-000991", + "ACH-000997", + "ACH-001039", + "ACH-001061", + "ACH-001081", + "ACH-001345", + "ACH-001399", + "ACH-001454", + "ACH-001458", + "ACH-001459", + "ACH-001460", + "ACH-001461", + "ACH-001786", + "ACH-002024", + "ACH-002025", + "ACH-002233", + "ACH-002535", + "ACH-002654", + "ACH-002659", + "ACH-002660", + "ACH-002662", + "ACH-002664", + "ACH-002669" + ], + "hoverinfo": "text", + "marker": { + "color": "#00CC96", + "size": 7 + }, + "mode": "markers", + "name": "Colorectal Adenocarcinoma", + "text": [ + "Colorectal Adenocarcinoma | ACH-000007", + "Colorectal Adenocarcinoma | ACH-000009", + "Colorectal Adenocarcinoma | ACH-000202", + "Colorectal Adenocarcinoma | ACH-000249", + "Colorectal Adenocarcinoma | ACH-000252", + "Colorectal Adenocarcinoma | ACH-000253", + "Colorectal Adenocarcinoma | ACH-000286", + "Colorectal Adenocarcinoma | ACH-000296", + "Colorectal Adenocarcinoma | ACH-000350", + "Colorectal Adenocarcinoma | ACH-000381", + "Colorectal Adenocarcinoma | ACH-000403", + "Colorectal Adenocarcinoma | ACH-000421", + "Colorectal Adenocarcinoma | ACH-000467", + "Colorectal Adenocarcinoma | ACH-000470", + "Colorectal Adenocarcinoma | ACH-000489", + "Colorectal Adenocarcinoma | ACH-000491", + "Colorectal Adenocarcinoma | ACH-000501", + "Colorectal Adenocarcinoma | ACH-000532", + "Colorectal Adenocarcinoma | ACH-000552", + "Colorectal Adenocarcinoma | ACH-000565", + "Colorectal Adenocarcinoma | ACH-000651", + "Colorectal Adenocarcinoma | ACH-000683", + "Colorectal Adenocarcinoma | ACH-000722", + "Colorectal Adenocarcinoma | ACH-000798", + "Colorectal Adenocarcinoma | ACH-000820", + "Colorectal Adenocarcinoma | ACH-000926", + "Colorectal Adenocarcinoma | ACH-000935", + "Colorectal Adenocarcinoma | ACH-000943", + "Colorectal Adenocarcinoma | ACH-000950", + "Colorectal Adenocarcinoma | ACH-000957", + "Colorectal Adenocarcinoma | ACH-000958", + "Colorectal Adenocarcinoma | ACH-000959", + "Colorectal Adenocarcinoma | ACH-000963", + "Colorectal Adenocarcinoma | ACH-000969", + "Colorectal Adenocarcinoma | ACH-000970", + "Colorectal Adenocarcinoma | ACH-000971", + "Colorectal Adenocarcinoma | ACH-000985", + "Colorectal Adenocarcinoma | ACH-000986", + "Colorectal Adenocarcinoma | ACH-000991", + "Colorectal Adenocarcinoma | ACH-000997", + "Colorectal Adenocarcinoma | ACH-001039", + "Colorectal Adenocarcinoma | ACH-001061", + "Colorectal Adenocarcinoma | ACH-001081", + "Colorectal Adenocarcinoma | ACH-001345", + "Colorectal Adenocarcinoma | ACH-001399", + "Colorectal Adenocarcinoma | ACH-001454", + "Colorectal Adenocarcinoma | ACH-001458", + "Colorectal Adenocarcinoma | ACH-001459", + "Colorectal Adenocarcinoma | ACH-001460", + "Colorectal Adenocarcinoma | ACH-001461", + "Colorectal Adenocarcinoma | ACH-001786", + "Colorectal Adenocarcinoma | ACH-002024", + "Colorectal Adenocarcinoma | ACH-002025", + "Colorectal Adenocarcinoma | ACH-002233", + "Colorectal Adenocarcinoma | ACH-002535", + "Colorectal Adenocarcinoma | ACH-002654", + "Colorectal Adenocarcinoma | ACH-002659", + "Colorectal Adenocarcinoma | ACH-002660", + "Colorectal Adenocarcinoma | ACH-002662", + "Colorectal Adenocarcinoma | ACH-002664", + "Colorectal Adenocarcinoma | ACH-002669" + ], + "type": "scattergl", + "x": { + "bdata": "Pj5MQJQn5z9ZM9M/tU/1wMHqRz71BYw/X7mpP51M4D8Z+xHA2fcoQMaEnb9Y0iS/XVH1wFC11L1RFoY/SDaFv+sez7whYoA/WRrNP5Fclz9S0C9AjWtrvuiJ2T80Y/XANglePyph9cBGXvXAThf1wIQ1WkB2GVtAzP4CQOYtI0CZ6J2/9V/1wI0s0T89tcs/SkVZP2pK9cAc7Jc/F0w0QA0yMkAr32BAnFL1wJxoCEAPLYM/tnarvzsJXD+il94/UiJFQLGhwr9BTPY+6/6gP7ZF9cB/R6M+pusxPxJGKb00gzpA/KuXP+1cKEDljipAPo9FQA==", + "dtype": "f4" + }, + "y": { + "bdata": 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Carcinoma", + "text": [ + "Bladder Urothelial Carcinoma | ACH-000011", + "Bladder Urothelial Carcinoma | ACH-000018", + "Bladder Urothelial Carcinoma | ACH-000026", + "Bladder Urothelial Carcinoma | ACH-000127", + "Bladder Urothelial Carcinoma | ACH-000142", + "Bladder Urothelial Carcinoma | ACH-000242", + "Bladder Urothelial Carcinoma | ACH-000396", + "Bladder Urothelial Carcinoma | ACH-000473", + "Bladder Urothelial Carcinoma | ACH-000486", + "Bladder Urothelial Carcinoma | ACH-000522", + "Bladder Urothelial Carcinoma | ACH-000545", + "Bladder Urothelial Carcinoma | ACH-000547", + "Bladder Urothelial Carcinoma | ACH-000593", + "Bladder Urothelial Carcinoma | ACH-000720", + "Bladder Urothelial Carcinoma | ACH-000724", + "Bladder Urothelial Carcinoma | ACH-000741", + "Bladder Urothelial Carcinoma | ACH-000753", + "Bladder Urothelial Carcinoma | ACH-000802", + "Bladder Urothelial Carcinoma | ACH-000834", + "Bladder Urothelial Carcinoma | ACH-000862", + "Bladder Urothelial Carcinoma | ACH-000896", + "Bladder Urothelial Carcinoma | ACH-000905", + "Bladder Urothelial Carcinoma | ACH-001183", + "Bladder Urothelial Carcinoma | ACH-001407", + "Bladder Urothelial Carcinoma | ACH-001409", + "Bladder Urothelial Carcinoma | ACH-001412", + "Bladder Urothelial Carcinoma | ACH-001413", + "Bladder Urothelial Carcinoma | ACH-001414", + "Bladder Urothelial Carcinoma | ACH-001415", + "Bladder Urothelial Carcinoma | ACH-001416" + ], + "type": "scattergl", + "x": { + "bdata": "0rv5PzG3yj+vyNg/FhtpQDqeCUAYkt4/6UXbvcBk9cADpklACDL1wFdV9cDAIwVApjTgP3fmAkBPV3O/cGzOP4y1VEBUPlBA7EJTQAGJ9cC0txFATzMbQLZZ9cAoOPXA90b1wNRY9cBkMvXAuFn1wD6N9cAQW/XA", + "dtype": "f4" + }, + "y": { + "bdata": "hcSLP9+nzD+pwsA9NZ2gu0SA2T4BWpo+kxOOP+H0br6XAgU/ZhR0vo+Jbb7meFQ/aJesP52y6T+q1KQ/bMNAPjR9IT99XYw/u/U1Pwu8Wb5bMjM/M4kPP5r9Xb4GpW++gyhovq9/bL5X74C+jlddvs4RZb6kAHO+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000012", + "ACH-000015", + "ACH-000021", + "ACH-000029", + "ACH-000030", + "ACH-000035", + "ACH-000143", + "ACH-000161", + "ACH-000176", + "ACH-000251", + "ACH-000261", + "ACH-000264", + "ACH-000311", + "ACH-000337", + "ACH-000339", + "ACH-000343", + "ACH-000378", + "ACH-000390", + "ACH-000395", + "ACH-000414", + "ACH-000416", + "ACH-000434", + "ACH-000438", + "ACH-000442", + "ACH-000444", + "ACH-000448", + "ACH-000454", + "ACH-000463", + "ACH-000481", + "ACH-000496", + "ACH-000510", + "ACH-000511", + "ACH-000521", + "ACH-000528", + "ACH-000562", + "ACH-000563", + "ACH-000585", + "ACH-000587", + "ACH-000589", + "ACH-000596", + "ACH-000627", + "ACH-000638", + "ACH-000662", + "ACH-000665", + "ACH-000666", + "ACH-000667", + "ACH-000672", + "ACH-000677", + "ACH-000681", + "ACH-000700", + "ACH-000706", + "ACH-000718", + "ACH-000747", + "ACH-000757", + "ACH-000766", + "ACH-000769", + "ACH-000774", + "ACH-000781", + "ACH-000785", + "ACH-000787", + "ACH-000791", + "ACH-000826", + "ACH-000837", + "ACH-000840", + "ACH-000841", + "ACH-000843", + "ACH-000845", + "ACH-000851", + "ACH-000853", + "ACH-000858", + "ACH-000860", + "ACH-000861", + "ACH-000867", + "ACH-000869", + "ACH-000872", + "ACH-000878", + "ACH-000886", + "ACH-000888", + "ACH-000894", + "ACH-000900", + "ACH-000901", + "ACH-000916", + "ACH-000921", + "ACH-000924", + "ACH-000929", + "ACH-000945", + "ACH-000975", + "ACH-000980", + "ACH-001075", + "ACH-001137", + "ACH-001233", + "ACH-002035", + "ACH-002156", + "ACH-002522", + "ACH-002526", + "ACH-002531", + "ACH-002650", + "ACH-003012" + ], + "hoverinfo": "text", + "marker": { + "color": "#FFA15A", + "size": 7 + }, + "mode": "markers", + "name": "Non-Small Cell Lung Cancer", + "text": [ + "Non-Small Cell Lung Cancer | ACH-000012", + "Non-Small Cell Lung Cancer | ACH-000015", + "Non-Small Cell Lung Cancer | ACH-000021", + "Non-Small Cell Lung Cancer | ACH-000029", + "Non-Small Cell Lung Cancer | ACH-000030", + "Non-Small Cell Lung Cancer | ACH-000035", + "Non-Small Cell Lung Cancer | ACH-000143", + "Non-Small Cell Lung Cancer | ACH-000161", + "Non-Small Cell Lung Cancer | ACH-000176", + "Non-Small Cell Lung Cancer | ACH-000251", + "Non-Small Cell Lung Cancer | ACH-000261", + "Non-Small Cell Lung Cancer | ACH-000264", + "Non-Small Cell Lung Cancer | ACH-000311", + "Non-Small Cell Lung Cancer | ACH-000337", + "Non-Small Cell Lung Cancer | ACH-000339", + "Non-Small Cell Lung Cancer | ACH-000343", + "Non-Small Cell Lung Cancer | ACH-000378", + "Non-Small Cell Lung Cancer | ACH-000390", + "Non-Small Cell Lung Cancer | ACH-000395", + "Non-Small Cell Lung Cancer | ACH-000414", + "Non-Small Cell Lung Cancer | ACH-000416", + "Non-Small Cell Lung Cancer | ACH-000434", + "Non-Small Cell Lung Cancer | ACH-000438", + "Non-Small Cell Lung Cancer | ACH-000442", + "Non-Small Cell Lung Cancer | ACH-000444", + "Non-Small Cell Lung Cancer | ACH-000448", + "Non-Small Cell Lung Cancer | ACH-000454", + "Non-Small Cell Lung Cancer | ACH-000463", + "Non-Small Cell Lung Cancer | ACH-000481", + "Non-Small Cell Lung Cancer | ACH-000496", + "Non-Small Cell Lung Cancer | ACH-000510", + "Non-Small Cell Lung Cancer | ACH-000511", + "Non-Small Cell Lung Cancer | ACH-000521", + "Non-Small Cell Lung Cancer | ACH-000528", + "Non-Small Cell Lung Cancer | ACH-000562", + "Non-Small Cell Lung Cancer | ACH-000563", + "Non-Small Cell Lung Cancer | ACH-000585", + "Non-Small Cell Lung Cancer | ACH-000587", + "Non-Small Cell Lung Cancer | ACH-000589", + "Non-Small Cell Lung Cancer | ACH-000596", + "Non-Small Cell Lung Cancer | ACH-000627", + "Non-Small Cell Lung Cancer | ACH-000638", + "Non-Small Cell Lung Cancer | ACH-000662", + "Non-Small Cell Lung Cancer | ACH-000665", + "Non-Small Cell Lung Cancer | ACH-000666", + "Non-Small Cell Lung Cancer | ACH-000667", + "Non-Small Cell Lung Cancer | ACH-000672", + "Non-Small Cell Lung Cancer | ACH-000677", + "Non-Small Cell Lung Cancer | ACH-000681", + "Non-Small Cell Lung Cancer | ACH-000700", + "Non-Small Cell Lung Cancer | ACH-000706", + "Non-Small Cell Lung Cancer | ACH-000718", + "Non-Small Cell Lung Cancer | ACH-000747", + "Non-Small Cell Lung Cancer | ACH-000757", + "Non-Small Cell Lung Cancer | ACH-000766", + "Non-Small Cell Lung Cancer | ACH-000769", + "Non-Small Cell Lung Cancer | ACH-000774", + "Non-Small Cell Lung Cancer | ACH-000781", + "Non-Small Cell Lung Cancer | ACH-000785", + "Non-Small Cell Lung Cancer | ACH-000787", + "Non-Small Cell Lung Cancer | ACH-000791", + "Non-Small Cell Lung Cancer | ACH-000826", + "Non-Small Cell Lung Cancer | ACH-000837", + "Non-Small Cell Lung Cancer | ACH-000840", + "Non-Small Cell Lung Cancer | ACH-000841", + "Non-Small Cell Lung Cancer | ACH-000843", + "Non-Small Cell Lung Cancer | ACH-000845", + "Non-Small Cell Lung Cancer | ACH-000851", + "Non-Small Cell Lung Cancer | ACH-000853", + "Non-Small Cell Lung Cancer | ACH-000858", + "Non-Small Cell Lung Cancer | ACH-000860", + "Non-Small Cell Lung Cancer | ACH-000861", + "Non-Small Cell Lung Cancer | ACH-000867", + "Non-Small Cell Lung Cancer | ACH-000869", + "Non-Small Cell Lung Cancer | ACH-000872", + "Non-Small Cell Lung Cancer | ACH-000878", + "Non-Small Cell Lung Cancer | ACH-000886", + "Non-Small Cell Lung Cancer | ACH-000888", + "Non-Small Cell Lung Cancer | ACH-000894", + "Non-Small Cell Lung Cancer | ACH-000900", + "Non-Small Cell Lung Cancer | ACH-000901", + "Non-Small Cell Lung Cancer | ACH-000916", + "Non-Small Cell Lung Cancer | ACH-000921", + "Non-Small Cell Lung Cancer | ACH-000924", + "Non-Small Cell Lung Cancer | ACH-000929", + "Non-Small Cell Lung Cancer | ACH-000945", + "Non-Small Cell Lung Cancer | ACH-000975", + "Non-Small Cell Lung Cancer | ACH-000980", + "Non-Small Cell Lung Cancer | ACH-001075", + "Non-Small Cell Lung Cancer | ACH-001137", + "Non-Small Cell Lung Cancer | ACH-001233", + "Non-Small Cell Lung Cancer | ACH-002035", + "Non-Small Cell Lung Cancer | ACH-002156", + "Non-Small Cell Lung Cancer | ACH-002522", + "Non-Small Cell Lung Cancer | ACH-002526", + "Non-Small Cell Lung Cancer | ACH-002531", + "Non-Small Cell Lung Cancer | ACH-002650", + "Non-Small Cell Lung Cancer | ACH-003012" + ], + "type": "scattergl", + "x": { + "bdata": "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", + "dtype": "f4" + }, + "y": { + "bdata": 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"ACH-000827", + "ACH-000881", + "ACH-000882", + "ACH-000884", + "ACH-000899", + "ACH-000915", + "ACH-000968", + "ACH-001041", + "ACH-001190", + "ACH-001239", + "ACH-001522", + "ACH-001563", + "ACH-001566", + "ACH-001567", + "ACH-001568", + "ACH-001570", + "ACH-001645", + "ACH-001970", + "ACH-001972", + "ACH-001973", + "ACH-001975", + "ACH-001982", + "ACH-001986", + "ACH-001990", + "ACH-002001", + "ACH-002002", + "ACH-002003", + "ACH-002004", + "ACH-002005", + "ACH-002084", + "ACH-002143", + "ACH-002458", + "ACH-002460", + "ACH-002461", + "ACH-002508", + "ACH-002510", + "ACH-002511", + "ACH-002512", + "ACH-002847", + "ACH-002928" + ], + "hoverinfo": "text", + "marker": { + "color": "#19D3F3", + "size": 7 + }, + "mode": "markers", + "name": "Melanoma", + "text": [ + "Melanoma | ACH-000014", + "Melanoma | ACH-000219", + "Melanoma | ACH-000274", + "Melanoma | ACH-000304", + "Melanoma | ACH-000322", + "Melanoma | ACH-000348", + "Melanoma | ACH-000401", + "Melanoma | ACH-000404", + "Melanoma | ACH-000425", + "Melanoma | ACH-000441", + "Melanoma | ACH-000450", + "Melanoma | ACH-000458", + "Melanoma | ACH-000477", + "Melanoma | ACH-000550", + "Melanoma | ACH-000579", + "Melanoma | ACH-000580", + "Melanoma | ACH-000614", + "Melanoma | ACH-000632", + "Melanoma | ACH-000661", + "Melanoma | ACH-000765", + "Melanoma | ACH-000788", + "Melanoma | ACH-000799", + "Melanoma | ACH-000801", + "Melanoma | ACH-000805", + "Melanoma | ACH-000810", + "Melanoma | ACH-000822", + "Melanoma | ACH-000827", + "Melanoma | ACH-000881", + "Melanoma | ACH-000882", + "Melanoma | ACH-000884", + "Melanoma | ACH-000899", + "Melanoma | ACH-000915", + "Melanoma | ACH-000968", + "Melanoma | ACH-001041", + "Melanoma | ACH-001190", + "Melanoma | ACH-001239", + "Melanoma | ACH-001522", + "Melanoma | ACH-001563", + "Melanoma | ACH-001566", + "Melanoma | ACH-001567", + "Melanoma | ACH-001568", + "Melanoma | ACH-001570", + "Melanoma | ACH-001645", + "Melanoma | ACH-001970", + "Melanoma | ACH-001972", + "Melanoma | ACH-001973", + "Melanoma | ACH-001975", + "Melanoma | ACH-001982", + "Melanoma | ACH-001986", + "Melanoma | ACH-001990", + "Melanoma | ACH-002001", + "Melanoma | ACH-002002", + "Melanoma | ACH-002003", + "Melanoma | ACH-002004", + "Melanoma | ACH-002005", + "Melanoma | ACH-002084", + "Melanoma | ACH-002143", + "Melanoma | ACH-002458", + "Melanoma | ACH-002460", + "Melanoma | ACH-002461", + "Melanoma | ACH-002508", + "Melanoma | ACH-002510", + "Melanoma | ACH-002511", + "Melanoma | ACH-002512", + "Melanoma | ACH-002847", + "Melanoma | ACH-002928" + ], + "type": "scattergl", + "x": { + "bdata": "RBoeQKmUpEBPvdC/Ne4KP3NkUkDyuRK/3akpQL1E9cCkbvXAlydcQDpV9cCcRfXAgTMlP8WRL7+OXfXAMmmqPmSkPEC0nyNAvmD1wJ4I4T8lkMU/5uURP7Z29cAIQc8/ouplP0KT1r8UMOo/WnVEQMDDakCWWjhAgkj1wIHxPkD0mi1AWfzrP5jKqrzmHDdAv7XuP9FI9cDfavXAgHL1wHZe9cDEVfXAjir1PPkzF0BTJvXA4Fn1wHxo9cD5ogVANGdCQCr6W0B9b2JA2LGPQHwAFEBYPfXA1utYQLMNPzuR2AvAKUcqQJo1GkCGwDE/KKZtPhI9OEBV5gTAySquP/zkrD7i4P2/", + "dtype": "f4" + }, + "y": { + "bdata": "RQEyP8tjKD9anoc//YAMPxiYaD9ZqKs/QtxfP5IDar6KK2C+oWq0Pkq3Xb4rWXS+5YucPzVJMEDr9mK+SOYkP4oQND93nwBAt59nvhpriz8cBMA/aZ7AP2DSXr570gU+SvcSP7buzL4sR3s/of+bPSHTjb7j0WG9dJZevrYIEr83/rm7mdW8P/1Xwz8/nXg+lzxGP32ZeL6az2i+7AlfvlLeXr6Gv3O+xhfOvtPBtT8DIHa+qbVpvi2vab78eTm/iyMYPmG45T1hF5s+Cc42v/wgDT8xAm6+wAvgupPnej8MZLc+MRzBP+iQHT8UDzU/sHQ/QC/rkj0zYgc/16vDPz1dFEDw70U+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000017", + "ACH-000019", + "ACH-000028", + "ACH-000097", + "ACH-000111", + "ACH-000147", + "ACH-000148", + "ACH-000212", + "ACH-000223", + "ACH-000248", + "ACH-000258", + "ACH-000276", + "ACH-000277", + "ACH-000288", + "ACH-000330", + "ACH-000352", + "ACH-000374", + "ACH-000554", + "ACH-000573", + "ACH-000621", + "ACH-000668", + "ACH-000699", + "ACH-000711", + "ACH-000721", + "ACH-000768", + "ACH-000783", + "ACH-000849", + "ACH-000856", + "ACH-000876", + "ACH-000910", + "ACH-000934", + "ACH-001065", + "ACH-001388", + "ACH-001389", + "ACH-001390", + "ACH-001391", + "ACH-001392", + "ACH-001393", + "ACH-001394", + "ACH-001396", + "ACH-001419", + "ACH-001662", + "ACH-001683", + "ACH-001819", + "ACH-002179", + "ACH-002399", + "ACH-002401" + ], + "hoverinfo": "text", + "marker": { + "color": "#FF6692", + "size": 7 + }, + "mode": "markers", + "name": "Invasive Breast Carcinoma", + "text": [ + "Invasive Breast Carcinoma | ACH-000017", + "Invasive Breast Carcinoma | ACH-000019", + "Invasive Breast Carcinoma | ACH-000028", + "Invasive Breast Carcinoma | ACH-000097", + "Invasive Breast Carcinoma | ACH-000111", + "Invasive Breast Carcinoma | ACH-000147", + "Invasive Breast Carcinoma | ACH-000148", + "Invasive Breast Carcinoma | ACH-000212", + "Invasive Breast Carcinoma | ACH-000223", + "Invasive Breast Carcinoma | ACH-000248", + "Invasive Breast Carcinoma | ACH-000258", + "Invasive Breast Carcinoma | ACH-000276", + "Invasive Breast Carcinoma | ACH-000277", + "Invasive Breast Carcinoma | ACH-000288", + "Invasive Breast Carcinoma | ACH-000330", + "Invasive Breast Carcinoma | ACH-000352", + "Invasive Breast Carcinoma | ACH-000374", + "Invasive Breast Carcinoma | ACH-000554", + "Invasive Breast Carcinoma | ACH-000573", + "Invasive Breast Carcinoma | ACH-000621", + "Invasive Breast Carcinoma | ACH-000668", + "Invasive Breast Carcinoma | ACH-000699", + "Invasive Breast Carcinoma | ACH-000711", + "Invasive Breast Carcinoma | ACH-000721", + "Invasive Breast Carcinoma | ACH-000768", + "Invasive Breast Carcinoma | ACH-000783", + "Invasive Breast Carcinoma | ACH-000849", + "Invasive Breast Carcinoma | ACH-000856", + "Invasive Breast Carcinoma | ACH-000876", + "Invasive Breast Carcinoma | ACH-000910", + "Invasive Breast Carcinoma | ACH-000934", + "Invasive Breast Carcinoma | ACH-001065", + "Invasive Breast Carcinoma | ACH-001388", + "Invasive Breast Carcinoma | ACH-001389", + "Invasive Breast Carcinoma | ACH-001390", + "Invasive Breast Carcinoma | ACH-001391", + "Invasive Breast Carcinoma | ACH-001392", + "Invasive Breast Carcinoma | ACH-001393", + "Invasive Breast Carcinoma | ACH-001394", + "Invasive Breast Carcinoma | ACH-001396", + "Invasive Breast Carcinoma | ACH-001419", + "Invasive Breast Carcinoma | ACH-001662", + "Invasive Breast Carcinoma | ACH-001683", + "Invasive Breast Carcinoma | ACH-001819", + "Invasive Breast Carcinoma | ACH-002179", + "Invasive Breast Carcinoma | ACH-002399", + "Invasive Breast Carcinoma | ACH-002401" + ], + "type": "scattergl", + "x": { + "bdata": "hOtRPmIYlT8ZFEJA/CokP62K0T9n0/c/fZToPpTtwD/IHnS/hZaxP3A4P75uMuK9sjkuvjxB1D8x9Rk/8wMDPwPIxT9ykDbAUauiP/vWGsDh95K+/ajHv/y+AUDQuj1AjB3NP3DHEMB6zShAtN+SQAUJ9r9tMfU/sjqAwJQDdUC2glm/2Vf1wHw1B0AiRLa/4V71wHBa9cDuY/XAb4b1wCUeYD8cOXu+v1QZu2/stL84zZE/jMOoP8j+J0A=", + "dtype": "f4" + }, + "y": { + "bdata": "bx9mv6Y817962tO/YaGSv3qEBsDlEMO/Jy6SP1WVCD9/Yyy/JaW8v27Bdr42n0k+U5B1v0OtEEAICoW/Fke1vww4P79nMA3APro9PmqgCD5PYqi/rEjaPvOTKr9xixO/XppvPEoxrr9cYwm/45ckPkjs7r/E4RrAZoL6vxMd1r8O5K48JuBivhgkMT+RPiM+aYJovo9YbL5xWG6+CeVpvl395b6JHiC/H750v3OXdr+PSibA33rjvs3rVL0=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000022", + "ACH-000023", + "ACH-000042", + "ACH-000060", + "ACH-000085", + "ACH-000093", + "ACH-000094", + "ACH-000114", + "ACH-000118", + "ACH-000138", + "ACH-000139", + "ACH-000155", + "ACH-000164", + "ACH-000178", + "ACH-000213", + "ACH-000222", + "ACH-000235", + "ACH-000243", + "ACH-000265", + "ACH-000266", + "ACH-000281", + "ACH-000307", + "ACH-000320", + "ACH-000332", + "ACH-000354", + "ACH-000417", + "ACH-000468", + "ACH-000502", + "ACH-000517", + "ACH-000535", + "ACH-000599", + "ACH-000601", + "ACH-000652", + "ACH-001098", + "ACH-001107", + "ACH-001353", + "ACH-001375", + "ACH-001377", + "ACH-001379", + "ACH-001380", + "ACH-001382", + "ACH-001999", + "ACH-002039", + "ACH-002186", + "ACH-002672" + ], + "hoverinfo": "text", + "marker": { + "color": "#B6E880", + "size": 7 + }, + "mode": "markers", + "name": "Pancreatic Adenocarcinoma", + "text": [ + "Pancreatic Adenocarcinoma | ACH-000022", + "Pancreatic Adenocarcinoma | ACH-000023", + "Pancreatic Adenocarcinoma | ACH-000042", + "Pancreatic Adenocarcinoma | ACH-000060", + "Pancreatic Adenocarcinoma | ACH-000085", + "Pancreatic Adenocarcinoma | ACH-000093", + "Pancreatic Adenocarcinoma | ACH-000094", + "Pancreatic Adenocarcinoma | ACH-000114", + "Pancreatic Adenocarcinoma | ACH-000118", + "Pancreatic Adenocarcinoma | ACH-000138", + "Pancreatic Adenocarcinoma | ACH-000139", + "Pancreatic Adenocarcinoma | ACH-000155", + "Pancreatic Adenocarcinoma | ACH-000164", + "Pancreatic Adenocarcinoma | ACH-000178", + "Pancreatic Adenocarcinoma | ACH-000213", + "Pancreatic Adenocarcinoma | ACH-000222", + "Pancreatic Adenocarcinoma | ACH-000235", + "Pancreatic Adenocarcinoma | ACH-000243", + "Pancreatic Adenocarcinoma | ACH-000265", + "Pancreatic Adenocarcinoma | ACH-000266", + "Pancreatic Adenocarcinoma | ACH-000281", + "Pancreatic Adenocarcinoma | ACH-000307", + "Pancreatic Adenocarcinoma | ACH-000320", + "Pancreatic Adenocarcinoma | ACH-000332", + "Pancreatic Adenocarcinoma | ACH-000354", + "Pancreatic Adenocarcinoma | ACH-000417", + "Pancreatic Adenocarcinoma | ACH-000468", + "Pancreatic Adenocarcinoma | ACH-000502", + "Pancreatic Adenocarcinoma | ACH-000517", + "Pancreatic Adenocarcinoma | ACH-000535", + "Pancreatic Adenocarcinoma | ACH-000599", + "Pancreatic Adenocarcinoma | ACH-000601", + "Pancreatic Adenocarcinoma | ACH-000652", + "Pancreatic Adenocarcinoma | ACH-001098", + "Pancreatic Adenocarcinoma | ACH-001107", + "Pancreatic Adenocarcinoma | ACH-001353", + "Pancreatic Adenocarcinoma | ACH-001375", + "Pancreatic Adenocarcinoma | ACH-001377", + "Pancreatic Adenocarcinoma | ACH-001379", + "Pancreatic Adenocarcinoma | ACH-001380", + "Pancreatic Adenocarcinoma | ACH-001382", + "Pancreatic Adenocarcinoma | ACH-001999", + "Pancreatic Adenocarcinoma | ACH-002039", + "Pancreatic Adenocarcinoma | ACH-002186", + "Pancreatic Adenocarcinoma | ACH-002672" + ], + "type": "scattergl", + "x": { + "bdata": "rgS9PzeViEDK2QW/btWKvnGMTj+PEks/C91evyPCfD1oPeM/5nQHQCkfoz+O2l4+kHnIP6rUF0Drk+E/ltQFwHxQlT8vmglAhcuOQOpJt79dYQ8/Omf1wNZyPkCacLk/g4b7Pm4vNL8HjvXA29zRP1Bhab9iAo0/VTp9P4ckX0C1BeM/2iwrQLRMSz7H8lc/jKWYPmqCEkA0je8/HGAqQEo7AD9CYPXAbV/1wHVX9cByhdE/", + "dtype": "f4" + }, + "y": { + "bdata": "pdfKvqClkj/z5uG9W9/vPi8SAD/zN0k/2jmnv40UQz9/cRq/Yzp+PiUrj706yi8+l5ypvRcupT7kAay/16ytvwsz675yqTY/6N2fPtKamT5e9As/7RBuvoVaAj8fLLg+JMqfv90fMr9BqVO+ixhnPcGDPz+NOA0/HKetvzUF8b4/X/c+HDuwvmijSj+7MTg/vO4MP/2WnT4M3Rg7RPMrPhC7uz9jNXC+xO1ivgb4c76ggXg9", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000024", + "ACH-000106", + "ACH-000124", + "ACH-000167", + "ACH-000183", + "ACH-000204", + "ACH-000271", + "ACH-000315", + "ACH-000334", + "ACH-000346", + "ACH-000363", + "ACH-000365", + "ACH-000371", + "ACH-000398", + "ACH-000402", + "ACH-000405", + "ACH-000426", + "ACH-000436", + "ACH-000512", + "ACH-000541", + "ACH-000567", + "ACH-000576", + "ACH-000588", + "ACH-000653", + "ACH-000654", + "ACH-000656", + "ACH-000660", + "ACH-000697", + "ACH-000714", + "ACH-000763", + "ACH-000817", + "ACH-000821", + "ACH-000829", + "ACH-000838", + "ACH-000889", + "ACH-000914", + "ACH-000944", + "ACH-001450", + "ACH-001498", + "ACH-001533", + "ACH-001539", + "ACH-001616", + "ACH-001634", + "ACH-001639", + "ACH-001677", + "ACH-001707", + "ACH-001709", + "ACH-002055", + "ACH-002062", + "ACH-002214", + "ACH-002215", + "ACH-002478", + "ACH-002485", + "ACH-002500", + "ACH-002677", + "ACH-002678" + ], + "hoverinfo": "text", + "marker": { + "color": "#FF97FF", + "size": 7 + }, + "mode": "markers", + "name": "Mature B-Cell Neoplasms", + "text": [ + "Mature B-Cell Neoplasms | ACH-000024", + "Mature B-Cell Neoplasms | ACH-000106", + "Mature B-Cell Neoplasms | ACH-000124", + "Mature B-Cell Neoplasms | ACH-000167", + "Mature B-Cell Neoplasms | ACH-000183", + "Mature B-Cell Neoplasms | ACH-000204", + "Mature B-Cell Neoplasms | ACH-000271", + "Mature B-Cell Neoplasms | ACH-000315", + "Mature B-Cell Neoplasms | ACH-000334", + "Mature B-Cell Neoplasms | ACH-000346", + "Mature B-Cell Neoplasms | ACH-000363", + "Mature B-Cell Neoplasms | ACH-000365", + "Mature B-Cell Neoplasms | ACH-000371", + "Mature B-Cell Neoplasms | ACH-000398", + "Mature B-Cell Neoplasms | ACH-000402", + "Mature B-Cell Neoplasms | ACH-000405", + "Mature B-Cell Neoplasms | ACH-000426", + "Mature B-Cell Neoplasms | ACH-000436", + "Mature B-Cell Neoplasms | ACH-000512", + "Mature B-Cell Neoplasms | ACH-000541", + "Mature B-Cell Neoplasms | ACH-000567", + "Mature B-Cell Neoplasms | ACH-000576", + "Mature B-Cell Neoplasms | ACH-000588", + "Mature B-Cell Neoplasms | ACH-000653", + "Mature B-Cell Neoplasms | ACH-000654", + "Mature B-Cell Neoplasms | ACH-000656", + "Mature B-Cell Neoplasms | ACH-000660", + "Mature B-Cell Neoplasms | ACH-000697", + "Mature B-Cell Neoplasms | ACH-000714", + "Mature B-Cell Neoplasms | ACH-000763", + "Mature B-Cell Neoplasms | ACH-000817", + "Mature B-Cell Neoplasms | ACH-000821", + "Mature B-Cell Neoplasms | ACH-000829", + "Mature B-Cell Neoplasms | ACH-000838", + "Mature B-Cell Neoplasms | ACH-000889", + "Mature B-Cell Neoplasms | ACH-000914", + "Mature B-Cell Neoplasms | ACH-000944", + "Mature B-Cell Neoplasms | ACH-001450", + "Mature B-Cell Neoplasms | ACH-001498", + "Mature B-Cell Neoplasms | ACH-001533", + "Mature B-Cell Neoplasms | ACH-001539", + "Mature B-Cell Neoplasms | ACH-001616", + "Mature B-Cell Neoplasms | ACH-001634", + "Mature B-Cell Neoplasms | ACH-001639", + "Mature B-Cell Neoplasms | ACH-001677", + "Mature B-Cell Neoplasms | ACH-001707", + "Mature B-Cell Neoplasms | ACH-001709", + "Mature B-Cell Neoplasms | ACH-002055", + "Mature B-Cell Neoplasms | ACH-002062", + "Mature B-Cell Neoplasms | ACH-002214", + "Mature B-Cell Neoplasms | ACH-002215", + "Mature B-Cell Neoplasms | ACH-002478", + "Mature B-Cell Neoplasms | ACH-002485", + "Mature B-Cell Neoplasms | ACH-002500", + "Mature B-Cell Neoplasms | ACH-002677", + "Mature B-Cell Neoplasms | ACH-002678" + ], + "type": "scattergl", + "x": { + "bdata": "J+omQHwl4z/a75ZA1dcUQPpscUDoeTVAQ/6jQEygAUCxBoK/lL5FQB9fCr/CXmxAxpQnQI6mGkBIQgxAusJpQLnAjD5BR/XA8uskQDLarD/NDPXACkNGP2rOWUBxyQtAMAoEQPhEoUCJcqZA32hQQMBs/j9/llY/bHFGQI302j90PfXA+U7XP2Kte0DUrn5ALTRXQKn/L0CRplpA4i71wPG+pj8bYmxAn1H1wJCcjj+fMNc/LFj1wDNch0ASkSpA5MQLQAk4eECyfE5AByQpQCyYIUCKQXhAlFRvQAh4AUA=", + "dtype": "f4" + }, + "y": { + "bdata": "MOcTwGrcTr9+/wTATzXkv45bJcBrpFnALixAwKVG6r+H4hHAIMIHwDdXMcCjNDPAtAMowBmnG8BistS/SrD5v1sC4b9agXO+jPn8v3OFEcDFfYO+zHMDwNcGHsANEifAAFoqwIzEFsC+pd+/QAjbv4sEKsBks/G/kdIawGSH8b+Jvm6+sbQHwMTaEsAXQTLAr5kPwAgyNsAQ6RPA69d/vtnt07+M+kvATZF0vhXMTcCBNW6/6MB5vgHKNcDwbwPAlrHTv8AeMcARA+W/dwkNwINqmb+TIgDA3Fs+wNwqDsA=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000025", + "ACH-001067", + "ACH-002070" + ], + "hoverinfo": "text", + "marker": { + "color": "#FECB52", + "size": 7 + }, + "mode": "markers", + "name": "Meningothelial Tumor", + "text": [ + "Meningothelial Tumor | ACH-000025", + "Meningothelial Tumor | ACH-001067", + "Meningothelial Tumor | ACH-002070" + ], + "type": "scattergl", + "x": { + "bdata": "yABNQNop9cD6YO4/", + "dtype": "f4" + }, + "y": { + "bdata": "7jABQMvIc749eaQ/", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000036", + "ACH-000040", + "ACH-000067", + "ACH-000075", + "ACH-000098", + "ACH-000128", + "ACH-000137", + "ACH-000152", + "ACH-000200", + "ACH-000208", + "ACH-000215", + "ACH-000231", + "ACH-000232", + "ACH-000244", + "ACH-000269", + "ACH-000273", + "ACH-000323", + "ACH-000329", + "ACH-000368", + "ACH-000370", + "ACH-000376", + "ACH-000389", + "ACH-000437", + "ACH-000445", + "ACH-000455", + "ACH-000464", + "ACH-000469", + "ACH-000479", + "ACH-000504", + "ACH-000558", + "ACH-000570", + "ACH-000571", + "ACH-000591", + "ACH-000592", + "ACH-000595", + "ACH-000609", + "ACH-000622", + "ACH-000623", + "ACH-000631", + "ACH-000634", + "ACH-000655", + "ACH-000673", + "ACH-000676", + "ACH-000738", + "ACH-000756", + "ACH-000760", + "ACH-000807", + "ACH-000819", + "ACH-000863", + "ACH-000887", + "ACH-001016", + "ACH-001126", + "ACH-001172", + "ACH-001329", + "ACH-001605", + "ACH-001606", + "ACH-001608", + "ACH-001609", + "ACH-001610", + "ACH-001611", + "ACH-001622", + "ACH-001623", + "ACH-001624", + "ACH-002228", + "ACH-002229", + "ACH-002230", + "ACH-002257", + "ACH-002269", + "ACH-002304", + "ACH-002680" + ], + "hoverinfo": "text", + "marker": { + "color": "#FD3216", + "size": 7 + }, + "mode": "markers", + "name": "Diffuse Glioma", + "text": [ + "Diffuse Glioma | ACH-000036", + "Diffuse Glioma | ACH-000040", + "Diffuse Glioma | ACH-000067", + "Diffuse Glioma | ACH-000075", + "Diffuse Glioma | ACH-000098", + "Diffuse Glioma | ACH-000128", + "Diffuse Glioma | ACH-000137", + "Diffuse Glioma | ACH-000152", + "Diffuse Glioma | ACH-000200", + "Diffuse Glioma | ACH-000208", + "Diffuse Glioma | ACH-000215", + "Diffuse Glioma | ACH-000231", + "Diffuse Glioma | ACH-000232", + "Diffuse Glioma | ACH-000244", + "Diffuse Glioma | ACH-000269", + "Diffuse Glioma | ACH-000273", + "Diffuse Glioma | ACH-000323", + "Diffuse Glioma | ACH-000329", + "Diffuse Glioma | ACH-000368", + "Diffuse Glioma | ACH-000370", + "Diffuse Glioma | ACH-000376", + "Diffuse Glioma | ACH-000389", + "Diffuse Glioma | ACH-000437", + "Diffuse Glioma | ACH-000445", + "Diffuse Glioma | ACH-000455", + "Diffuse Glioma | ACH-000464", + "Diffuse Glioma | ACH-000469", + "Diffuse Glioma | ACH-000479", + "Diffuse Glioma | ACH-000504", + "Diffuse Glioma | ACH-000558", + "Diffuse Glioma | ACH-000570", + "Diffuse Glioma | ACH-000571", + "Diffuse Glioma | ACH-000591", + "Diffuse Glioma | ACH-000592", + "Diffuse Glioma | ACH-000595", + "Diffuse Glioma | ACH-000609", + "Diffuse Glioma | ACH-000622", + "Diffuse Glioma | ACH-000623", + "Diffuse Glioma | ACH-000631", + "Diffuse Glioma | ACH-000634", + "Diffuse Glioma | ACH-000655", + "Diffuse Glioma | ACH-000673", + "Diffuse Glioma | ACH-000676", + "Diffuse Glioma | ACH-000738", + "Diffuse Glioma | ACH-000756", + "Diffuse Glioma | ACH-000760", + "Diffuse Glioma | ACH-000807", + "Diffuse Glioma | ACH-000819", + "Diffuse Glioma | ACH-000863", + "Diffuse Glioma | ACH-000887", + "Diffuse Glioma | ACH-001016", + "Diffuse Glioma | ACH-001126", + "Diffuse Glioma | ACH-001172", + "Diffuse Glioma | ACH-001329", + "Diffuse Glioma | ACH-001605", + "Diffuse Glioma | ACH-001606", + "Diffuse Glioma | ACH-001608", + "Diffuse Glioma | ACH-001609", + "Diffuse Glioma | ACH-001610", + "Diffuse Glioma | ACH-001611", + "Diffuse Glioma | ACH-001622", + "Diffuse Glioma | ACH-001623", + "Diffuse Glioma | ACH-001624", + "Diffuse Glioma | ACH-002228", + "Diffuse Glioma | ACH-002229", + "Diffuse Glioma | ACH-002230", + "Diffuse Glioma | ACH-002257", + "Diffuse Glioma | ACH-002269", + "Diffuse Glioma | ACH-002304", + "Diffuse Glioma | ACH-002680" + ], + "type": "scattergl", + "x": { + "bdata": "ygmvP89N+b29fTS/QAfnvvIPmT8iee8/f8nZP9oa/b6ZbPXAH6ZoP27ADECr7q4/hrlUQCLlEMCq4I29orkyQLJnbT9wk26+GJy1PhFm4L46kmpAetGaP4PHqz9s0Pk+hPVcQCr2zL8SfqE/4L5fP8RmAMCLasU/ct0DQMdXob84M44/i/wWv90sxz+ELTc/CIIGwFTdCr9Pf60+T9bRP/yXBz9qffXATF9MQAJDNkBIrCdAEDJvP1lx5z/p960/6lErQJYHAUCuo/Y/Eln1wBFGV0A3+1m/trwlPWARrr+/ag9AxVGrP/RbkT+pPLU/5r5YPoEJ/b6P9zO+6lz1wAY+9cCdUvXAOjxCP71yU0CAOfXA9mVkPw==", + "dtype": "f4" + }, + "y": { + "bdata": "+5M6QEexPkCn1BFAcmgTQC5XXUC5OBc/vjkYQAzSA0CnHl++dtGrP6wHBUBKvw9AbOJzP0oSP0CUIsU+6mENQOsR0T9ranI/fYFlQCBuEj+N5qA/pvIQQNfeB0D0px1A/kNLP+L9IUCLmBlALkPvP7tVAkAp8vk/oGYqQLzjtz9rwUpAQaMBQBYKBkAVCw5AZe0NP+d0IkDRjrw/YsnZP5T0ZD8w6VS+aMTUvt+2Yj/LtyBAhbUlPy2DXz6cUt8/cpkOQG8WPD/3yIo/b4FvvjN2xT7S/xtA0CbvPykpoz8jrdg/ah/AP8mQuT/Gn9M/zK06QJxMK0AzdDs/Si1wviRqYb6ImWS+OJpgQFheqz/Xvnm+xko8QA==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000037" + ], + "hoverinfo": "text", + "marker": { + "color": "#00FE35", + "size": 7 + }, + "mode": "markers", + "name": "Sarcoma, NOS", + "text": [ + "Sarcoma, NOS | ACH-000037" + ], + "type": "scattergl", + "x": { + "bdata": "LiYbvw==", + "dtype": "f4" + }, + "y": { + "bdata": "atrvPw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000039", + "ACH-000041", + "ACH-000052", + "ACH-000087", + "ACH-000210", + "ACH-000279", + "ACH-000391", + "ACH-000424", + "ACH-000499", + "ACH-001029", + "ACH-001038", + "ACH-001192", + "ACH-001193", + "ACH-001205", + "ACH-001283", + "ACH-001430", + "ACH-001431", + "ACH-002105", + "ACH-002106", + "ACH-002109", + "ACH-002110", + "ACH-002114", + "ACH-002116", + "ACH-002119", + "ACH-002160" + ], + "hoverinfo": "text", + "marker": { + "color": "#6A76FC", + "size": 7 + }, + "mode": "markers", + "name": "Ewing Sarcoma", + "text": [ + "Ewing Sarcoma | ACH-000039", + "Ewing Sarcoma | ACH-000041", + "Ewing Sarcoma | ACH-000052", + "Ewing Sarcoma | ACH-000087", + "Ewing Sarcoma | ACH-000210", + "Ewing Sarcoma | ACH-000279", + "Ewing Sarcoma | ACH-000391", + "Ewing Sarcoma | ACH-000424", + "Ewing Sarcoma | ACH-000499", + "Ewing Sarcoma | ACH-001029", + "Ewing Sarcoma | ACH-001038", + "Ewing Sarcoma | ACH-001192", + "Ewing Sarcoma | ACH-001193", + "Ewing Sarcoma | ACH-001205", + "Ewing Sarcoma | ACH-001283", + "Ewing Sarcoma | ACH-001430", + "Ewing Sarcoma | ACH-001431", + "Ewing Sarcoma | ACH-002105", + "Ewing Sarcoma | ACH-002106", + "Ewing Sarcoma | ACH-002109", + "Ewing Sarcoma | ACH-002110", + "Ewing Sarcoma | ACH-002114", + "Ewing Sarcoma | ACH-002116", + "Ewing Sarcoma | ACH-002119", + "Ewing Sarcoma | ACH-002160" + ], + "type": "scattergl", + "x": { + "bdata": "DIWCPlcphD4KdZ8/thsdQLIjlz9V7UpAk0tyQCU3j0DyikRAMshnQJhb6z9/vPg/VwPoPxxY7j+fkARAc8PTPwXXBkDiogBAl7lOQGySBUBVWphA7U/1wHBz9cDmIoNAD2t4QA==", + "dtype": "f4" + }, + "y": { + "bdata": "F6ncPh4t474dvcY/3PfOvmmndb5xT/a+RMSRP8TFaj8rhCI/O74qP5zz0L+ynJA+tmSQP2iMAj5lVgw+P1gIPxWHhr4laBJA7r+tvyxFxT6QGBk+5lJqvktxY76d8gc/iJ/7vQ==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000047", + "ACH-000144", + "ACH-000216", + "ACH-000239", + "ACH-000247", + "ACH-000255", + "ACH-000303", + "ACH-000325", + "ACH-000344", + "ACH-000356", + "ACH-000383", + "ACH-000427", + "ACH-000466", + "ACH-000485", + "ACH-000507", + "ACH-000581", + "ACH-000616", + "ACH-000633", + "ACH-000736", + "ACH-000746", + "ACH-000758", + "ACH-000764", + "ACH-000793", + "ACH-000847", + "ACH-000880", + "ACH-000898", + "ACH-000911", + "ACH-000919", + "ACH-000932", + "ACH-000948", + "ACH-001368", + "ACH-001496", + "ACH-001497", + "ACH-001500", + "ACH-001544", + "ACH-001653", + "ACH-001654", + "ACH-001664", + "ACH-002141", + "ACH-002161", + "ACH-002202", + "ACH-002446", + "ACH-002705", + "ACH-002706" + ], + "hoverinfo": "text", + "marker": { + "color": "#FED4C4", + "size": 7 + }, + "mode": "markers", + "name": "Esophagogastric Adenocarcinoma", + "text": [ + "Esophagogastric Adenocarcinoma | ACH-000047", + "Esophagogastric Adenocarcinoma | ACH-000144", + "Esophagogastric Adenocarcinoma | ACH-000216", + "Esophagogastric Adenocarcinoma | ACH-000239", + "Esophagogastric Adenocarcinoma | ACH-000247", + "Esophagogastric Adenocarcinoma | ACH-000255", + "Esophagogastric Adenocarcinoma | ACH-000303", + "Esophagogastric Adenocarcinoma | ACH-000325", + "Esophagogastric Adenocarcinoma | ACH-000344", + "Esophagogastric Adenocarcinoma | ACH-000356", + "Esophagogastric Adenocarcinoma | ACH-000383", + "Esophagogastric Adenocarcinoma | ACH-000427", + "Esophagogastric Adenocarcinoma | ACH-000466", + "Esophagogastric Adenocarcinoma | ACH-000485", + "Esophagogastric Adenocarcinoma | ACH-000507", + "Esophagogastric Adenocarcinoma | ACH-000581", + "Esophagogastric Adenocarcinoma | ACH-000616", + "Esophagogastric Adenocarcinoma | ACH-000633", + "Esophagogastric Adenocarcinoma | ACH-000736", + "Esophagogastric Adenocarcinoma | ACH-000746", + "Esophagogastric Adenocarcinoma | ACH-000758", + "Esophagogastric Adenocarcinoma | ACH-000764", + "Esophagogastric Adenocarcinoma | ACH-000793", + "Esophagogastric Adenocarcinoma | ACH-000847", + "Esophagogastric Adenocarcinoma | ACH-000880", + "Esophagogastric Adenocarcinoma | ACH-000898", + "Esophagogastric Adenocarcinoma | ACH-000911", + "Esophagogastric Adenocarcinoma | ACH-000919", + "Esophagogastric Adenocarcinoma | ACH-000932", + "Esophagogastric Adenocarcinoma | ACH-000948", + "Esophagogastric Adenocarcinoma | ACH-001368", + "Esophagogastric Adenocarcinoma | ACH-001496", + "Esophagogastric Adenocarcinoma | ACH-001497", + "Esophagogastric Adenocarcinoma | ACH-001500", + "Esophagogastric Adenocarcinoma | ACH-001544", + "Esophagogastric Adenocarcinoma | ACH-001653", + "Esophagogastric Adenocarcinoma | ACH-001654", + "Esophagogastric Adenocarcinoma | ACH-001664", + "Esophagogastric Adenocarcinoma | ACH-002141", + "Esophagogastric Adenocarcinoma | ACH-002161", + "Esophagogastric Adenocarcinoma | ACH-002202", + "Esophagogastric Adenocarcinoma | ACH-002446", + "Esophagogastric Adenocarcinoma | ACH-002705", + "Esophagogastric Adenocarcinoma | ACH-002706" + ], + "type": "scattergl", + "x": { + "bdata": "WLhTQBshJ8BPCxlA/opNPxZrKUDoZe8/mdIJQBIuGEDqf6A/D0DcP/GbFz9yYvXANyF2P71lHEBmrlJA1IbnP/HTND8AgbA/gPlJQEMCvD6f5yJAcmj1wAK8GUDtHvXADD94QC1qAT/jeltA3evlP8X1OkD3PztAGjzPP0oDPT+4rqQ/L7ckQHpu5z2xfQZAF3spQL34WkCcO4BA5+X/P74GPUCVxhZAVLciQPEjWUA=", + "dtype": "f4" + }, + "y": { + "bdata": "FveQv2c2Vb80eC0/JatOPQWBvb8B1NU/YR4vv4vSHMAQkEI/LCf6vn7Rw7/Z7nS+9qzlP3D2q79F+5K/aITvvyP+yj/qi66/zAK/v8HLGMCoro+/2tVgvna4AcDOBoG+UqaQvsv8+L8SlUm/08L7vhRX3r+THXm/2dDjv2Sn9r8Uj6W/HFdhPwkX0L8FWIe/JzPHPwM1DcDJQ8u/DgE+v82cOr5IofW+Em3Uvv7Cyb4=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000053", + "ACH-000101", + "ACH-000226", + "ACH-000233", + "ACH-000338", + "ACH-000664", + "ACH-000773", + "ACH-001111", + "ACH-001119", + "ACH-001737" + ], + "hoverinfo": "text", + "marker": { + "color": "#FE00CE", + "size": 7 + }, + "mode": "markers", + "name": "Mature T and NK Neoplasms", + "text": [ + "Mature T and NK Neoplasms | ACH-000053", + "Mature T and NK Neoplasms | ACH-000101", + "Mature T and NK Neoplasms | ACH-000226", + "Mature T and NK Neoplasms | ACH-000233", + "Mature T and NK Neoplasms | ACH-000338", + "Mature T and NK Neoplasms | ACH-000664", + "Mature T and NK Neoplasms | ACH-000773", + "Mature T and NK Neoplasms | ACH-001111", + "Mature T and NK Neoplasms | ACH-001119", + "Mature T and NK Neoplasms | ACH-001737" + ], + "type": "scattergl", + "x": { + "bdata": "EWe6P5C9Z0BdeE5AwjM9QJPJvD+sbItATXoLQPlr7j/09zG/8jMfQA==", + "dtype": "f4" + }, + "y": { + "bdata": "7uwIwIumIcDK5v+/HiW7v8fczL6mmhXAb47Xv85/hb9OAzW/aUcuPg==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000054" + ], + "hoverinfo": "text", + "marker": { + "color": "#0DF9FF", + "size": 7 + }, + "mode": "markers", + "name": "Fibrosarcoma", + "text": [ + "Fibrosarcoma | ACH-000054" + ], + "type": "scattergl", + "x": { + "bdata": "DTuBPw==", + "dtype": "f4" + }, + "y": { + "bdata": "fpSPPw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000055", + "ACH-000095", + "ACH-000160", + "ACH-000211", + "ACH-000776", + "ACH-001020", + "ACH-001028", + "ACH-001031", + "ACH-001033", + "ACH-001053", + "ACH-001054", + "ACH-001232", + "ACH-001289", + "ACH-001670", + "ACH-001711" + ], + "hoverinfo": "text", + "marker": { + "color": "#F6F926", + "size": 7 + }, + "mode": "markers", + "name": "Embryonal Tumor", + "text": [ + "Embryonal Tumor | ACH-000055", + "Embryonal Tumor | ACH-000095", + "Embryonal Tumor | ACH-000160", + "Embryonal Tumor | ACH-000211", + "Embryonal Tumor | ACH-000776", + "Embryonal Tumor | ACH-001020", + "Embryonal Tumor | ACH-001028", + "Embryonal Tumor | ACH-001031", + "Embryonal Tumor | ACH-001033", + "Embryonal Tumor | ACH-001053", + "Embryonal Tumor | ACH-001054", + "Embryonal Tumor | ACH-001232", + "Embryonal Tumor | ACH-001289", + "Embryonal Tumor | ACH-001670", + "Embryonal Tumor | ACH-001711" + ], + "type": "scattergl", + "x": { + "bdata": "/esoQHAd9z9/anFAHl5zP3E6BECd5QJA1vFTQCNMY0C6Mdg/3HTSPygGWkDQKFA/TeugPwsmOkBiSA9A", + "dtype": "f4" + }, + "y": { + "bdata": "Q8R1v+p5Lb8gP/Y+C+LtP/W6Qz/CeHU/IU+kvpUT8D6yS+M+6LWbviaXi78FYC5AOGz2vu+Q5T7U2sc+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000070", + "ACH-000151", + "ACH-000782", + "ACH-000922", + "ACH-000938", + "ACH-000960", + "ACH-001484", + "ACH-001520", + "ACH-001669", + "ACH-001735", + "ACH-001736", + "ACH-001993", + "ACH-002059" + ], + "hoverinfo": "text", + "marker": { + "color": "#FF9616", + "size": 7 + }, + "mode": "markers", + "name": "B-Lymphoblastic Leukemia/Lymphoma", + "text": [ + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000070", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000151", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000782", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000922", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000938", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-000960", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001484", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001520", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001669", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001735", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001736", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-001993", + "B-Lymphoblastic Leukemia/Lymphoma | ACH-002059" + ], + "type": "scattergl", + "x": { + "bdata": "DitMQDjJqz/1ZDtAUVFtQEOATUBzyEpA6Xo1QDW7VUBJHm5AC3EhQGJAeUDe6dA/KUE+QA==", + "dtype": "f4" + }, + "y": { + "bdata": "+i4gwBykJcBwwirAq+ZBwC5PWsC1HDPAq8YAwAIsCsDFainAeBA5wOYvRcDGSwrAlaf5vw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000074", + "ACH-000076", + "ACH-000198", + "ACH-000295", + "ACH-000326", + "ACH-000551", + "ACH-000604", + "ACH-000920", + "ACH-000983", + "ACH-002061" + ], + "hoverinfo": "text", + "marker": { + "color": "#479B55", + "size": 7 + }, + "mode": "markers", + "name": "Myeloproliferative Neoplasms", + "text": [ + "Myeloproliferative Neoplasms | ACH-000074", + "Myeloproliferative Neoplasms | ACH-000076", + "Myeloproliferative Neoplasms | ACH-000198", + "Myeloproliferative Neoplasms | ACH-000295", + "Myeloproliferative Neoplasms | ACH-000326", + "Myeloproliferative Neoplasms | ACH-000551", + "Myeloproliferative Neoplasms | ACH-000604", + "Myeloproliferative Neoplasms | ACH-000920", + "Myeloproliferative Neoplasms | ACH-000983", + "Myeloproliferative Neoplasms | ACH-002061" + ], + "type": "scattergl", + "x": { + "bdata": "u1n9P1XPSkA1Y4xAHpSaP8A6X0CWkB1A6Gb9P1Obzj8DFGlADDJEQA==", + "dtype": "f4" + }, + "y": { + "bdata": "WHsbwGzt4L8QWjTAZlPLv25QBcDHQx7AuYDgv8ilFL++ByLAo6L8vw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000077", + "ACH-000583", + "ACH-001197", + "ACH-001642" + ], + "hoverinfo": "text", + "marker": { + "color": "#EEA6FB", + "size": 7 + }, + "mode": "markers", + "name": "Non-Hodgkin Lymphoma", + "text": [ + "Non-Hodgkin Lymphoma | ACH-000077", + "Non-Hodgkin Lymphoma | ACH-000583", + "Non-Hodgkin Lymphoma | ACH-001197", + "Non-Hodgkin Lymphoma | ACH-001642" + ], + "type": "scattergl", + "x": { + "bdata": "k+NUQEUn9cAoSSJABGnVPw==", + "dtype": "f4" + }, + "y": { + "bdata": "vr1nvz1chL4rKPq/i8u3vw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000078", + "ACH-000099", + "ACH-000120", + "ACH-000149", + "ACH-000203", + "ACH-000227", + "ACH-000259", + "ACH-000260", + "ACH-000310", + "ACH-000312", + "ACH-000341", + "ACH-000366", + "ACH-000804", + "ACH-001188", + "ACH-001300", + "ACH-001301", + "ACH-001302", + "ACH-001303", + "ACH-001338", + "ACH-001344", + "ACH-001354", + "ACH-001366", + "ACH-001367", + "ACH-001481", + "ACH-001548", + "ACH-001603", + "ACH-001674", + "ACH-002080", + "ACH-002083", + "ACH-002261", + "ACH-002278", + "ACH-002280", + "ACH-002282", + "ACH-002283", + "ACH-002284", + "ACH-002285", + "ACH-002922" + ], + "hoverinfo": "text", + "marker": { + "color": "#DC587D", + "size": 7 + }, + "mode": "markers", + "name": "Neuroblastoma", + "text": [ + "Neuroblastoma | ACH-000078", + "Neuroblastoma | ACH-000099", + "Neuroblastoma | ACH-000120", + "Neuroblastoma | ACH-000149", + "Neuroblastoma | ACH-000203", + "Neuroblastoma | ACH-000227", + "Neuroblastoma | ACH-000259", + "Neuroblastoma | ACH-000260", + "Neuroblastoma | ACH-000310", + "Neuroblastoma | ACH-000312", + "Neuroblastoma | ACH-000341", + "Neuroblastoma | ACH-000366", + "Neuroblastoma | ACH-000804", + "Neuroblastoma | ACH-001188", + "Neuroblastoma | ACH-001300", + "Neuroblastoma | ACH-001301", + "Neuroblastoma | ACH-001302", + "Neuroblastoma | ACH-001303", + "Neuroblastoma | ACH-001338", + "Neuroblastoma | ACH-001344", + "Neuroblastoma | ACH-001354", + "Neuroblastoma | ACH-001366", + "Neuroblastoma | ACH-001367", + "Neuroblastoma | ACH-001481", + "Neuroblastoma | ACH-001548", + "Neuroblastoma | ACH-001603", + "Neuroblastoma | ACH-001674", + "Neuroblastoma | ACH-002080", + "Neuroblastoma | ACH-002083", + "Neuroblastoma | ACH-002261", + "Neuroblastoma | ACH-002278", + "Neuroblastoma | ACH-002280", + "Neuroblastoma | ACH-002282", + "Neuroblastoma | ACH-002283", + "Neuroblastoma | ACH-002284", + "Neuroblastoma | ACH-002285", + "Neuroblastoma | ACH-002922" + ], + "type": "scattergl", + "x": { + "bdata": "Xm9AP+mTHkDgf30/cRkuQBOtET9j7e+/VONSQHdECUAyo8W/zXc0P92s5b4Xe7E/J3ZVQN/AC0AIbixAewHfvG/VWj/d9lA+YhUnQF9Gij/zJLo/P03zPxpGHkAPO0o/qGo3PwaYoj967c8/ein1wFK5ckBl20JANbMzQCeQIUD1RA9AHxwQQFlI9cDNS6dATmspQA==", + "dtype": "f4" + }, + "y": { + "bdata": "Tdwyv8WvWL9jkEw/xtSfPux4yT46Dmu/iU95vxjGez/qCR2/DuuQv3KPlD5dFsm+9i20vs9z0z7FtJa+UDXmPiHBr743CFy+62XRv5SOnj8rH2i9zNAov8DHGr91irE/LjTvPrNHKb8QadS/BTF8vhITvT9jMm6/qDoOv2V8Rb/C9wK/MsopPzncab5VWSY/+c1Cvw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000082", + "ACH-000359", + "ACH-000364", + "ACH-000410", + "ACH-000748", + "ACH-001001", + "ACH-001526", + "ACH-001715", + "ACH-001814", + "ACH-002067", + "ACH-002069", + "ACH-002471", + "ACH-002834" + ], + "hoverinfo": "text", + "marker": { + "color": "#D626FF", + "size": 7 + }, + "mode": "markers", + "name": "Osteosarcoma", + "text": [ + "Osteosarcoma | ACH-000082", + "Osteosarcoma | ACH-000359", + "Osteosarcoma | ACH-000364", + "Osteosarcoma | ACH-000410", + "Osteosarcoma | ACH-000748", + "Osteosarcoma | ACH-001001", + "Osteosarcoma | ACH-001526", + "Osteosarcoma | ACH-001715", + "Osteosarcoma | ACH-001814", + "Osteosarcoma | ACH-002067", + "Osteosarcoma | ACH-002069", + "Osteosarcoma | ACH-002471", + "Osteosarcoma | ACH-002834" + ], + "type": "scattergl", + "x": { + "bdata": "tqkRwK0axL/2lQdA5suAPzL9DUBoBWFAiAibvjQj+b5AbcS+TBajP6qLgj9bGTQ/qo71wA==", + "dtype": "f4" + }, + "y": { + "bdata": "DXmcP+yRpz++IwNANiqXPz8gN0CgQ6y+UTChP3jguT+JYBZAHyIOP7UaIkBKmbw/SeJavg==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000086", + "ACH-000092", + "ACH-000153", + "ACH-000319", + "ACH-000331", + "ACH-000335", + "ACH-000367", + "ACH-000569", + "ACH-000645", + "ACH-000648", + "ACH-001547", + "ACH-001555", + "ACH-001556", + "ACH-001557", + "ACH-001558", + "ACH-001559", + "ACH-001560", + "ACH-001562", + "ACH-001977", + "ACH-001992", + "ACH-002033" + ], + "hoverinfo": "text", + "marker": { + "color": "#6E899C", + "size": 7 + }, + "mode": "markers", + "name": "Pleural Mesothelioma", + "text": [ + "Pleural Mesothelioma | ACH-000086", + "Pleural Mesothelioma | ACH-000092", + "Pleural Mesothelioma | ACH-000153", + "Pleural Mesothelioma | ACH-000319", + "Pleural Mesothelioma | ACH-000331", + "Pleural Mesothelioma | ACH-000335", + "Pleural Mesothelioma | ACH-000367", + "Pleural Mesothelioma | ACH-000569", + "Pleural Mesothelioma | ACH-000645", + "Pleural Mesothelioma | ACH-000648", + "Pleural Mesothelioma | ACH-001547", + "Pleural Mesothelioma | ACH-001555", + "Pleural Mesothelioma | ACH-001556", + "Pleural Mesothelioma | ACH-001557", + "Pleural Mesothelioma | ACH-001558", + "Pleural Mesothelioma | ACH-001559", + "Pleural Mesothelioma | ACH-001560", + "Pleural Mesothelioma | ACH-001562", + "Pleural Mesothelioma | ACH-001977", + "Pleural Mesothelioma | ACH-001992", + "Pleural Mesothelioma | ACH-002033" + ], + "type": "scattergl", + "x": { + "bdata": "2ScXQOObKr9EWAI97RhwPWrLlj+bpiJAO0r1wCyKjD/Vv1a/VSLXP2qhZj/GUKU/KGH4PwQKrT8UZPXACjr1wF1Z9cCEMPXAL2lJQKNGN0AXSP+/", + "dtype": "f4" + }, + "y": { + "bdata": "iK3GP9RAzz+GvQFA5HQVQF7T3j+CjLE+xWFsvs6ECT9X1Ng/Mkm/P8kNJEDVm/A/c7dRP0VMBUCxDmK+m15xvsy9bL6Ll2u+Eqv/vWZojT8f2Gs+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000090", + "ACH-000115", + "ACH-000956", + "ACH-000977", + "ACH-000979", + "ACH-001422", + "ACH-001627", + "ACH-001648", + "ACH-001649" + ], + "hoverinfo": "text", + "marker": { + "color": "#00B5F7", + "size": 7 + }, + "mode": "markers", + "name": "Prostate Adenocarcinoma", + "text": [ + "Prostate Adenocarcinoma | ACH-000090", + "Prostate Adenocarcinoma | ACH-000115", + "Prostate Adenocarcinoma | ACH-000956", + "Prostate Adenocarcinoma | ACH-000977", + "Prostate Adenocarcinoma | ACH-000979", + "Prostate Adenocarcinoma | ACH-001422", + "Prostate Adenocarcinoma | ACH-001627", + "Prostate Adenocarcinoma | ACH-001648", + "Prostate Adenocarcinoma | ACH-001649" + ], + "type": "scattergl", + "x": { + "bdata": "5niCP7HAFsAfKUI/XY9KQID1pD93MEDAujD1wFUp9cCyY/XA", + "dtype": "f4" + }, + "y": { + "bdata": "q6SdP5k+L78R376/jie9v00E/D7XvsK/vs98vkiAfL4HQGa+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000096", + "ACH-000172", + "ACH-000533", + "ACH-000597", + "ACH-001099", + "ACH-001128", + "ACH-001211", + "ACH-001212", + "ACH-001532" + ], + "hoverinfo": "text", + "marker": { + "color": "#B68E00", + "size": 7 + }, + "mode": "markers", + "name": "Rhabdoid Cancer", + "text": [ + "Rhabdoid Cancer | ACH-000096", + "Rhabdoid Cancer | ACH-000172", + "Rhabdoid Cancer | ACH-000533", + "Rhabdoid Cancer | ACH-000597", + "Rhabdoid Cancer | ACH-001099", + "Rhabdoid Cancer | ACH-001128", + "Rhabdoid Cancer | ACH-001211", + "Rhabdoid Cancer | ACH-001212", + "Rhabdoid Cancer | ACH-001532" + ], + "type": "scattergl", + "x": { + "bdata": "gQ/7Pxz6AEDGinVAxe0vQHBzeECgdxNAZk0kQM7A7T+J4W9A", + "dtype": "f4" + }, + "y": { + "bdata": "eH2zPnlXgD/lvKY+JwteP1q2Nj+9qwc/p3fuPmuwpz/pf/m+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000100", + "ACH-000169", + "ACH-000607", + "ACH-000833", + "ACH-001050", + "ACH-001096", + "ACH-001184", + "ACH-001196", + "ACH-001740", + "ACH-001745", + "ACH-001750", + "ACH-001765", + "ACH-002048" + ], + "hoverinfo": "text", + "marker": { + "color": "#C9FBE5", + "size": 7 + }, + "mode": "markers", + "name": "Rhabdomyosarcoma", + "text": [ + "Rhabdomyosarcoma | ACH-000100", + "Rhabdomyosarcoma | ACH-000169", + "Rhabdomyosarcoma | ACH-000607", + "Rhabdomyosarcoma | ACH-000833", + "Rhabdomyosarcoma | ACH-001050", + "Rhabdomyosarcoma | ACH-001096", + "Rhabdomyosarcoma | ACH-001184", + "Rhabdomyosarcoma | ACH-001196", + "Rhabdomyosarcoma | ACH-001740", + "Rhabdomyosarcoma | ACH-001745", + "Rhabdomyosarcoma | ACH-001750", + "Rhabdomyosarcoma | ACH-001765", + "Rhabdomyosarcoma | ACH-002048" + ], + "type": "scattergl", + "x": { + "bdata": "OQcIQCJnGUAkqeA/+v8aQIslaD8NtFdAiPE9QNgvN0DlANI/FFUPQL5i/z9qezxAZBxsQA==", + "dtype": "f4" + }, + "y": { + "bdata": "SakQv5iQeD7fAQ4/uQibva5RL0DuAna+UnQkv0xqGz+2F949OFOOvivajD8QylK/mycWvg==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000108", + "ACH-000685" + ], + "hoverinfo": "text", + "marker": { + "color": "#FF0092", + "size": 7 + }, + "mode": "markers", + "name": "Adenosquamous Carcinoma of the Pancreas", + "text": [ + "Adenosquamous Carcinoma of the Pancreas | ACH-000108", + "Adenosquamous Carcinoma of the Pancreas | ACH-000685" + ], + "type": "scattergl", + "x": { + "bdata": "Q21bv+xvOkA=", + "dtype": "f4" + }, + "y": { + "bdata": "YnGZPkp3wz8=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000133", + "ACH-001310", + "ACH-001453", + "ACH-002210", + "ACH-002247", + "ACH-002462", + "ACH-002463", + "ACH-002464", + "ACH-002465", + "ACH-002467" + ], + "hoverinfo": "text", + "marker": { + "color": "#22FFA7", + "size": 7 + }, + "mode": "markers", + "name": "Non-Cancerous", + "text": [ + "Non-Cancerous | ACH-000133", + "Non-Cancerous | ACH-001310", + "Non-Cancerous | ACH-001453", + "Non-Cancerous | ACH-002210", + "Non-Cancerous | ACH-002247", + "Non-Cancerous | ACH-002462", + "Non-Cancerous | ACH-002463", + "Non-Cancerous | ACH-002464", + "Non-Cancerous | ACH-002465", + "Non-Cancerous | ACH-002467" + ], + "type": "scattergl", + "x": { + "bdata": "inBOP8U49cBENfg/ORyPQFk79cBSfPXAZVn1wIes9cA3ZfXAyFT1wA==", + "dtype": "f4" + }, + "y": { + "bdata": "WREnQHe2db7Lvq8/INL9v0cbdr7rFmG+UjtjvsLDWb63JGy+lztsvg==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000141", + "ACH-001607", + "ACH-001619", + "ACH-001850", + "ACH-001861", + "ACH-001961" + ], + "hoverinfo": "text", + "marker": { + "color": "#E3EE9E", + "size": 7 + }, + "mode": "markers", + "name": "Intracholecystic Papillary Neoplasm", + "text": [ + "Intracholecystic Papillary Neoplasm | ACH-000141", + "Intracholecystic Papillary Neoplasm | ACH-001607", + "Intracholecystic Papillary Neoplasm | ACH-001619", + "Intracholecystic Papillary Neoplasm | ACH-001850", + "Intracholecystic Papillary Neoplasm | ACH-001861", + "Intracholecystic Papillary Neoplasm | ACH-001961" + ], + "type": "scattergl", + "x": { + "bdata": "ho31wPBPLkBRPsK+qDdCQGd09cDhdyVA", + "dtype": "f4" + }, + "y": { + "bdata": "CmZTvgIhHb9T5aU/vgpHPrcRZr5dMpi+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000145", + "ACH-000505", + "ACH-002785" + ], + "hoverinfo": "text", + "marker": { + "color": "#86CE00", + "size": 7 + }, + "mode": "markers", + "name": "Leiomyosarcoma", + "text": [ + "Leiomyosarcoma | ACH-000145", + "Leiomyosarcoma | ACH-000505", + "Leiomyosarcoma | ACH-002785" + ], + "type": "scattergl", + "x": { + "bdata": "mskwv9vcwb+ghI+/", + "dtype": "f4" + }, + "y": { + "bdata": "a0XnP4YXxz+YzK4+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000159", + "ACH-000189", + "ACH-000234", + "ACH-000246", + "ACH-000250", + "ACH-000262", + "ACH-000272", + "ACH-000313", + "ACH-000317", + "ACH-000375", + "ACH-000385", + "ACH-000411", + "ACH-000433", + "ACH-000459", + "ACH-000484", + "ACH-000495", + "ACH-000649", + "ACH-000684", + "ACH-000709", + "ACH-000792", + "ACH-000907", + "ACH-001163", + "ACH-001194", + "ACH-001398", + "ACH-001687", + "ACH-001688", + "ACH-002150", + "ACH-002189", + "ACH-002533" + ], + "hoverinfo": "text", + "marker": { + "color": "#BC7196", + "size": 7 + }, + "mode": "markers", + "name": "Renal Cell Carcinoma", + "text": [ + "Renal Cell Carcinoma | ACH-000159", + "Renal Cell Carcinoma | ACH-000189", + "Renal Cell Carcinoma | ACH-000234", + "Renal Cell Carcinoma | ACH-000246", + "Renal Cell Carcinoma | ACH-000250", + "Renal Cell Carcinoma | ACH-000262", + "Renal Cell Carcinoma | ACH-000272", + "Renal Cell Carcinoma | ACH-000313", + "Renal Cell Carcinoma | ACH-000317", + "Renal Cell Carcinoma | ACH-000375", + "Renal Cell Carcinoma | ACH-000385", + "Renal Cell Carcinoma | ACH-000411", + "Renal Cell Carcinoma | ACH-000433", + "Renal Cell Carcinoma | ACH-000459", + "Renal Cell Carcinoma | ACH-000484", + "Renal Cell Carcinoma | ACH-000495", + "Renal Cell Carcinoma | ACH-000649", + "Renal Cell Carcinoma | ACH-000684", + "Renal Cell Carcinoma | ACH-000709", + "Renal Cell Carcinoma | ACH-000792", + "Renal Cell Carcinoma | ACH-000907", + "Renal Cell Carcinoma | ACH-001163", + "Renal Cell Carcinoma | ACH-001194", + "Renal Cell Carcinoma | ACH-001398", + "Renal Cell Carcinoma | ACH-001687", + "Renal Cell Carcinoma | ACH-001688", + "Renal Cell Carcinoma | ACH-002150", + "Renal Cell Carcinoma | ACH-002189", + "Renal Cell Carcinoma | ACH-002533" + ], + "type": "scattergl", + "x": { + "bdata": "SJ0vv4Bo9cDFbNi+iVf1wGxD9cCKVfXA04b1wGoBmr9Oe/XAl+ZOQPRrnT+1NQRAL9r9PSSwlsBzjPXA4JUSPgVOG0BVBV4/x9B8vwLmyD9RTfS/W3OBPxKX9cD6TCy+Azv1wGeS9cBgSfXAhvkXwCjzVUA=", + "dtype": "f4" + }, + "y": { + "bdata": "EfAeP/DXVr7SkvU/Z5tivtGtZL4hmFe+1p5cviFWsj/q1GO+UMW9PNC9vT8zRtc/chD2P+D62b6EeGO+5J/sPz6o8z9FDBRAjsmxP5beRUADrABA1CWcv7bySL5WTu8+VcVovui+Z74FjWy+VZFzPzt0nrs=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000163", + "ACH-000181", + "ACH-000188", + "ACH-000207", + "ACH-000228", + "ACH-000238", + "ACH-000415", + "ACH-000472", + "ACH-000500", + "ACH-000503", + "ACH-000518", + "ACH-000546", + "ACH-000548", + "ACH-000549", + "ACH-000606", + "ACH-000618", + "ACH-000619", + "ACH-000630", + "ACH-000682", + "ACH-000732", + "ACH-000735", + "ACH-000740", + "ACH-000762", + "ACH-000771", + "ACH-000778", + "ACH-000794", + "ACH-000832", + "ACH-000836", + "ACH-000846", + "ACH-001228", + "ACH-001229", + "ACH-001331", + "ACH-001332", + "ACH-001346", + "ACH-001347", + "ACH-001385", + "ACH-001509", + "ACH-001510", + "ACH-001511", + "ACH-001542", + "ACH-001543", + "ACH-001625", + "ACH-001626", + "ACH-001641", + "ACH-001675", + "ACH-001690", + "ACH-001691", + "ACH-001692", + "ACH-001694", + "ACH-001695", + "ACH-001696", + "ACH-001698", + "ACH-001699", + "ACH-001701", + "ACH-002029", + "ACH-002030", + "ACH-002042", + "ACH-002043", + "ACH-002044", + "ACH-002045", + "ACH-002212", + "ACH-002249", + "ACH-002250", + "ACH-002251", + "ACH-002265", + "ACH-002294", + "ACH-002295", + "ACH-002296", + "ACH-002297", + "ACH-002298", + "ACH-002305" + ], + "hoverinfo": "text", + "marker": { + "color": "#7E7DCD", + "size": 7 + }, + "mode": "markers", + "name": "Head and Neck Squamous Cell Carcinoma", + "text": [ + "Head and Neck Squamous Cell Carcinoma | ACH-000163", + "Head and Neck Squamous Cell Carcinoma | ACH-000181", + "Head and Neck Squamous Cell Carcinoma | ACH-000188", + "Head and Neck Squamous Cell Carcinoma | ACH-000207", + "Head and Neck Squamous Cell Carcinoma | ACH-000228", + "Head and Neck Squamous Cell Carcinoma | ACH-000238", + "Head and Neck Squamous Cell Carcinoma | ACH-000415", + "Head and Neck Squamous Cell Carcinoma | ACH-000472", + "Head and Neck Squamous Cell Carcinoma | ACH-000500", + "Head and Neck Squamous Cell Carcinoma | ACH-000503", + "Head and Neck Squamous Cell Carcinoma | ACH-000518", + "Head and Neck Squamous Cell Carcinoma | ACH-000546", + "Head and Neck Squamous Cell Carcinoma | ACH-000548", + "Head and Neck Squamous Cell Carcinoma | ACH-000549", + "Head and Neck Squamous Cell Carcinoma | ACH-000606", + "Head and Neck Squamous Cell Carcinoma | ACH-000618", + "Head and Neck Squamous Cell Carcinoma | ACH-000619", + "Head and Neck Squamous Cell Carcinoma | ACH-000630", + "Head and Neck Squamous Cell Carcinoma | ACH-000682", + "Head and Neck Squamous Cell Carcinoma | ACH-000732", + "Head and Neck Squamous Cell Carcinoma | ACH-000735", + "Head and Neck Squamous Cell Carcinoma | ACH-000740", + "Head and Neck Squamous Cell Carcinoma | ACH-000762", + "Head and Neck Squamous Cell Carcinoma | ACH-000771", + "Head and Neck Squamous Cell Carcinoma | ACH-000778", + "Head and Neck Squamous Cell Carcinoma | ACH-000794", + "Head and Neck Squamous Cell Carcinoma | ACH-000832", + "Head and Neck Squamous Cell Carcinoma | ACH-000836", + "Head and Neck Squamous Cell Carcinoma | ACH-000846", + "Head and Neck Squamous Cell Carcinoma | ACH-001228", + "Head and Neck Squamous Cell Carcinoma | ACH-001229", + "Head and Neck Squamous Cell Carcinoma | ACH-001331", + "Head and Neck Squamous Cell Carcinoma | ACH-001332", + "Head and Neck Squamous Cell Carcinoma | ACH-001346", + "Head and Neck Squamous Cell Carcinoma | ACH-001347", + "Head and Neck Squamous Cell Carcinoma | ACH-001385", + "Head and Neck Squamous Cell Carcinoma | ACH-001509", + "Head and Neck Squamous Cell Carcinoma | ACH-001510", + "Head and Neck Squamous Cell Carcinoma | ACH-001511", + "Head and Neck Squamous Cell Carcinoma | ACH-001542", + "Head and Neck Squamous Cell Carcinoma | ACH-001543", + "Head and Neck Squamous Cell Carcinoma | ACH-001625", + "Head and Neck Squamous Cell Carcinoma | ACH-001626", + "Head and Neck Squamous Cell Carcinoma | ACH-001641", + "Head and Neck Squamous Cell Carcinoma | ACH-001675", + "Head and Neck Squamous Cell Carcinoma | ACH-001690", + "Head and Neck Squamous Cell Carcinoma | ACH-001691", + "Head and Neck Squamous Cell Carcinoma | ACH-001692", + "Head and Neck Squamous Cell Carcinoma | ACH-001694", + "Head and Neck Squamous Cell Carcinoma | ACH-001695", + "Head and Neck Squamous Cell Carcinoma | ACH-001696", + "Head and Neck Squamous Cell Carcinoma | ACH-001698", + "Head and Neck Squamous Cell Carcinoma | ACH-001699", + "Head and Neck Squamous Cell Carcinoma | ACH-001701", + "Head and Neck Squamous Cell Carcinoma | ACH-002029", + "Head and Neck Squamous Cell Carcinoma | ACH-002030", + "Head and Neck Squamous Cell Carcinoma | ACH-002042", + "Head and Neck Squamous Cell Carcinoma | ACH-002043", + "Head and Neck Squamous Cell Carcinoma | ACH-002044", + "Head and Neck Squamous Cell Carcinoma | ACH-002045", + "Head and Neck Squamous Cell Carcinoma | ACH-002212", + "Head and Neck Squamous Cell Carcinoma | ACH-002249", + "Head and Neck Squamous Cell Carcinoma | ACH-002250", + "Head and Neck Squamous Cell Carcinoma | ACH-002251", + "Head and Neck Squamous Cell Carcinoma | ACH-002265", + "Head and Neck Squamous Cell Carcinoma | ACH-002294", + "Head and Neck Squamous Cell Carcinoma | ACH-002295", + "Head and Neck Squamous Cell Carcinoma | ACH-002296", + "Head and Neck Squamous Cell Carcinoma | ACH-002297", + "Head and Neck Squamous Cell Carcinoma | ACH-002298", + "Head and Neck Squamous Cell Carcinoma | ACH-002305" + ], + "type": "scattergl", + "x": { + "bdata": "3LxePzs2AkDYNBZA+lL1wDlf9cD9IN0/uG/1wIUzjT5zSDg/zm/1wL7VY0Bg30tARd3qPgmFCkBcXyJA88tuQKq4XEAk+RFAveJBQNyb6T9wpwBA/t6/P7cR9j+HYvXAZ4AkvXngOUC5l5NA6XwbQASrbEAaAlG+RkHePzp19cCMePXAoyITQPDxGkDiWlxAw2eWP7UjFEDbZjU+QUqDQNjSD0Ao7yq/znubv61T9cA99f4/NslPQCzQXD+MwU9Ac0suQCLqD0AM+B1AHW8AQAuZcEA0uCVACkCAQN/ELkDscoa+Y5AjQGycc0AV2DJAuGb1wJABd0BCc4Q/ScVMQAlF9cA/rSpAiuNbP9ygjEDtAGFAF3x6QD1l9cA=", + "dtype": "f4" + }, + "y": { + "bdata": 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ACH-002041" + ], + "type": "scattergl", + "x": { + "bdata": "QZrQPzuE8j/0Zco+ti6Sv8VlCcC1eo4/Ds4YPw==", + "dtype": "f4" + }, + "y": { + "bdata": "vw3SP5GYyT/AZSZAp5hOP/nwk72qnaA/hGEbQA==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000182", + "ACH-000377", + "ACH-001862", + "ACH-002023" + ], + "hoverinfo": "text", + "marker": { + "color": "#E48F72", + "size": 7 + }, + "mode": "markers", + "name": "Ampullary Carcinoma", + "text": [ + "Ampullary Carcinoma | ACH-000182", + "Ampullary Carcinoma | ACH-000377", + "Ampullary Carcinoma | ACH-001862", + "Ampullary Carcinoma | ACH-002023" + ], + "type": "scattergl", + "x": { + "bdata": "okP1wF9K9cCtYQK/I6ggQA==", + "dtype": "f4" + }, + "y": { + "bdata": "+rB/vp1Rbb5jYXg+ulJgvw==", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000187", + "ACH-000257", + "ACH-000290", + "ACH-000292", + "ACH-000355", + "ACH-000431", + "ACH-000514", + "ACH-000515", + "ACH-000525", + "ACH-000559", + "ACH-000639", + "ACH-000695", + "ACH-000698", + "ACH-000749", + "ACH-000767", + "ACH-000775", + "ACH-000790", + "ACH-000800", + "ACH-000866", + "ACH-000871", + "ACH-000890", + "ACH-000912", + "ACH-001386", + "ACH-001549", + "ACH-002051", + "ACH-002052", + "ACH-002077" + ], + "hoverinfo": "text", + "marker": { + "color": "#2E91E5", + "size": 7 + }, + "mode": "markers", + "name": "Lung Neuroendocrine Tumor", + "text": [ + "Lung Neuroendocrine Tumor | ACH-000187", + "Lung Neuroendocrine Tumor | ACH-000257", + "Lung Neuroendocrine Tumor | ACH-000290", + "Lung Neuroendocrine Tumor | ACH-000292", + "Lung Neuroendocrine Tumor | ACH-000355", + "Lung Neuroendocrine Tumor | ACH-000431", + "Lung Neuroendocrine Tumor | ACH-000514", + "Lung Neuroendocrine Tumor | ACH-000515", + "Lung Neuroendocrine Tumor | ACH-000525", + "Lung Neuroendocrine Tumor | ACH-000559", + "Lung Neuroendocrine Tumor | ACH-000639", + "Lung Neuroendocrine Tumor | ACH-000695", + "Lung Neuroendocrine Tumor | ACH-000698", + "Lung Neuroendocrine Tumor | ACH-000749", + "Lung Neuroendocrine Tumor | ACH-000767", + "Lung Neuroendocrine Tumor | ACH-000775", + "Lung Neuroendocrine Tumor | ACH-000790", + "Lung Neuroendocrine Tumor | ACH-000800", + "Lung Neuroendocrine Tumor | ACH-000866", + "Lung Neuroendocrine Tumor | ACH-000871", + "Lung Neuroendocrine Tumor | ACH-000890", + "Lung Neuroendocrine Tumor | ACH-000912", + "Lung Neuroendocrine Tumor | ACH-001386", + "Lung Neuroendocrine Tumor | ACH-001549", + "Lung Neuroendocrine Tumor | ACH-002051", + "Lung Neuroendocrine Tumor | ACH-002052", + "Lung Neuroendocrine Tumor | ACH-002077" + ], + "type": "scattergl", + "x": { + "bdata": "v60WP1hRub4G5NQ+k1ZWQNpHVECeBZE7p+yev4/PDEBR15w/uLiAvw4kOUDpLlG/k4riPxzn6j+RSKG/inv7P39cE0BmUQBAeypAQADJOkA8Olk/LC0pQMQi3704ydE+Cgvzv96bf7/PwYa/", + "dtype": "f4" + }, + "y": { + "bdata": "iZ8pwNhWvr840gXA1OmiPhRzBr8wiW+/pfLav5u6X7/r2bG/AGiuv1SXDsDVg36/g6UewLpKa77t1/m/Ljf4vrkQoL9JjFA/cnazv12ynr8uywdAcY8HP391w79Adau/u/jKv+rm6L+rpWS/", + "dtype": "f4" + } + }, + { + "customdata": [ + 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"Endometrial Carcinoma | ACH-000941", + "Endometrial Carcinoma | ACH-000946", + "Endometrial Carcinoma | ACH-000961", + "Endometrial Carcinoma | ACH-000965", + "Endometrial Carcinoma | ACH-000972", + "Endometrial Carcinoma | ACH-000974", + "Endometrial Carcinoma | ACH-000978", + "Endometrial Carcinoma | ACH-000984", + "Endometrial Carcinoma | ACH-000988", + "Endometrial Carcinoma | ACH-000993", + "Endometrial Carcinoma | ACH-000994", + "Endometrial Carcinoma | ACH-000996", + "Endometrial Carcinoma | ACH-001495", + "Endometrial Carcinoma | ACH-001517", + "Endometrial Carcinoma | ACH-001518", + "Endometrial Carcinoma | ACH-002026", + "Endometrial Carcinoma | ACH-002027", + "Endometrial Carcinoma | ACH-002046" + ], + "type": "scattergl", + "x": { + "bdata": "Y1IewEPDAsDLISE+GpczP8fQiD82IAs+x1b1wP/pdD/V/CJAhF9KQDL5jb/V0QtAfgs4QD2jcEDKcPXAPfMxQJVcbj+yhW2/S9tOP6vEhz+CZ/XAZF3RPp0kHL8FHSjAQqf1wLxyKkD09co/oaoSPw==", + "dtype": "f4" + }, + "y": { + "bdata": 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ACH-001538", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001673", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001834", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001835", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001836", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001838", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001839", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001841", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001842", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001843", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001844", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001848", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001849", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001852", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001856", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001857", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001858", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001863", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001864", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001959", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001960", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001997", + "Intraductal Papillary Neoplasm of the Bile Duct | ACH-002647" + ], + "type": "scattergl", + "x": { + "bdata": "8Fv1wOZT9cCSKvXAEcSSP1aw3D95UMU/N0IMQHi1RUDXfPXAu4j1wNqF9cB3e/XAl2L1wOtV9cCy9Xc/gWb1wA5o9cAmb/XAkyL1wIbubUC1DbM/IVLcP4v9E0A3jPXArScqP2TZcUAPKiNAMVT1wA5JG0A=", + "dtype": "f4" + }, + "y": { + "bdata": "vAhrvoXAYb7Oe3G+GCm8PqQLHz87R+I//cvuP3889b/jRk++TsBfvm80W77v4ma+DRdnvlkdar6qXrY/9ANkvi+Tcb4HHVy+Jv1+voETWT7hS6I/Lqy+vR57kj60gF6+zyPuvhYE1rvh3LU/Wixnvlx9gj8=", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000217", + "ACH-000221", + "ACH-000316", + "ACH-000361", + 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Carcinoma | ACH-000493", + "Hepatocellular Carcinoma | ACH-000537", + "Hepatocellular Carcinoma | ACH-000577", + "Hepatocellular Carcinoma | ACH-000620", + "Hepatocellular Carcinoma | ACH-000734", + "Hepatocellular Carcinoma | ACH-000848", + "Hepatocellular Carcinoma | ACH-001318", + "Hepatocellular Carcinoma | ACH-002523" + ], + "type": "scattergl", + "x": { + "bdata": "JCnUP9pFVUBKWcw/YsavP26grL+hdeG+UjkPQJvqnj851AxAj1wSv9meQT71JyxARB9tvyHdUT+m37c//D3zv0Tloj9Z/jxA7DtEQKam9T+iDPQ/", + "dtype": "f4" + }, + "y": { + "bdata": "4f8QPtPO377vozxAypmIP/Hf6z8NK+o/y7Y+QGxPDEC7JC09weWlPgX8/D9Ey4A/KxLrP4hbDECtX8Y/uH+mP25HgL6yqTS/Bpc6vxlLVD5iA0BA", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000305", + "ACH-000318", + "ACH-000408", + "ACH-000452", + "ACH-000488", + "ACH-000544", + "ACH-000561", + "ACH-000605", + "ACH-000637", + "ACH-000647", + "ACH-000693", + "ACH-000694", + "ACH-000717", + "ACH-000777", + "ACH-000784", + "ACH-000809", + "ACH-000823", + "ACH-000824", + "ACH-000855", + 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Squamous Cell Carcinoma | ACH-000784", + "Esophageal Squamous Cell Carcinoma | ACH-000809", + "Esophageal Squamous Cell Carcinoma | ACH-000823", + "Esophageal Squamous Cell Carcinoma | ACH-000824", + "Esophageal Squamous Cell Carcinoma | ACH-000855", + "Esophageal Squamous Cell Carcinoma | ACH-000865", + "Esophageal Squamous Cell Carcinoma | ACH-000873", + "Esophageal Squamous Cell Carcinoma | ACH-000917", + "Esophageal Squamous Cell Carcinoma | ACH-002243", + "Esophageal Squamous Cell Carcinoma | ACH-002263" + ], + "type": "scattergl", + "x": { + "bdata": "B89eP+s5JUCKxjlAUiRRP+F/eEC+5jdAqmXiP2Tb2j99/Lo/69QfPRltgUAGHBpA1aqqP/fCMEC9HChANmlmQHGvP0DdxBVA1VddQAYcQ0CI4VFAyRIsQLJmEEAtSD1A", + "dtype": "f4" + }, + "y": { + "bdata": "7Ba9Pnq/kz5m/qk+/P2XP1BuCr94QFs/67Hgvvr5Kz9wFqc/ELxHvdgVLT4vTHE+mKBDP/JiDz8mY5s+urSmvgSfC77hh0c/E+voPkTflz9Jb9K+bzYmvwxPoj98w/e+", + "dtype": "f4" + } + }, + { + "customdata": [ + "ACH-000456" + ], + "hoverinfo": "text", + "marker": { + "color": "#B68100", + 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"color": "lightgrey" + }, + { + "color": "lightgrey" + }, + { + "color": "lightgrey" + }, + { + "color": "lightgrey" + }, + { + "color": "lightgrey" + }, + { + "color": "lightgrey" + }, + { + "color": "lightgrey" + }, + { + "color": "lightgrey" + }, + { + "color": "lightgrey" + }, + { + "color": "lightgrey" + }, + { + "color": "lightgrey" + }, + { + "color": "lightgrey" + }, + { + "color": "#F6F926" + } + ], + "visible": [ + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true, + true + ] + }, + { + "title": "PCA Highlighted: Salivary Carcinoma" + } + ], + "label": "Salivary Carcinoma", + "method": "update" + } + ], + "direction": "down", + "showactive": true, + "x": 1.15, + "xanchor": "left", + "y": 1.15, + "yanchor": "top" + } + ], + "width": 1500, + "xaxis": { + "title": { + "text": "PCA1" + } + }, + "yaxis": { + "title": { + "text": "PCA2" + } + } + } + } + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "92e3889c12d5473f886a52d78b22ca39", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Output()" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Assuming combined_df is your full dataset\n", + "reactome_fig, reactome_out = make_dropdown_pca_with_selection(\n", + " reactome_matrix, \"PCA: Reactome Subset\"\n", + ")\n", + "corum_fig, corum_out = make_dropdown_pca_with_selection(\n", + " corum_matrix, \"PCA: CORUM Subset\"\n", + ")\n", + "drug_fig, drug_out = make_dropdown_pca_with_selection(drug_matrix, \"PCA: Drug Subset\")\n", + "\n", + "# Show plots\n", + "reactome_fig.show()\n", + "display(reactome_out)\n", + "\n", + "corum_fig.show()\n", + "display(corum_out)\n", + "\n", + "drug_fig.show()\n", + "display(drug_out)\n", + "\n", + "# Save HTMLs\n", + "reactome_fig.write_html(\"pca_reactome.html\")\n", + "corum_fig.write_html(\"pca_corum.html\")\n", + "drug_fig.write_html(\"pca_drug.html\")" + ] + }, + { + "cell_type": "markdown", + "id": "d65a9394", + "metadata": {}, + "source": [ + "## spider plots" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "529ca84c", + "metadata": {}, + "outputs": [], + "source": [ + "import textwrap\n", + "\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import pandas as pd" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "3a41344d", + "metadata": {}, + "outputs": [], + "source": [ + "model_ids = [\"ACH-000323\", \"ACH-002083\", \"ACH-002228\"]\n", + "files = {\n", + " \"Reactome Pathways\": \"../5.drug-dependency/results/all_reactome_results.parquet\",\n", + " \"CORUM Complexes\": \"../5.drug-dependency/results/all_corum_results.parquet\",\n", + " \"Drug Responses\": \"../5.drug-dependency/results/all_drug_results.parquet\",\n", + "}\n", + "# Adjust these if your column names differ\n", + "feature_colnames = {\n", + " \"Reactome Pathways\": \"reactome_pathway\",\n", + " \"CORUM Complexes\": \"reactome_pathway\",\n", + " \"Drug Responses\": \"name\",\n", + "}\n", + "score_col = \"pathway_score\"\n", + "\n", + "model_colors = {\n", + " \"ACH-000323\": \"#00FFFF\", # cyan\n", + " \"ACH-002083\": \"#FF69B4\", # pink\n", + " \"ACH-002228\": \"#800080\", # purple\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "aa291f2e", + "metadata": {}, + "outputs": [], + "source": [ + "def clean_label(x: str) -> str:\n", + " \"\"\"\n", + " Clean or override specific long labels before truncation.\n", + " \"\"\"\n", + " # Polymerase switching\n", + " if \"Polymerase Switching\" in x:\n", + " return \"Polymerase Switching\"\n", + "\n", + " # Negative MET regulation\n", + " if \"Negative Regulation Of MET\" in x or \"Negative Regulation of MET\" in x:\n", + " return \"Negative MET Regulation\"\n", + "\n", + " return truncate_label(x)\n", + "\n", + "\n", + "def truncate_label(\n", + " label: str,\n", + " max_chars_per_line: int = 22,\n", + " max_total_words: int = 4,\n", + " max_lines: int = 2,\n", + ") -> str:\n", + " \"\"\"\n", + " Truncate a label according to character and line limits.\n", + " \"\"\"\n", + " words = label.split()\n", + " short = \" \".join(words[:max_total_words])\n", + "\n", + " # Wrap\n", + " lines = textwrap.wrap(short, width=max_chars_per_line)\n", + "\n", + " # clamp to max lines\n", + " if len(lines) > max_lines:\n", + " lines = lines[:max_lines]\n", + "\n", + " wrapped = \"\\n\".join(lines)\n", + "\n", + " # Determine if truncated\n", + " if len(words) > max_total_words or (\n", + " len(lines) >= max_lines\n", + " and len(lines) < len(textwrap.wrap(short, width=max_chars_per_line))\n", + " ):\n", + " wrapped += \"...\"\n", + "\n", + " return wrapped\n", + "\n", + "\n", + "def place_labels_polar(ax, angles, labels, radius: float) -> None:\n", + " \"\"\"\n", + " Place labels around a polar plot at a given radius.\n", + " \"\"\"\n", + " for angle, label in zip(angles[:-1], labels):\n", + " r = radius\n", + "\n", + " # left / right alignment\n", + " if 0 <= angle <= np.pi / 2 or 3 * np.pi / 2 <= angle <= 2 * np.pi:\n", + " ha = \"left\"\n", + " else:\n", + " ha = \"right\"\n", + "\n", + " ax.text(\n", + " angle, r, label, fontsize=9, color=\"black\", ha=ha, va=\"center\", wrap=True\n", + " )\n", + "\n", + " return None\n", + "\n", + "\n", + "def make_radar(\n", + " ax,\n", + " df: pd.DataFrame,\n", + " feature_col: str,\n", + " title: str,\n", + " global_max: float,\n", + " num_circles: int = 5,\n", + ") -> None:\n", + " \"\"\"\n", + " Draw a radar plot on an existing polar matplotlib axis.\n", + " \"\"\"\n", + " df = df[df[\"ModelID\"].isin(model_ids)].copy()\n", + "\n", + " # Top 5 per model, union of all\n", + " top_by_model = (\n", + " df.groupby(\"ModelID\", group_keys=False)\n", + " .apply(lambda x: x.nlargest(5, score_col))\n", + " .reset_index(drop=True)\n", + " )\n", + " top_features = top_by_model[feature_col].drop_duplicates().tolist()\n", + " n_vars = len(top_features)\n", + " labels = [clean_label(x) for x in top_features]\n", + "\n", + " # Angles\n", + " angles = np.linspace(0, 2 * np.pi, n_vars, endpoint=False).tolist()\n", + " angles += [angles[0]]\n", + "\n", + " # Reference circles\n", + " circle_levels = np.linspace(0, global_max, num_circles + 1)[1:]\n", + " for r in circle_levels:\n", + " circle_vals = [r] * (n_vars + 1)\n", + " ax.plot(\n", + " angles, circle_vals, color=\"grey\", linestyle=\"--\", linewidth=1, zorder=0\n", + " )\n", + "\n", + " # Plot each model\n", + " for mid in model_ids:\n", + " subset = df[df[\"ModelID\"] == mid]\n", + "\n", + " merged = pd.DataFrame({feature_col: top_features}).merge(\n", + " subset[[feature_col, score_col]], on=feature_col, how=\"left\"\n", + " )\n", + "\n", + " values = merged[score_col].fillna(0).tolist()\n", + " values += [values[0]]\n", + "\n", + " ax.plot(angles, values, color=model_colors[mid], linewidth=3, label=mid)\n", + " ax.scatter(\n", + " angles, values, color=model_colors[mid], s=30, edgecolor=\"black\", zorder=5\n", + " )\n", + "\n", + " # Axis styling\n", + " ax.set_ylim(0, global_max * 1.25)\n", + " ax.set_xticks([])\n", + " ax.set_yticks([])\n", + " ax.set_aspect(\"equal\")\n", + "\n", + " # Labels\n", + " label_radius = global_max * 1.4\n", + " place_labels_polar(ax, angles, labels, label_radius)\n", + "\n", + " # Title\n", + " ax.set_title(title, fontsize=18, pad=30, fontweight=\"bold\", y=1)\n", + "\n", + " return None" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "2ced4797", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[Index(['ModelID', 'model', 'latent_dim_total', 'init', 'seed',\n", + " 'OncotreePrimaryDisease', 'z', 'latent_score', 'reactome_pathway',\n", + " 'nes_score', 'pathway_score'],\n", + " dtype='str'),\n", + " Index(['ModelID', 'model', 'latent_dim_total', 'init', 'seed',\n", + " 'OncotreePrimaryDisease', 'z', 'latent_score', 'reactome_pathway',\n", + " 'gsea_es_score', 'pathway_score'],\n", + " dtype='str'),\n", + " Index(['ModelID', 'model', 'latent_dim_total', 'init', 'seed',\n", + " 'OncotreePrimaryDisease', 'z', 'latent_score', 'name',\n", + " 'pearson_correlation', 'pathway_score'],\n", + " dtype='str')]" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "[df.columns for df in dfs.values()]" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "dd6645ac", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
    " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "global_max = 0\n", + "dfs = {}\n", + "for name, file in files.items():\n", + " df = pd.read_parquet(file)\n", + " dfs[name] = df\n", + " if df[score_col].max() > global_max:\n", + " global_max = df[score_col].max()\n", + "\n", + "# --- Create one combined figure ---\n", + "fig, axes = plt.subplots(3, 1, figsize=(18, 12), subplot_kw=dict(polar=True))\n", + "\n", + "for ax, (title, df) in zip(axes, dfs.items()):\n", + " make_radar(ax, df, feature_colnames[title], title, global_max)\n", + "\n", + "# Shared legend (one for all)\n", + "handles, labels = axes[0].get_legend_handles_labels()\n", + "\n", + "fig.legend(\n", + " handles,\n", + " labels,\n", + " loc=\"lower center\",\n", + " ncol=3,\n", + " fontsize=12,\n", + " frameon=False,\n", + " bbox_to_anchor=(0.5, -0.05),\n", + ")\n", + "\n", + "plt.tight_layout(rect=[0, 0, 1, 0.95])\n", + "# plt.savefig(\"visualize/combined_radar_plots.png\", dpi=600,\n", + "# bbox_inches=\"tight\", transparent=True)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "34752035", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "id": "8e416fd5", + "metadata": {}, + "source": [ + "## testing" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "1529353d", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[(0.25660503201582907, 0.9323619711728774, 0.8292577291672704),\n", + " (0.3484708479375381, 0.3074749658243011, 0.0645616837705435),\n", + " (0.6096646070080306, 0.9514553535026719, 0.4209623091794289)]" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model_colors = generate_random_palette(len(model_ids), seed=12)\n", + "model_colors" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "a0b3b2e7", + "metadata": {}, + "outputs": [ + { + "ename": "TypeError", + "evalue": "list indices must be integers or slices, not str", + "output_type": "error", + "traceback": [ + "\u001b[31m---------------------------------------------------------------------------\u001b[39m", + "\u001b[31mTypeError\u001b[39m Traceback (most recent call last)", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[4]\u001b[39m\u001b[32m, line 40\u001b[39m\n\u001b[32m 36\u001b[39m subplot_kw=dict(polar=\u001b[38;5;28;01mTrue\u001b[39;00m))\n\u001b[32m 37\u001b[39m \n\u001b[32m 38\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m ax, (title, df) \u001b[38;5;28;01min\u001b[39;00m zip(axes, dfs.items()):\n\u001b[32m 39\u001b[39m df = df[df[\u001b[33m\"ModelID\"\u001b[39m].isin(model_ids)].copy()\n\u001b[32m---> \u001b[39m\u001b[32m40\u001b[39m make_radar(ax, df, feature_colnames[title], title, global_max)\n\u001b[32m 41\u001b[39m \n\u001b[32m 42\u001b[39m \u001b[38;5;66;03m# Shared legend (one for all)\u001b[39;00m\n\u001b[32m 43\u001b[39m handles, labels = axes[\u001b[32m0\u001b[39m].get_legend_handles_labels()\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/gene-process-dependencies/9.webapp/app_utils.py:150\u001b[39m, in \u001b[36mmake_radar\u001b[39m\u001b[34m(ax, df, feature_col, title, global_max, score_col, model_ids, num_circles)\u001b[39m\n\u001b[32m 147\u001b[39m values = merged[score_col].fillna(\u001b[32m0\u001b[39m).tolist()\n\u001b[32m 148\u001b[39m values += [values[\u001b[32m0\u001b[39m]]\n\u001b[32m--> \u001b[39m\u001b[32m150\u001b[39m ax.plot(angles, values, color=\u001b[30;43mmodel_colors\u001b[39;49m\u001b[30;43m[\u001b[39;49m\u001b[30;43mmid\u001b[39;49m\u001b[30;43m]\u001b[39;49m,\n\u001b[32m 151\u001b[39m linewidth=\u001b[32m3\u001b[39m, label=mid)\n\u001b[32m 152\u001b[39m ax.scatter(angles, values, color=model_colors[mid],\n\u001b[32m 153\u001b[39m s=\u001b[32m30\u001b[39m, edgecolor=\u001b[33m\"\u001b[39m\u001b[33mblack\u001b[39m\u001b[33m\"\u001b[39m, zorder=\u001b[32m5\u001b[39m)\n\u001b[32m 155\u001b[39m \u001b[38;5;66;03m# Axis styling\u001b[39;00m\n", + "\u001b[31mTypeError\u001b[39m: list indices must be integers or slices, not str" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
    " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import textwrap\n", + "\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import pandas as pd\n", + "from app_utils import (\n", + " clean_label,\n", + " generate_random_palette,\n", + " make_radar,\n", + " place_labels_polar,\n", + " truncate_label,\n", + ")\n", + "\n", + "model_ids = [\"ACH-000323\", \"ACH-002083\", \"ACH-002228\"]\n", + "files = {\n", + " \"Reactome Pathways\": \"../5.drug-dependency/results/all_reactome_results.parquet\",\n", + " \"CORUM Complexes\": \"../5.drug-dependency/results/all_corum_results.parquet\",\n", + " \"Drug Responses\": \"../5.drug-dependency/results/all_drug_results.parquet\",\n", + "}\n", + "# Adjust these if your column names differ\n", + "feature_colnames = {\n", + " \"Reactome Pathways\": \"reactome_pathway\",\n", + " \"CORUM Complexes\": \"reactome_pathway\",\n", + " \"Drug Responses\": \"name\",\n", + "}\n", + "score_col = \"pathway_score\"\n", + "\n", + "model_colors = {\n", + " \"ACH-000323\": \"#00FFFF\", # cyan\n", + " \"ACH-002083\": \"#FF69B4\", # pink\n", + " \"ACH-002228\": \"#800080\", # purple\n", + "}\n", + "\n", + "global_max = 0\n", + "dfs = {}\n", + "for name, file in files.items():\n", + " df = pd.read_parquet(file)\n", + " dfs[name] = df\n", + " if df[score_col].max() > global_max:\n", + " global_max = df[score_col].max()\n", + "\n", + "# --- Create one combined figure ---\n", + "fig, axes = plt.subplots(3, 1, figsize=(18, 12), subplot_kw=dict(polar=True))\n", + "\n", + "for ax, (title, df) in zip(axes, dfs.items()):\n", + " df = df[df[\"ModelID\"].isin(model_ids)].copy()\n", + " make_radar(ax, df, feature_colnames[title], title, global_max)\n", + "\n", + "# Shared legend (one for all)\n", + "handles, labels = axes[0].get_legend_handles_labels()\n", + "\n", + "fig.legend(\n", + " handles,\n", + " labels,\n", + " loc=\"lower center\",\n", + " ncol=3,\n", + " fontsize=12,\n", + " 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This repository is structured as follows: -| Order | Module | Description | -| :---- | :----- | :---------- | -| [0.data-download](0.data-download/) | Download required files | Download gene effect data and cell line information, and download gene QC and construct gene filtering dictionary | -| [1.data-exploration](1.data-exploration/) | Explore and visualize data | Create figures to visualize cell line information and split gene effect data into balanced test and train dataframes | -| [2.train-VAE](2.train-VAE/) | Train Beta VAE and Beta TC VAE models | Optimize hyperparameters and train Beta Variational Autoencoder/Beta Total Correlation Variational Autoencoder with optimal hyperparameters and previously created test and train dataframes | -| [3.analysis](3.analysis/) | Analyze Beta VAE and Beta TC VAE Outputs | Generate heatmaps to visualize death windows by cell line and by genes, run Gene Set Enrichment Analysis with BVAE and BTCVAE synthesized data, and analyze extracted BVAE/BTCVAE latent space data to compare similarity of cancer between different demographics | +| Order | Module | Description | +| :---------------------------------------- | :--------------------------------------- | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| [0.data-download](0.data-download/) | Download required files | Download gene effect data and cell line information, and download gene QC and construct gene filtering dictionary | +| [1.data-exploration](1.data-exploration/) | Explore and visualize data | Create figures to visualize cell line information and split gene effect data into balanced test and train dataframes | +| [2.train-VAE](2.train-VAE/) | Train Beta VAE and Beta TC VAE models | Optimize hyperparameters and train Beta Variational Autoencoder/Beta Total Correlation Variational Autoencoder with optimal hyperparameters and previously created test and train dataframes | +| [3.analysis](3.analysis/) | Analyze Beta VAE and Beta TC VAE Outputs | Generate heatmaps to visualize death windows by cell line and by genes, run Gene Set Enrichment Analysis with BVAE and BTCVAE synthesized data, and analyze extracted BVAE/BTCVAE latent space data to compare similarity of cancer between different demographics | ## Environment Setup @@ -50,3 +50,18 @@ conda env create --yes --file environment.yml # Run this command to activate the conda environment for Gene Dependency Representations conda activate gene_dependency_representations +``` + +## Webapp + +This repository now includes a Streamlit dashboard for interactive exploration of the parquet-backed plot outputs in `9.webapp/`. + +Run it from the repository root after activating the environment: + +```sh +just run +``` + +Use `just build` to syntax-check the app and `just deploy` to run Streamlit in headless mode on port `8501` by default. + +The dashboard currently exposes the Reactome, CORUM, and Drug result tables with toggleable Projection, Radar, and Heatmap views. From ac290a94ce4ba418a7b09030e5fa68b1a53e7ec9 Mon Sep 17 00:00:00 2001 From: MikeLippincott <1michaell2017@gmail.com> Date: Mon, 8 Jun 2026 18:44:41 -0600 Subject: [PATCH 02/25] progress capture --- 9.webapp/app.py | 482 +++++++++++++++++++++++++++++++---- 9.webapp/app_utils.py | 16 +- 9.webapp/test_notebook.ipynb | 253 +++++++++++++++--- 3 files changed, 662 insertions(+), 89 deletions(-) diff --git a/9.webapp/app.py b/9.webapp/app.py index 8cd52b7..0ff286f 100644 --- a/9.webapp/app.py +++ b/9.webapp/app.py @@ -128,36 +128,84 @@ # ── Sidebar controls ────────────────────────────────────────────────────────── with st.sidebar: - st.markdown("## 🧬 Controls") + st.markdown("## 🧬 Selections") st.markdown("---") reactome_matrix, corum_matrix, drug_matrix = latent_load_data() - # st.markdown("**DISEASE TYPES**") - # selected_diseases = st.multiselect( - # "Primary diseases", - # PRIMARY_DISEASES, - # default=PRIMARY_DISEASES[:8], - # label_visibility="collapsed", - # ) + + # ── Disease selector ────────────────────────────────────────────── + all_diseases = list(reactome_matrix["OncotreePrimaryDisease"].unique()) + + st.markdown( + "Primary diseases", + unsafe_allow_html=True, + ) + col_d1, col_d2 = st.columns(2) + if col_d1.button("All", key="disease_all", use_container_width=True): + st.session_state["diseases"] = all_diseases + if col_d2.button("None", key="disease_none", use_container_width=True): + st.session_state["diseases"] = [] + selected_diseases = st.multiselect( "Primary diseases", - reactome_matrix["OncotreePrimaryDisease"].unique(), - default=reactome_matrix["OncotreePrimaryDisease"].unique(), + all_diseases, + default=st.session_state.get("diseases", all_diseases), label_visibility="collapsed", + key="diseases", ) + st.markdown("---") + + # ── Model ID selector ───────────────────────────────────────────── + DEFAULT_MODEL_IDS = ["ACH-000323", "ACH-002083", "ACH-002228"] + all_model_ids = list(reactome_matrix["ModelID"].unique()) + + st.markdown( + "ModelIDs (spider plots)", + unsafe_allow_html=True, + ) + col_m1, col_m2, col_m3 = st.columns(3) + if col_m1.button("All", key="model_all", use_container_width=True): + st.session_state["model_ids"] = all_model_ids + if col_m2.button("None", key="model_none", use_container_width=True): + st.session_state["model_ids"] = [] + if col_m3.button("Default", key="model_default", use_container_width=True): + st.session_state["model_ids"] = DEFAULT_MODEL_IDS + model_ids = st.multiselect( "ModelIds (for spider plots)", - ["ACH-000323", "ACH-002083", "ACH-002228"], - default=["ACH-000323", "ACH-002083", "ACH-002228"], + all_model_ids, + default=st.session_state.get("model_ids", DEFAULT_MODEL_IDS), label_visibility="collapsed", + key="model_ids", ) st.markdown("---") + + # ── Spider plot process limit ───────────────────────────────────── st.markdown( - 'Data: DepMap synthetic (mirrors WayScience/gene-process-dependencies schema)', + "Spider plot — max processes", unsafe_allow_html=True, ) + limit_processes = st.toggle("Limit axes", value=False, key="limit_processes") + + if limit_processes: + max_processes = st.slider( + "Max processes per plot", + min_value=3, + max_value=20, + value=20, + step=1, + label_visibility="collapsed", + ) + else: + max_processes = None # signals downstream: show all + + st.markdown("---") + st.markdown( + 'Data: DepMap synthetic (mirrors WayScience/gene-process-dependencies schema)', + unsafe_allow_html=True, + ) # ── Header ──────────────────────────────────────────────────────────────────── st.markdown("# Gene Process Dependency Explorer") @@ -168,40 +216,51 @@ # ── Tabs ────────────────────────────────────────────────────────────────────── -# tab_single = st.tabs( -# tab_single, tab_latent= st.tabs( -(tab_spider,) = st.tabs(["🕷 Spider Plots"]) -# tab_single, = st.tabs(["📍 single dependency plots"]) -# tab_latent, = st.tabs(["📍 latent plots"]) -# tab_single, tab_latent, tab_spider = st.tabs( -# ["📍 single dependency plots", "📍 latent plots", "🕷 Spider Plots"] -# ["📍 single dependency plots", "📍 latent plots", "🕷 Spider Plots"] - - -# # ───────────────────────────────────────────────────────────────────────────── -# # TAB 1: PCA -# # ───────────────────────────────────────────────────────────────────────────── -# with tab_latent: -# st.markdown("### Latent Space PCA Projections") -# st.markdown( -# "PCA projection of latent representations learned by the selected compression model. " -# "Each point is a cancer cell line; clusters indicate similar gene dependency profiles." -# ) - - -# reactome_matrix, corum_matrix, drug_matrix = latent_load_data() -# # add a way to show all diseases or select specific ones - -# reactome_matrix = reactome_matrix[reactome_matrix["OncotreePrimaryDisease"].isin(selected_diseases)] -# corum_matrix = corum_matrix[corum_matrix["OncotreePrimaryDisease"].isin(selected_diseases)] -# drug_matrix = drug_matrix[drug_matrix["OncotreePrimaryDisease"].isin(selected_diseases)] -# # Assuming combined_df is your full dataset -# reactome_fig, reactome_out = make_dropdown_pca_with_selection(reactome_matrix, "PCA: Reactome Subset") -# corum_fig, corum_out = make_dropdown_pca_with_selection(corum_matrix, "PCA: CORUM Subset") -# drug_fig, drug_out = make_dropdown_pca_with_selection(drug_matrix, "PCA: Drug Subset") -# st.plotly_chart(reactome_fig, use_container_width=True) -# st.plotly_chart(corum_fig, use_container_width=True) -# st.plotly_chart(drug_fig, use_container_width=True) +tab_single, tab_latent, tab_spider, tab_scores, tab_table = st.tabs( + [ + "📍 single dependency plots", + "📍 latent plots", + "🕷 Spider Plots", + "📊 Top Scores", + "📋 Data Table", + ] +) + +# ───────────────────────────────────────────────────────────────────────────── +# TAB 1: PCA +# ───────────────────────────────────────────────────────────────────────────── +with tab_latent: + st.markdown("### Latent Space PCA Projections") + st.markdown( + "PCA projection of latent representations learned by the selected compression model. " + "Each point is a cancer cell line; clusters indicate similar gene dependency profiles." + ) + + reactome_matrix, corum_matrix, drug_matrix = latent_load_data() + # add a way to show all diseases or select specific ones + + reactome_matrix = reactome_matrix[ + reactome_matrix["OncotreePrimaryDisease"].isin(selected_diseases) + ] + corum_matrix = corum_matrix[ + corum_matrix["OncotreePrimaryDisease"].isin(selected_diseases) + ] + drug_matrix = drug_matrix[ + drug_matrix["OncotreePrimaryDisease"].isin(selected_diseases) + ] + # Assuming combined_df is your full dataset + reactome_fig, reactome_out = make_dropdown_pca_with_selection( + reactome_matrix, "PCA: Reactome Subset" + ) + corum_fig, corum_out = make_dropdown_pca_with_selection( + corum_matrix, "PCA: CORUM Subset" + ) + drug_fig, drug_out = make_dropdown_pca_with_selection( + drug_matrix, "PCA: Drug Subset" + ) + st.plotly_chart(reactome_fig, use_container_width=True) + st.plotly_chart(corum_fig, use_container_width=True) + st.plotly_chart(drug_fig, use_container_width=True) # ───────────────────────────────────────────────────────────────────────────── @@ -281,16 +340,27 @@ "Each axis = one process; the profile shape captures cancer-type-specific vulnerabilities." ) - # --- Create one combined figure --- + dfs, global_max, feature_colnames = spider_load_data() + fig, axes = plt.subplots(3, 1, figsize=(18, 12), subplot_kw=dict(polar=True)) for ax, (title, df) in zip(axes, dfs.items()): df = df[df["ModelID"].isin(model_ids)].copy() - make_radar(ax, df, feature_colnames[title], title, global_max) - # Shared legend (one for all) - handles, labels = axes[0].get_legend_handles_labels() + # Apply process limit if set + cols = feature_colnames[title] + + make_radar( + ax, + df, + cols, + title, + global_max, + model_ids=model_ids, + max_processes=max_processes, + ) + handles, labels = axes[0].get_legend_handles_labels() fig.legend( handles, labels, @@ -303,3 +373,313 @@ plt.tight_layout(rect=[0, 0, 1, 0.95]) st.pyplot(fig) + +# ───────────────────────────────────────────────────────────────────────────── +# TAB 4: Top Scores +# ───────────────────────────────────────────────────────────────────────────── +with tab_scores: + st.markdown("### Top Dependency Scores") + st.markdown( + "Visualize the highest-scoring biological processes across cancer types and individual cell lines. " + "Use the controls below to tune how many processes, cancer types, and model IDs are shown." + ) + + reactome_matrix, corum_matrix, drug_matrix = latent_load_data() + all_matrices = { + "Reactome": reactome_matrix, + "CORUM": corum_matrix, + "Drug": drug_matrix, + } + + # ── Controls ────────────────────────────────────────────────────── + sc1, sc2, sc3, sc4 = st.columns(4) + with sc1: + scores_dataset = st.selectbox( + "Dataset", + options=["Reactome", "CORUM", "Drug"], + key="scores_dataset", + ) + with sc2: + top_n_scores = st.slider( + "Top N processes", + min_value=3, + max_value=50, + value=15, + step=1, + key="scores_top_n", + ) + with sc3: + top_m_types = st.slider( + "Top M cancer types", + min_value=1, + max_value=30, + value=8, + step=1, + key="scores_top_m", + ) + with sc4: + top_i_models = st.slider( + "Top I model IDs", + min_value=1, + max_value=30, + value=8, + step=1, + key="scores_top_i", + ) + + score_df = all_matrices[scores_dataset].copy() + score_df = score_df[score_df["OncotreePrimaryDisease"].isin(selected_diseases)] + + meta_cols = ["ModelID", "OncotreePrimaryDisease"] + score_cols = [c for c in score_df.columns if c not in meta_cols] + + # ── Plot 1: top N processes × top M cancer types ────────────────── + st.markdown("---") + st.markdown("#### By cancer type") + st.markdown( + "Mean dependency score per process, averaged across all cell lines in each cancer type. " + "Only the top N processes (by max mean score across shown cancer types) are displayed." + ) + + # Mean score per (disease, process) + disease_means = ( + score_df.groupby("OncotreePrimaryDisease")[score_cols].mean().reset_index() + ) + + # Pick top M cancer types by their single highest mean score across all processes + disease_means["_max"] = disease_means[score_cols].max(axis=1) + top_diseases = disease_means.nlargest(top_m_types, "_max")[ + "OncotreePrimaryDisease" + ].tolist() + disease_means = disease_means[ + disease_means["OncotreePrimaryDisease"].isin(top_diseases) + ] + disease_means = disease_means.drop(columns=["_max"]) + + # Pick top N processes by max mean score across selected diseases + process_maxes = disease_means[score_cols].max(axis=0) + top_processes = process_maxes.nlargest(top_n_scores).index.tolist() + + heatmap_disease = disease_means.set_index("OncotreePrimaryDisease")[top_processes] + + fig_disease = go.Figure( + go.Heatmap( + z=heatmap_disease.values, + x=[ + textwrap.shorten(p, width=30, placeholder="…") + for p in heatmap_disease.columns + ], + y=heatmap_disease.index.tolist(), + colorscale="Blues", + hovertemplate="Disease: %{y}
    Process: %{x}
    Score: %{z:.3f}", + colorbar=dict(title="Mean score", thickness=14, len=0.6), + ) + ) + fig_disease.update_layout( + height=max(300, top_m_types * 36 + 120), + margin=dict(l=20, r=20, t=30, b=120), + paper_bgcolor="#0d1117", + plot_bgcolor="#0d1117", + font=dict(color="#e6edf3", size=11), + xaxis=dict(tickangle=-40, gridcolor="#21262d"), + yaxis=dict(gridcolor="#21262d"), + ) + st.plotly_chart(fig_disease, use_container_width=True) + + # ── Plot 2: top N processes × top I model IDs ───────────────────── + st.markdown("---") + st.markdown("#### By model ID") + st.markdown( + "Raw dependency score per process for individual cell lines. " + "Only the top I model IDs (by their single highest score across all processes) are shown." + ) + + # Pick top I models by max score across all processes + score_df["_max"] = score_df[score_cols].max(axis=1) + top_models = score_df.nlargest(top_i_models, "_max")["ModelID"].tolist() + score_df = score_df.drop(columns=["_max"]) + + model_df = score_df[score_df["ModelID"].isin(top_models)].set_index("ModelID")[ + top_processes + ] + + fig_model = go.Figure( + go.Heatmap( + z=model_df.values, + x=[ + textwrap.shorten(p, width=30, placeholder="…") for p in model_df.columns + ], + y=model_df.index.tolist(), + colorscale="Purples", + hovertemplate="Model: %{y}
    Process: %{x}
    Score: %{z:.3f}", + colorbar=dict(title="Score", thickness=14, len=0.6), + ) + ) + fig_model.update_layout( + height=max(300, top_i_models * 36 + 120), + margin=dict(l=20, r=20, t=30, b=120), + paper_bgcolor="#0d1117", + plot_bgcolor="#0d1117", + font=dict(color="#e6edf3", size=11), + xaxis=dict(tickangle=-40, gridcolor="#21262d"), + yaxis=dict(gridcolor="#21262d"), + ) + st.plotly_chart(fig_model, use_container_width=True) + + # ── Bar charts: top N processes collapsed ───────────────────────── + st.markdown("---") + st.markdown("#### Overall top processes") + st.markdown( + "Global mean score per process across all cell lines in the filtered dataset, ranked." + ) + + overall_means = score_df[score_cols].mean().nlargest(top_n_scores).reset_index() + overall_means.columns = ["Process", "Mean Score"] + overall_means["Process"] = overall_means["Process"].apply( + lambda p: textwrap.shorten(p, width=40, placeholder="…") + ) + + bar1, bar2 = st.columns(2) + + with bar1: + fig_bar_d = px.bar( + overall_means, + x="Mean Score", + y="Process", + orientation="h", + title="Top processes — all cell lines", + color="Mean Score", + color_continuous_scale="Blues", + ) + fig_bar_d.update_layout( + height=max(300, top_n_scores * 24 + 80), + margin=dict(l=10, r=10, t=40, b=20), + paper_bgcolor="#0d1117", + plot_bgcolor="#0d1117", + font=dict(color="#e6edf3", size=11), + yaxis=dict(autorange="reversed", gridcolor="#21262d"), + xaxis=dict(gridcolor="#21262d"), + coloraxis_showscale=False, + showlegend=False, + ) + st.plotly_chart(fig_bar_d, use_container_width=True) + + with bar2: + # Same but restricted to the top-M diseases + top_disease_means = ( + score_df[score_df["OncotreePrimaryDisease"].isin(top_diseases)][score_cols] + .mean() + .nlargest(top_n_scores) + .reset_index() + ) + top_disease_means.columns = ["Process", "Mean Score"] + top_disease_means["Process"] = top_disease_means["Process"].apply( + lambda p: textwrap.shorten(p, width=40, placeholder="…") + ) + fig_bar_m = px.bar( + top_disease_means, + x="Mean Score", + y="Process", + orientation="h", + title=f"Top processes — top {top_m_types} cancer types", + color="Mean Score", + color_continuous_scale="Purples", + ) + fig_bar_m.update_layout( + height=max(300, top_n_scores * 24 + 80), + margin=dict(l=10, r=10, t=40, b=20), + paper_bgcolor="#0d1117", + plot_bgcolor="#0d1117", + font=dict(color="#e6edf3", size=11), + yaxis=dict(autorange="reversed", gridcolor="#21262d"), + xaxis=dict(gridcolor="#21262d"), + coloraxis_showscale=False, + showlegend=False, + ) + st.plotly_chart(fig_bar_m, use_container_width=True) + +# ───────────────────────────────────────────────────────────────────────────── +# TAB 5: Data Table +# ───────────────────────────────────────────────────────────────────────────── +with tab_table: + st.markdown("### Cancer Types & Primary Diseases") + st.markdown( + "Summary of all cancer types and their associated primary diseases present in the dataset." + ) + + reactome_matrix, corum_matrix, drug_matrix = latent_load_data() + full_df = reactome_matrix[ + reactome_matrix["OncotreePrimaryDisease"].isin(selected_diseases) + ] + + # Build summary: one row per unique (OncotreeLineage, OncotreePrimaryDisease) pair + # adjust column names below to match whatever lineage/cancer-type column your data actually has + group_cols = ["OncotreePrimaryDisease", "ModelID"] # ← rename if needed + summary = ( + reactome_matrix.groupby(group_cols, dropna=False) + .agg(n_models=("ModelID", "nunique")) + .reset_index() + .sort_values(group_cols) + .rename( + columns={ + "OncotreePrimaryDisease": "Primary Disease", + "n_models": "Cell Lines", + } + ) + .drop(columns=["Cell Lines"]) + .drop_duplicates() + ) + + # ── Summary metrics ─────────────────────────────────────────────── + m1, m2 = st.columns(2) + m1.markdown( + f'
    Primary diseases
    {summary["Primary Disease"].nunique()}
    ', + unsafe_allow_html=True, + ) + m2.markdown( + f'
    Total cell lines
    {int(summary["ModelID"].nunique())}
    ', + unsafe_allow_html=True, + ) + st.markdown("") + + # ── Sort controls ───────────────────────────────────────────────── + sc1, sc2 = st.columns([3, 1]) + with sc1: + sort_by = st.selectbox( + "Sort by", + options=summary.columns.tolist(), + index=0, + key="table_sort_col", + ) + with sc2: + sort_asc = st.radio( + "Order", + ["Ascending", "Descending"], + index=0, + horizontal=True, + key="table_sort_dir", + ) + + summary = summary.sort_values(sort_by, ascending=(sort_asc == "Ascending")) + + # ── Table ───────────────────────────────────────────────────────── + st.dataframe( + summary.reset_index(drop=True), + use_container_width=True, + height=560, + column_config={ + "Lineage / Cancer Type": st.column_config.TextColumn(width="large"), + "Primary Disease": st.column_config.TextColumn(width="large"), + "Cell Lines": st.column_config.NumberColumn(width="small", format="%d"), + }, + hide_index=True, + ) + + # ── Download ────────────────────────────────────────────────────── + st.download_button( + label="⬇ Download as CSV", + data=summary.to_csv(index=False).encode("utf-8"), + file_name="cancer_types_diseases.csv", + mime="text/csv", + key="table_download", + ) diff --git a/9.webapp/app_utils.py b/9.webapp/app_utils.py index 688a57a..106630a 100644 --- a/9.webapp/app_utils.py +++ b/9.webapp/app_utils.py @@ -120,7 +120,7 @@ def spider_load_data(): # Adjust these if your column names differ feature_colnames = { "Reactome Pathways": "reactome_pathway", - "CORUM Complexes": "CORUM_pathway", + "CORUM Complexes": "reactome_pathway", "Drug Responses": "name", } score_col = "pathway_score" @@ -139,7 +139,7 @@ def spider_load_data(): if df[score_col].max() > global_max: global_max = df[score_col].max() - return dfs, global_max + return dfs, global_max, feature_colnames def clean_label(x: str) -> str: @@ -238,11 +238,19 @@ def make_radar( score_col: str = "pathway_score", model_ids: list = ["ACH-000323", "ACH-002083", "ACH-002228"], num_circles: int = 5, + max_processes: int = None, ) -> None: """ Draw a radar plot on an existing polar matplotlib axis. """ - model_colors = generate_model_color_map(model_ids, seed=12) + if model_ids == ["ACH-000323", "ACH-002083", "ACH-002228"]: + model_colors = { + "ACH-000323": "#00FFFF", # cyan + "ACH-002083": "#FF69B4", # pink + "ACH-002228": "#800080", # purple + } + else: + model_colors = generate_model_color_map(model_ids, seed=12) # Top 5 per model, union of all top_by_model = ( @@ -251,6 +259,8 @@ def make_radar( .reset_index(drop=True) ) top_features = top_by_model[feature_col].drop_duplicates().tolist() + if max_processes is not None: + top_features = top_features[:max_processes] n_vars = len(top_features) labels = [clean_label(x) for x in top_features] diff --git a/9.webapp/test_notebook.ipynb b/9.webapp/test_notebook.ipynb index d525410..920cffa 100644 --- a/9.webapp/test_notebook.ipynb +++ b/9.webapp/test_notebook.ipynb @@ -86969,12 +86969,12 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 32, "id": "3a41344d", "metadata": {}, "outputs": [], "source": [ - "model_ids = [\"ACH-000323\", \"ACH-002083\", \"ACH-002228\"]\n", + "model_ids = [\"ACH-000323\", \"ACH-002083\", \"ACH-002228\", \"ACH-000001\"]\n", "files = {\n", " \"Reactome Pathways\": \"../5.drug-dependency/results/all_reactome_results.parquet\",\n", " \"CORUM Complexes\": \"../5.drug-dependency/results/all_corum_results.parquet\",\n", @@ -86992,12 +86992,13 @@ " \"ACH-000323\": \"#00FFFF\", # cyan\n", " \"ACH-002083\": \"#FF69B4\", # pink\n", " \"ACH-002228\": \"#800080\", # purple\n", + " \"ACH-000001\": \"#FFA500\", # orange\n", "}" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 42, "id": "aa291f2e", "metadata": {}, "outputs": [], @@ -87074,12 +87075,21 @@ " feature_col: str,\n", " title: str,\n", " global_max: float,\n", + " score_col: str = \"pathway_score\",\n", + " model_ids: list = [\"ACH-000323\", \"ACH-002083\", \"ACH-002228\"],\n", " num_circles: int = 5,\n", ") -> None:\n", " \"\"\"\n", " Draw a radar plot on an existing polar matplotlib axis.\n", " \"\"\"\n", - " df = df[df[\"ModelID\"].isin(model_ids)].copy()\n", + " if model_ids == [\"ACH-000323\", \"ACH-002083\", \"ACH-002228\"]:\n", + " model_colors = {\n", + " \"ACH-000323\": \"#00FFFF\", # cyan\n", + " \"ACH-002083\": \"#FF69B4\", # pink\n", + " \"ACH-002228\": \"#800080\", # purple\n", + " }\n", + " else:\n", + " model_colors = generate_model_color_map(model_ids, seed=12)\n", "\n", " # Top 5 per model, union of all\n", " top_by_model = (\n", @@ -87102,7 +87112,6 @@ " ax.plot(\n", " angles, circle_vals, color=\"grey\", linestyle=\"--\", linewidth=1, zorder=0\n", " )\n", - "\n", " # Plot each model\n", " for mid in model_ids:\n", " subset = df[df[\"ModelID\"] == mid]\n", @@ -87132,50 +87141,60 @@ " # Title\n", " ax.set_title(title, fontsize=18, pad=30, fontweight=\"bold\", y=1)\n", "\n", - " return None" + " return None\n", + "\n", + "\n", + "def generate_model_color_map(model_ids, seed=12):\n", + " colors = generate_random_palette(len(model_ids), seed)\n", + " return {model_id: color for model_id, color in zip(model_ids, colors)}" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "id": "dd6645ac", + "metadata": {}, + "outputs": [], + "source": [ + "global_max = 0\n", + "dfs = {}\n", + "for name, file in files.items():\n", + " df = pd.read_parquet(file)\n", + " dfs[name] = df\n", + " if df[score_col].max() > global_max:\n", + " global_max = df[score_col].max()" ] }, { "cell_type": "code", - "execution_count": 16, - "id": "2ced4797", + "execution_count": 47, + "id": "36779957", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[Index(['ModelID', 'model', 'latent_dim_total', 'init', 'seed',\n", - " 'OncotreePrimaryDisease', 'z', 'latent_score', 'reactome_pathway',\n", - " 'nes_score', 'pathway_score'],\n", - " dtype='str'),\n", - " Index(['ModelID', 'model', 'latent_dim_total', 'init', 'seed',\n", - " 'OncotreePrimaryDisease', 'z', 'latent_score', 'reactome_pathway',\n", - " 'gsea_es_score', 'pathway_score'],\n", - " dtype='str'),\n", - " Index(['ModelID', 'model', 'latent_dim_total', 'init', 'seed',\n", - " 'OncotreePrimaryDisease', 'z', 'latent_score', 'name',\n", - " 'pearson_correlation', 'pathway_score'],\n", - " dtype='str')]" + "'name'" ] }, - "execution_count": 16, + "execution_count": 47, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "[df.columns for df in dfs.values()]" + "cols" ] }, { "cell_type": "code", - "execution_count": 12, - "id": "dd6645ac", + "execution_count": 46, + "id": "81e8b00c", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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    " ] @@ -87185,20 +87204,28 @@ } ], "source": [ - "global_max = 0\n", - "dfs = {}\n", - "for name, file in files.items():\n", - " df = pd.read_parquet(file)\n", - " dfs[name] = df\n", - " if df[score_col].max() > global_max:\n", - " global_max = df[score_col].max()\n", - "\n", + "max_processes = 3\n", "# --- Create one combined figure ---\n", "fig, axes = plt.subplots(3, 1, figsize=(18, 12), subplot_kw=dict(polar=True))\n", "\n", "for ax, (title, df) in zip(axes, dfs.items()):\n", - " make_radar(ax, df, feature_colnames[title], title, global_max)\n", + " df = df[df[\"ModelID\"].isin(model_ids)].copy()\n", + "\n", + " # Apply process limit if set\n", + " cols = feature_colnames[title]\n", + " # if max_processes is not None:\n", + " # cols = cols[:max_processes]\n", "\n", + " make_radar(ax, df, cols, title, global_max, model_ids=model_ids)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d206f528", + "metadata": {}, + "outputs": [], + "source": [ "# Shared legend (one for all)\n", "handles, labels = axes[0].get_legend_handles_labels()\n", "\n", @@ -87355,9 +87382,165 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "id": "dfca7abf", "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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    Primary DiseaseModelID
    0Acute Myeloid LeukemiaACH-000004
    1Acute Myeloid LeukemiaACH-000005
    2Acute Myeloid LeukemiaACH-000045
    3Acute Myeloid LeukemiaACH-000113
    4Acute Myeloid LeukemiaACH-000146
    .........
    1145Uterine Sarcoma/MesenchymalACH-000939
    1146Uterine Sarcoma/MesenchymalACH-001655
    1147Well-Differentiated Thyroid CancerACH-000716
    1148Well-Differentiated Thyroid CancerACH-000903
    1149Well-Differentiated Thyroid CancerACH-001528
    \n", + "

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    " + ], + "text/plain": [ + " Primary Disease ModelID\n", + "0 Acute Myeloid Leukemia ACH-000004\n", + "1 Acute Myeloid Leukemia ACH-000005\n", + "2 Acute Myeloid Leukemia ACH-000045\n", + "3 Acute Myeloid Leukemia ACH-000113\n", + "4 Acute Myeloid Leukemia ACH-000146\n", + "... ... ...\n", + "1145 Uterine Sarcoma/Mesenchymal ACH-000939\n", + "1146 Uterine Sarcoma/Mesenchymal ACH-001655\n", + "1147 Well-Differentiated Thyroid Cancer ACH-000716\n", + "1148 Well-Differentiated Thyroid Cancer ACH-000903\n", + "1149 Well-Differentiated Thyroid Cancer ACH-001528\n", + "\n", + "[1150 rows x 2 columns]" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import pandas as pd\n", + "from app_utils import latent_load_data\n", + "\n", + "selected_diseases = [\n", + " \"Lung Adenocarcinoma\",\n", + " \"Lung Squamous Cell Carcinoma\",\n", + " \"Small Cell Lung Carcinoma\",\n", + " \"Colorectal Adenocarcinoma\",\n", + " \"Pancreatic Adenocarcinoma\",\n", + " \"Ovarian Serous Cystadenocarcinoma\",\n", + " \"Glioblastoma Multiforme\",\n", + " \"Skin Cutaneous Melanoma\",\n", + " \"Uterine Corpus Endometrial Carcinoma\",\n", + " \"Prostate Adenocarcinoma\",\n", + "]\n", + "reactome_matrix, corum_matrix, drug_matrix = latent_load_data()\n", + "full_df = reactome_matrix[\n", + " reactome_matrix[\"OncotreePrimaryDisease\"].isin(selected_diseases)\n", + "]\n", + "\n", + "# Build summary: one row per unique (OncotreeLineage, OncotreePrimaryDisease) pair\n", + "# adjust column names below to match whatever lineage/cancer-type column your data actually has\n", + "group_cols = [\"OncotreePrimaryDisease\", \"ModelID\"] # ← rename if needed\n", + "summary = (\n", + " reactome_matrix.groupby(group_cols, dropna=False)\n", + " .agg(n_models=(\"ModelID\", \"nunique\"))\n", + " .reset_index()\n", + " .sort_values(group_cols)\n", + " .rename(\n", + " columns={\n", + " \"OncotreeLineage\": \"Lineage / Cancer Type\",\n", + " \"OncotreePrimaryDisease\": \"Primary Disease\",\n", + " \"n_models\": \"Cell Lines\",\n", + " }\n", + " )\n", + " .drop(columns=[\"Cell Lines\"])\n", + " .drop_duplicates()\n", + ")\n", + "summary" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "810f449e", + "metadata": {}, "outputs": [], "source": [] } From d1c3ee2d0023b7686aef7781289995b37f1d912d Mon Sep 17 00:00:00 2001 From: MikeLippincott <1michaell2017@gmail.com> Date: Mon, 8 Jun 2026 18:57:44 -0600 Subject: [PATCH 03/25] add new webapp --- 9.webapp/0.single-dependency-umaps(1).ipynb | 30279 ------ 9.webapp/1.latent-umaps(1).ipynb | 86709 ----------------- 9.webapp/8.spider_plots.ipynb | 266 - 9.webapp/app.py | 604 +- 9.webapp/requirements.txt | 88 + 9.webapp/test_notebook.ipynb | 87569 ------------------ 6 files changed, 375 insertions(+), 205140 deletions(-) delete mode 100644 9.webapp/0.single-dependency-umaps(1).ipynb delete mode 100644 9.webapp/1.latent-umaps(1).ipynb delete mode 100644 9.webapp/8.spider_plots.ipynb create mode 100644 9.webapp/requirements.txt delete mode 100644 9.webapp/test_notebook.ipynb diff --git a/9.webapp/0.single-dependency-umaps(1).ipynb b/9.webapp/0.single-dependency-umaps(1).ipynb deleted file mode 100644 index 40f53d8..0000000 --- a/9.webapp/0.single-dependency-umaps(1).ipynb +++ /dev/null @@ -1,30279 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import pathlib\n", - "import sys\n", - "\n", - "import joblib\n", - "import numpy as np\n", - "import pandas as pd\n", - "\n", - "script_directory = pathlib.Path(\"../utils/\").resolve()\n", - "sys.path.insert(0, str(script_directory))\n", - "from data_loader import load_model_data, load_train_test_data" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(1150, 18444)\n" - ] - } - ], - "source": [ - "# Load dependency data\n", - "data_directory = pathlib.Path(\"../0.data-download/data\").resolve()\n", - "dependency_file = pathlib.Path(f\"{data_directory}/CRISPRGeneEffect.parquet\").resolve()\n", - "gene_dict_file = pathlib.Path(\n", - " f\"{data_directory}/CRISPR_gene_dictionary.parquet\"\n", - ").resolve()\n", - "dependency_df, gene_dict_df = load_model_data(dependency_file, gene_dict_file)\n", - "dependency_df = dependency_df.set_index(\"ModelID\")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "cancer_type_input_file = pathlib.Path(\"../0.data-download/data/Model.parquet\")\n", - "cancer_type_df = pd.read_parquet(cancer_type_input_file)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "combined_df = dependency_df.merge(\n", - " cancer_type_df[[\"ModelID\", \"OncotreePrimaryDisease\"]], on=\"ModelID\", how=\"left\"\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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"\n", - "def generate_random_palette(num_colors, seed=12):\n", - " # Generate random colors with varied lightness and saturation\n", - " random.seed(seed)\n", - "\n", - " colors = []\n", - "\n", - " for _ in range(num_colors):\n", - " h = random.random() # Random hue between 0 and 1\n", - " l = random.uniform(0.2, 0.8) # Lightness between 0.3 and 0.9 for contrast\n", - " s = random.uniform(0.5, 1.0) # Saturation between 0.6 and 1.0 for vivid colors\n", - " color = colorsys.hls_to_rgb(h, l, s) # Convert HLS to RGB color\n", - " colors.append(color)\n", - "\n", - " return colors" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.plotly.v1+json": { - "config": { - "plotlyServerURL": "https://plot.ly" - }, - "data": [ - { - "hoverinfo": "text", - "marker": { - "color": "#636EFA", - "size": 7 - }, - "mode": "markers", - "name": "Ovarian Epithelial Tumor", - "text": [ - "Ovarian Epithelial Tumor | ACH-000001", - "Ovarian Epithelial Tumor | ACH-000013", - "Ovarian Epithelial Tumor | ACH-000048", - "Ovarian Epithelial Tumor | ACH-000103", - "Ovarian Epithelial Tumor | ACH-000116", - "Ovarian Epithelial Tumor | ACH-000123", - "Ovarian Epithelial Tumor | ACH-000132", - "Ovarian Epithelial Tumor | ACH-000237", - "Ovarian Epithelial Tumor | ACH-000256", - "Ovarian Epithelial Tumor | ACH-000278", - "Ovarian Epithelial Tumor | ACH-000280", - "Ovarian Epithelial Tumor | ACH-000291", - "Ovarian Epithelial Tumor | ACH-000308", - "Ovarian Epithelial Tumor | ACH-000324", - "Ovarian Epithelial Tumor | ACH-000430", - "Ovarian Epithelial Tumor | ACH-000460", - "Ovarian Epithelial Tumor | ACH-000520", - "Ovarian Epithelial Tumor | ACH-000524", - "Ovarian Epithelial Tumor | ACH-000527", - "Ovarian Epithelial Tumor | ACH-000542", - "Ovarian Epithelial Tumor | ACH-000584", - "Ovarian Epithelial Tumor | ACH-000608", - "Ovarian Epithelial Tumor | ACH-000646", - "Ovarian Epithelial Tumor | ACH-000657", - "Ovarian Epithelial Tumor | ACH-000663", - "Ovarian Epithelial Tumor | ACH-000688", - "Ovarian Epithelial Tumor | ACH-000696", - "Ovarian Epithelial Tumor | ACH-000701", - "Ovarian Epithelial Tumor | ACH-000704", - "Ovarian Epithelial Tumor | ACH-000713", - "Ovarian Epithelial Tumor | ACH-000719", - "Ovarian Epithelial Tumor | ACH-000796", - "Ovarian Epithelial Tumor | ACH-000811", - "Ovarian Epithelial Tumor | ACH-000885", - "Ovarian Epithelial Tumor | ACH-000906", - "Ovarian Epithelial Tumor | ACH-000936", - "Ovarian Epithelial Tumor | ACH-000947", - "Ovarian Epithelial Tumor | ACH-000962", - "Ovarian Epithelial Tumor | ACH-000966", - "Ovarian Epithelial Tumor | ACH-001048", - "Ovarian Epithelial Tumor | ACH-001063", - "Ovarian Epithelial Tumor | ACH-001145", - "Ovarian Epithelial Tumor | ACH-001151", - "Ovarian Epithelial Tumor | ACH-001278", - "Ovarian Epithelial Tumor | ACH-001279", - "Ovarian Epithelial Tumor | ACH-001340", - "Ovarian Epithelial Tumor | ACH-001370", - "Ovarian Epithelial Tumor | ACH-001403", - "Ovarian Epithelial Tumor | ACH-001418", - "Ovarian Epithelial Tumor | ACH-001628", - "Ovarian Epithelial Tumor | ACH-001630", - "Ovarian Epithelial Tumor | ACH-001632", - "Ovarian Epithelial Tumor | ACH-001719", - "Ovarian Epithelial Tumor | ACH-001991", - "Ovarian Epithelial Tumor | ACH-002140", - "Ovarian Epithelial Tumor | ACH-002181", - "Ovarian Epithelial Tumor | ACH-002183", - "Ovarian Epithelial Tumor | ACH-002486", - "Ovarian Epithelial Tumor | ACH-002524" - ], - "type": "scatter", - "x": [ - 3.0309908218654065, - -0.6451330075414331, - -5.083336194271603, - 3.5501342155382747, - 1.2761951845240291, - -4.2168917744847105, - 1.2208674505264685, - 4.743704058920847, - 3.645265085276565, - 5.3927939548802355, - -0.17458554447799873, - 1.109578612850182, - 5.19861859404294, - -0.9380287199461492, - -4.317228187345513, - -1.9085663724207853, - 1.8912339629311985, - 6.421946990041236, - -0.41849604585415023, - -1.741250797602297, - -1.0492796345395083, - 9.86362418697908, - 6.701553547924745, - -4.5140904696967725, - 1.802430503590046, - 11.992510340272734, - -2.796348381410119, - 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{ - "hoverinfo": "text", - "marker": { - "color": "#EF553B", - "size": 7 - }, - "mode": "markers", - "name": "Acute Myeloid Leukemia", - "text": [ - "Acute Myeloid Leukemia | ACH-000004", - "Acute Myeloid Leukemia | ACH-000005", - "Acute Myeloid Leukemia | ACH-000045", - "Acute Myeloid Leukemia | ACH-000113", - "Acute Myeloid Leukemia | ACH-000146", - "Acute Myeloid Leukemia | ACH-000168", - "Acute Myeloid Leukemia | ACH-000190", - "Acute Myeloid Leukemia | ACH-000195", - "Acute Myeloid Leukemia | ACH-000263", - "Acute Myeloid Leukemia | ACH-000294", - "Acute Myeloid Leukemia | ACH-000336", - "Acute Myeloid Leukemia | ACH-000362", - "Acute Myeloid Leukemia | ACH-000387", - "Acute Myeloid Leukemia | ACH-000406", - "Acute Myeloid Leukemia | ACH-000498", - "Acute Myeloid Leukemia | ACH-000557", - "Acute Myeloid Leukemia | ACH-000602", - "Acute Myeloid Leukemia | ACH-000770", - "Acute Myeloid Leukemia | ACH-001036", - "Acute Myeloid Leukemia | ACH-001129", - "Acute Myeloid Leukemia | ACH-001574", - "Acute Myeloid Leukemia | ACH-001577", - "Acute Myeloid Leukemia | ACH-001613", - "Acute Myeloid Leukemia | ACH-001618", - "Acute Myeloid Leukemia | ACH-001647", - "Acute Myeloid Leukemia | ACH-001656" - ], - "type": "scatter", - "x": [ - -1.6359361722925707, - 0.4834905698216894, - -6.531038651377258, - -11.09913868177248, - 0.8459884211523804, - 0.514664624703801, - -1.296518072646908, - 0.22424472936031345, - 2.3869046661542495, - -4.295842304675442, - -8.606653683819603, - -7.044163136811803, - -1.6912790399001725, - -7.671529385626213, - 0.9409884876537782, - 3.949597781168233, - -2.3405781597377486, - -5.648626543729697, - -3.2907976519237487, - 1.5310739821303658, - -6.606256502808931, - -1.2256552446295208, - -4.5233046170403, - -2.626557271506326, - -5.134742175790549, - -4.345399401861395 - ], - "y": [ - -2.4546475476212577, - -2.1102610601084018, - -3.855905265396789, - -3.2115678380518893, - -5.464751152850505, - -3.639290938345915, - 0.6050267255749116, - -1.699085018303891, - 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"Colorectal Adenocarcinoma | ACH-000403", - "Colorectal Adenocarcinoma | ACH-000421", - "Colorectal Adenocarcinoma | ACH-000467", - "Colorectal Adenocarcinoma | ACH-000470", - "Colorectal Adenocarcinoma | ACH-000489", - "Colorectal Adenocarcinoma | ACH-000491", - "Colorectal Adenocarcinoma | ACH-000501", - "Colorectal Adenocarcinoma | ACH-000532", - "Colorectal Adenocarcinoma | ACH-000552", - "Colorectal Adenocarcinoma | ACH-000565", - "Colorectal Adenocarcinoma | ACH-000651", - "Colorectal Adenocarcinoma | ACH-000683", - "Colorectal Adenocarcinoma | ACH-000722", - "Colorectal Adenocarcinoma | ACH-000798", - "Colorectal Adenocarcinoma | ACH-000820", - "Colorectal Adenocarcinoma | ACH-000926", - "Colorectal Adenocarcinoma | ACH-000935", - "Colorectal Adenocarcinoma | ACH-000943", - "Colorectal Adenocarcinoma | ACH-000950", - "Colorectal Adenocarcinoma | ACH-000957", - "Colorectal Adenocarcinoma | ACH-000958", - "Colorectal Adenocarcinoma | ACH-000959", - "Colorectal Adenocarcinoma | ACH-000963", - "Colorectal Adenocarcinoma | ACH-000969", - "Colorectal Adenocarcinoma | ACH-000970", - "Colorectal Adenocarcinoma | ACH-000971", - "Colorectal Adenocarcinoma | ACH-000985", - "Colorectal Adenocarcinoma | ACH-000986", - "Colorectal Adenocarcinoma | ACH-000991", - "Colorectal Adenocarcinoma | ACH-000997", - "Colorectal Adenocarcinoma | ACH-001039", - "Colorectal Adenocarcinoma | ACH-001061", - "Colorectal Adenocarcinoma | ACH-001081", - "Colorectal Adenocarcinoma | ACH-001345", - "Colorectal Adenocarcinoma | ACH-001399", - "Colorectal Adenocarcinoma | ACH-001454", - "Colorectal Adenocarcinoma | ACH-001458", - "Colorectal Adenocarcinoma | ACH-001459", - "Colorectal Adenocarcinoma | ACH-001460", - "Colorectal Adenocarcinoma | ACH-001461", - "Colorectal Adenocarcinoma | ACH-001786", - "Colorectal Adenocarcinoma | ACH-002024", - "Colorectal Adenocarcinoma | ACH-002025", - "Colorectal Adenocarcinoma | ACH-002233", - "Colorectal Adenocarcinoma | ACH-002535", - "Colorectal Adenocarcinoma | ACH-002654", - 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"Non-Small Cell Lung Cancer | ACH-000438", - "Non-Small Cell Lung Cancer | ACH-000442", - "Non-Small Cell Lung Cancer | ACH-000444", - "Non-Small Cell Lung Cancer | ACH-000448", - "Non-Small Cell Lung Cancer | ACH-000454", - "Non-Small Cell Lung Cancer | ACH-000463", - "Non-Small Cell Lung Cancer | ACH-000481", - "Non-Small Cell Lung Cancer | ACH-000496", - "Non-Small Cell Lung Cancer | ACH-000510", - "Non-Small Cell Lung Cancer | ACH-000511", - "Non-Small Cell Lung Cancer | ACH-000521", - "Non-Small Cell Lung Cancer | ACH-000528", - "Non-Small Cell Lung Cancer | ACH-000562", - "Non-Small Cell Lung Cancer | ACH-000563", - "Non-Small Cell Lung Cancer | ACH-000585", - "Non-Small Cell Lung Cancer | ACH-000587", - "Non-Small Cell Lung Cancer | ACH-000589", - "Non-Small Cell Lung Cancer | ACH-000596", - "Non-Small Cell Lung Cancer | ACH-000627", - "Non-Small Cell Lung Cancer | ACH-000638", - "Non-Small Cell Lung Cancer | ACH-000662", - "Non-Small Cell Lung Cancer | ACH-000665", - "Non-Small Cell Lung Cancer | ACH-000666", - 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}, - "mode": "markers", - "name": "Mature B-Cell Neoplasms", - "text": [ - "Mature B-Cell Neoplasms | ACH-000024", - "Mature B-Cell Neoplasms | ACH-000106", - "Mature B-Cell Neoplasms | ACH-000124", - "Mature B-Cell Neoplasms | ACH-000167", - "Mature B-Cell Neoplasms | ACH-000183", - "Mature B-Cell Neoplasms | ACH-000204", - "Mature B-Cell Neoplasms | ACH-000271", - "Mature B-Cell Neoplasms | ACH-000315", - "Mature B-Cell Neoplasms | ACH-000334", - "Mature B-Cell Neoplasms | ACH-000346", - "Mature B-Cell Neoplasms | ACH-000363", - "Mature B-Cell Neoplasms | ACH-000365", - "Mature B-Cell Neoplasms | ACH-000371", - "Mature B-Cell Neoplasms | ACH-000398", - "Mature B-Cell Neoplasms | ACH-000402", - "Mature B-Cell Neoplasms | ACH-000405", - "Mature B-Cell Neoplasms | ACH-000426", - "Mature B-Cell Neoplasms | ACH-000436", - "Mature B-Cell Neoplasms | ACH-000512", - "Mature B-Cell Neoplasms | ACH-000541", - "Mature B-Cell Neoplasms | ACH-000567", - "Mature B-Cell Neoplasms | ACH-000576", - "Mature B-Cell Neoplasms | ACH-000588", - 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"text": [ - "Meningothelial Tumor | ACH-000025", - "Meningothelial Tumor | ACH-001067", - "Meningothelial Tumor | ACH-002070" - ], - "type": "scatter", - "x": [ - -2.2918653508813356, - -3.4818530281270608, - 0.23544159568970377 - ], - "y": [ - 4.234922789292899, - 2.1384628407115835, - 2.2506814100749017 - ] - }, - { - "hoverinfo": "text", - "marker": { - "color": "#FD3216", - "size": 7 - }, - "mode": "markers", - "name": "Diffuse Glioma", - "text": [ - "Diffuse Glioma | ACH-000036", - "Diffuse Glioma | ACH-000040", - "Diffuse Glioma | ACH-000067", - "Diffuse Glioma | ACH-000075", - "Diffuse Glioma | ACH-000098", - "Diffuse Glioma | ACH-000128", - "Diffuse Glioma | ACH-000137", - "Diffuse Glioma | ACH-000152", - "Diffuse Glioma | ACH-000200", - "Diffuse Glioma | ACH-000208", - "Diffuse Glioma | ACH-000215", - "Diffuse Glioma | ACH-000231", - "Diffuse Glioma | ACH-000232", - "Diffuse Glioma | ACH-000244", - "Diffuse Glioma | ACH-000269", - "Diffuse Glioma | ACH-000273", - "Diffuse Glioma | ACH-000323", - "Diffuse Glioma | ACH-000329", - "Diffuse Glioma | ACH-000368", - "Diffuse Glioma | ACH-000370", - "Diffuse Glioma | ACH-000376", - "Diffuse Glioma | ACH-000389", - "Diffuse Glioma | ACH-000437", - "Diffuse Glioma | ACH-000445", - "Diffuse Glioma | ACH-000455", - "Diffuse Glioma | ACH-000464", - "Diffuse Glioma | ACH-000469", - "Diffuse Glioma | ACH-000479", - "Diffuse Glioma | ACH-000504", - "Diffuse Glioma | ACH-000558", - "Diffuse Glioma | ACH-000570", - "Diffuse Glioma | ACH-000571", - "Diffuse Glioma | ACH-000591", - "Diffuse Glioma | ACH-000592", - "Diffuse Glioma | ACH-000595", - "Diffuse Glioma | ACH-000609", - "Diffuse Glioma | ACH-000622", - "Diffuse Glioma | ACH-000623", - "Diffuse Glioma | ACH-000631", - "Diffuse Glioma | ACH-000634", - "Diffuse Glioma | ACH-000655", - "Diffuse Glioma | ACH-000673", - "Diffuse Glioma | ACH-000676", - "Diffuse Glioma | ACH-000738", - "Diffuse Glioma | ACH-000756", - "Diffuse Glioma | ACH-000760", - "Diffuse Glioma | ACH-000807", - "Diffuse Glioma | ACH-000819", - "Diffuse Glioma | ACH-000863", - "Diffuse Glioma | ACH-000887", - "Diffuse Glioma | ACH-001016", - "Diffuse Glioma | ACH-001126", - "Diffuse Glioma | ACH-001172", - "Diffuse Glioma | ACH-001329", - "Diffuse Glioma | ACH-001605", - "Diffuse Glioma | ACH-001606", - "Diffuse Glioma | ACH-001608", - "Diffuse Glioma | ACH-001609", - "Diffuse Glioma | ACH-001610", - "Diffuse Glioma | ACH-001611", - "Diffuse Glioma | ACH-001622", - "Diffuse Glioma | ACH-001623", - "Diffuse Glioma | ACH-001624", - "Diffuse Glioma | ACH-002228", - "Diffuse Glioma | ACH-002229", - "Diffuse Glioma | ACH-002230", - "Diffuse Glioma | ACH-002257", - "Diffuse Glioma | ACH-002269", - "Diffuse Glioma | ACH-002304", - "Diffuse Glioma | ACH-002680" - ], - "type": "scatter", - "x": [ - 1.3681271217849218, - 4.5321645145029095, - 5.081596980585533, - 5.1037044573937544, - 1.638986998836172, - -0.2698655142711293, - 0.7399423006717846, - 4.733350651180982, - 4.012916453112655, - 2.3243204974846883, - -0.728350624067885, - 1.2267911398789155, - 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"Esophagogastric Adenocarcinoma | ACH-000581", - "Esophagogastric Adenocarcinoma | ACH-000616", - "Esophagogastric Adenocarcinoma | ACH-000633", - "Esophagogastric Adenocarcinoma | ACH-000736", - "Esophagogastric Adenocarcinoma | ACH-000746", - "Esophagogastric Adenocarcinoma | ACH-000758", - "Esophagogastric Adenocarcinoma | ACH-000764", - "Esophagogastric Adenocarcinoma | ACH-000793", - "Esophagogastric Adenocarcinoma | ACH-000847", - "Esophagogastric Adenocarcinoma | ACH-000880", - "Esophagogastric Adenocarcinoma | ACH-000898", - "Esophagogastric Adenocarcinoma | ACH-000911", - "Esophagogastric Adenocarcinoma | ACH-000919", - "Esophagogastric Adenocarcinoma | ACH-000932", - "Esophagogastric Adenocarcinoma | ACH-000948", - "Esophagogastric Adenocarcinoma | ACH-001368", - "Esophagogastric Adenocarcinoma | ACH-001496", - "Esophagogastric Adenocarcinoma | ACH-001497", - "Esophagogastric Adenocarcinoma | ACH-001500", - "Esophagogastric Adenocarcinoma | ACH-001544", - "Esophagogastric Adenocarcinoma | ACH-001653", - "Esophagogastric Adenocarcinoma | ACH-001654", - "Esophagogastric Adenocarcinoma | ACH-001664", - "Esophagogastric Adenocarcinoma | ACH-002141", - "Esophagogastric Adenocarcinoma | ACH-002161", - "Esophagogastric Adenocarcinoma | ACH-002202", - "Esophagogastric Adenocarcinoma | ACH-002446", - "Esophagogastric Adenocarcinoma | ACH-002705", - "Esophagogastric Adenocarcinoma | ACH-002706" - ], - "type": "scatter", - "x": [ - -4.162764787605665, - 8.797004721880963, - -0.8355828331646905, - 1.6733375074106704, - -2.6269941085749107, - 0.324125484967366, - -1.0386285488971287, - -3.167319375828302, - 0.8293499524287758, - -0.05959084354024104, - 1.2226371479776177, - 3.460471563584129, - 2.4488212104865283, - -1.7068676947380108, - -3.8083503652102486, - -1.9638563709752628, - 2.651208177301365, - -0.9810663818919616, - -3.2594659570837363, - 0.6732714312264414, - -2.1246489090500003, - 1.8941848345384389, - -2.7335539787352325, - -5.774124569861559, - -4.658850383176383, - 1.309316275419729, - 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"Embryonal Tumor | ACH-000776", - "Embryonal Tumor | ACH-001020", - "Embryonal Tumor | ACH-001028", - "Embryonal Tumor | ACH-001031", - "Embryonal Tumor | ACH-001033", - "Embryonal Tumor | ACH-001053", - "Embryonal Tumor | ACH-001054", - "Embryonal Tumor | ACH-001232", - "Embryonal Tumor | ACH-001289", - "Embryonal Tumor | ACH-001670", - "Embryonal Tumor | ACH-001711" - ], - "type": "scatter", - "x": [ - -2.659851809912358, - -1.5662884627651907, - -4.665277568369991, - 2.0929611576980864, - -0.7345169861004269, - -0.324303839458803, - -4.24581168664449, - -3.861316722666653, - 0.22390404626451577, - -0.6271155217257527, - -5.044323667627733, - 2.2694265946131704, - -0.5472631215649119, - -2.329318495121874, - -1.4254379139783628 - ], - "y": [ - -0.47068373445639977, - 0.2925382181190015, - 2.3576189434524375, - 3.13944205097863, - 1.6658021795665836, - 2.166646414956354, - 0.4201462690431714, - 2.2022303830034273, - 0.5597617456668382, - 0.16723259508318097, - -0.5556522060060175, - 4.717203551555202, - 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"Myeloproliferative Neoplasms | ACH-000920", - "Myeloproliferative Neoplasms | ACH-000983", - "Myeloproliferative Neoplasms | ACH-002061" - ], - "type": "scatter", - "x": [ - -2.669714697898407, - -4.319140886969565, - -8.773924961486193, - -0.3695678679773042, - -5.415508277929856, - -3.534830844479983, - -1.9521546712489664, - -0.2579746696551216, - -6.477556475669396, - -4.0839384565601815 - ], - "y": [ - -4.38777789512208, - -2.749080333804357, - -4.073523282217145, - -3.3497656372028297, - -2.949498201534456, - -4.247150967187889, - -3.480068553794545, - -1.3053387153499303, - -4.057328791075288, - -2.9592164389295723 - ] - }, - { - "hoverinfo": "text", - "marker": { - "color": "#EEA6FB", - "size": 7 - }, - "mode": "markers", - "name": "Non-Hodgkin Lymphoma", - "text": [ - "Non-Hodgkin Lymphoma | ACH-000077", - "Non-Hodgkin Lymphoma | ACH-000583", - "Non-Hodgkin Lymphoma | ACH-001197", - "Non-Hodgkin Lymphoma | ACH-001642" - ], - "type": "scatter", - "x": [ - -4.4342958080891295, - 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"Neuroblastoma | ACH-001367", - "Neuroblastoma | ACH-001481", - "Neuroblastoma | ACH-001548", - "Neuroblastoma | ACH-001603", - "Neuroblastoma | ACH-001674", - "Neuroblastoma | ACH-002080", - "Neuroblastoma | ACH-002083", - "Neuroblastoma | ACH-002261", - "Neuroblastoma | ACH-002278", - "Neuroblastoma | ACH-002280", - "Neuroblastoma | ACH-002282", - "Neuroblastoma | ACH-002283", - "Neuroblastoma | ACH-002284", - "Neuroblastoma | ACH-002285", - "Neuroblastoma | ACH-002922" - ], - "type": "scatter", - "x": [ - 0.4082600987518737, - -3.251873669925637, - 0.6150663745100188, - -2.5994084109264417, - 1.884785020649007, - 5.005787077953376, - -5.622301801563553, - -1.4463144647011563, - 5.524703752978904, - 0.25308641537712745, - 2.272182216234488, - -1.2770672906846428, - -4.149909613371795, - -1.821855823399664, - -3.0908911954714413, - 2.797063852563436, - 0.7187108599479375, - 1.7298944718774254, - -3.4491621450455767, - 1.2182884072758733, - -0.6750975418192354, - -1.7554991474846662, - 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"Pleural Mesothelioma | ACH-001559", - "Pleural Mesothelioma | ACH-001560", - "Pleural Mesothelioma | ACH-001562", - "Pleural Mesothelioma | ACH-001977", - "Pleural Mesothelioma | ACH-001992", - "Pleural Mesothelioma | ACH-002033" - ], - "type": "scatter", - "x": [ - -0.629931015600818, - 5.069924962160149, - 4.374737788776979, - 4.0488807468578125, - 1.544893280283976, - -1.2988474375306642, - 6.985951559162894, - 1.3775768461795364, - 5.591385942207075, - 0.4551762312084493, - 2.461853999557073, - 1.6156462353816845, - -0.30454981124735975, - 1.0180832941865174, - 1.1582661462742694, - -0.2029099183491843, - 1.9286907628888577, - -1.3145054218840089, - -3.3847266030407357, - -2.0542985275344807, - 7.013029834317919 - ], - "y": [ - 3.052823826835156, - 1.1614582058152825, - 3.176213665563452, - 3.147240429663835, - 2.366358690461577, - 1.165848974895758, - -2.6450972945200704, - 1.0348003251985587, - 2.0442530777353873, - 2.449276135805664, - 3.776329967041004, - 3.1008453345250486, - 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"Non-Cancerous | ACH-002462", - "Non-Cancerous | ACH-002463", - "Non-Cancerous | ACH-002464", - "Non-Cancerous | ACH-002465", - "Non-Cancerous | ACH-002467" - ], - "type": "scatter", - "x": [ - 2.1729337754738225, - -0.6693827170197243, - 0.6218161149860384, - -7.241008227661885, - -2.8997403811198303, - 3.352290269835757, - 4.411480743412238, - 11.52988499291458, - 1.9643975029627936, - 2.770683156418975 - ], - "y": [ - 4.076620631894248, - 3.63259955297147, - 2.3963195310868706, - -2.031102158927911, - 0.12415371778766436, - 6.151240402401803, - 6.3868498112132235, - 2.8411914741068576, - 4.995659684563751, - 4.924528293081592 - ] - }, - { - "hoverinfo": "text", - "marker": { - "color": "#E3EE9E", - "size": 7 - }, - "mode": "markers", - "name": "Intracholecystic Papillary Neoplasm", - "text": [ - "Intracholecystic Papillary Neoplasm | ACH-000141", - "Intracholecystic Papillary Neoplasm | ACH-001607", - "Intracholecystic Papillary Neoplasm | ACH-001619", - "Intracholecystic Papillary Neoplasm | ACH-001850", - "Intracholecystic Papillary Neoplasm | ACH-001861", - "Intracholecystic Papillary Neoplasm | ACH-001961" - ], - "type": "scatter", - "x": [ - 5.272497181497207, - -2.646533044051488, - 4.411954195660837, - -2.6719822075761654, - -5.127151970770218, - -1.587019614433913 - ], - "y": [ - -1.483442915192007, - -0.8505549845594961, - 1.1403489688404842, - 0.6522924821688806, - -0.9448242081881564, - -0.5536270175745971 - ] - }, - { - "hoverinfo": "text", - "marker": { - "color": "#86CE00", - "size": 7 - }, - "mode": "markers", - "name": "Leiomyosarcoma", - "text": [ - "Leiomyosarcoma | ACH-000145", - "Leiomyosarcoma | ACH-000505", - "Leiomyosarcoma | ACH-002785" - ], - "type": "scatter", - "x": [ - 5.047799929955265, - 7.311698905558325, - 4.593619045259388 - ], - "y": [ - 2.3866154760583025, - 1.4799479038843526, - -0.2677403196937987 - ] - }, - { - "hoverinfo": "text", - "marker": { - "color": "#BC7196", - "size": 7 - }, - "mode": "markers", - "name": "Renal Cell Carcinoma", - "text": [ - "Renal Cell Carcinoma | ACH-000159", - "Renal Cell Carcinoma | ACH-000189", - "Renal Cell Carcinoma | ACH-000234", - "Renal Cell Carcinoma | ACH-000246", - "Renal Cell Carcinoma | ACH-000250", - "Renal Cell Carcinoma | ACH-000262", - "Renal Cell Carcinoma | ACH-000272", - "Renal Cell Carcinoma | ACH-000313", - "Renal Cell Carcinoma | ACH-000317", - "Renal Cell Carcinoma | ACH-000375", - "Renal Cell Carcinoma | ACH-000385", - "Renal Cell Carcinoma | ACH-000411", - "Renal Cell Carcinoma | ACH-000433", - "Renal Cell Carcinoma | ACH-000459", - "Renal Cell Carcinoma | ACH-000484", - "Renal Cell Carcinoma | ACH-000495", - "Renal Cell Carcinoma | ACH-000649", - "Renal Cell Carcinoma | ACH-000684", - "Renal Cell Carcinoma | ACH-000709", - "Renal Cell Carcinoma | ACH-000792", - "Renal Cell Carcinoma | ACH-000907", - "Renal Cell Carcinoma | ACH-001163", - "Renal Cell Carcinoma | ACH-001194", - "Renal Cell Carcinoma | ACH-001398", - "Renal Cell Carcinoma | ACH-001687", - "Renal Cell Carcinoma | ACH-001688", - "Renal Cell Carcinoma | ACH-002150", - "Renal Cell Carcinoma | ACH-002189", - "Renal Cell Carcinoma | ACH-002533" - ], - "type": "scatter", - "x": [ - 4.124666901622867, - 4.415360950959302, - 5.565606460803343, - -0.26987035020501215, - 0.4498496881028425, - 0.195280369109114, - 2.7396781996015434, - 6.1554513288847446, - -1.8124535476282573, - -3.222977659884704, - 1.5254385829365114, - -0.0013735812594187632, - 3.993881452978225, - 14.061971124128588, - 7.839864897847747, - 4.0415090548971495, - -1.0852811250820742, - 2.4748427356929144, - 5.820338524296377, - 1.2342017037857222, - 8.05764850301894, - 0.27901460985138116, - 6.373126463390758, - 3.293680959272059, - -1.5147409836327608, - 8.617755305041493, - -2.297170098461978, - 8.483495386386844, - -2.88562606607037 - ], - "y": [ - -0.23506622769856125, - 2.231089112086252, - 1.655499342896252, - 2.6445958780194103, - 1.752560397290766, - 3.9072429776088056, - -0.31358763210167, - 0.17690856745070352, - 1.517444556171333, - 1.15193785496911, - 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"Head and Neck Squamous Cell Carcinoma | ACH-000500", - "Head and Neck Squamous Cell Carcinoma | ACH-000503", - "Head and Neck Squamous Cell Carcinoma | ACH-000518", - "Head and Neck Squamous Cell Carcinoma | ACH-000546", - "Head and Neck Squamous Cell Carcinoma | ACH-000548", - "Head and Neck Squamous Cell Carcinoma | ACH-000549", - "Head and Neck Squamous Cell Carcinoma | ACH-000606", - "Head and Neck Squamous Cell Carcinoma | ACH-000618", - "Head and Neck Squamous Cell Carcinoma | ACH-000619", - "Head and Neck Squamous Cell Carcinoma | ACH-000630", - "Head and Neck Squamous Cell Carcinoma | ACH-000682", - "Head and Neck Squamous Cell Carcinoma | ACH-000732", - "Head and Neck Squamous Cell Carcinoma | ACH-000735", - "Head and Neck Squamous Cell Carcinoma | ACH-000740", - "Head and Neck Squamous Cell Carcinoma | ACH-000762", - "Head and Neck Squamous Cell Carcinoma | ACH-000771", - "Head and Neck Squamous Cell Carcinoma | ACH-000778", - "Head and Neck Squamous Cell Carcinoma | ACH-000794", - "Head and Neck Squamous Cell Carcinoma | ACH-000832", - "Head and Neck Squamous Cell Carcinoma | ACH-000836", - "Head and Neck Squamous Cell Carcinoma | ACH-000846", - "Head and Neck Squamous Cell Carcinoma | ACH-001228", - "Head and Neck Squamous Cell Carcinoma | ACH-001229", - "Head and Neck Squamous Cell Carcinoma | ACH-001331", - "Head and Neck Squamous Cell Carcinoma | ACH-001332", - "Head and Neck Squamous Cell Carcinoma | ACH-001346", - "Head and Neck Squamous Cell Carcinoma | ACH-001347", - "Head and Neck Squamous Cell Carcinoma | ACH-001385", - "Head and Neck Squamous Cell Carcinoma | ACH-001509", - "Head and Neck Squamous Cell Carcinoma | ACH-001510", - "Head and Neck Squamous Cell Carcinoma | ACH-001511", - "Head and Neck Squamous Cell Carcinoma | ACH-001542", - "Head and Neck Squamous Cell Carcinoma | ACH-001543", - "Head and Neck Squamous Cell Carcinoma | ACH-001625", - "Head and Neck Squamous Cell Carcinoma | ACH-001626", - "Head and Neck Squamous Cell Carcinoma | ACH-001641", - "Head and Neck Squamous Cell Carcinoma | ACH-001675", - "Head and Neck Squamous Cell Carcinoma | ACH-001690", - "Head and Neck Squamous Cell Carcinoma | ACH-001691", - "Head and Neck Squamous Cell Carcinoma | ACH-001692", - "Head and Neck Squamous Cell Carcinoma | ACH-001694", - "Head and Neck Squamous Cell Carcinoma | ACH-001695", - "Head and Neck Squamous Cell Carcinoma | ACH-001696", - "Head and Neck Squamous Cell Carcinoma | ACH-001698", - "Head and Neck Squamous Cell Carcinoma | ACH-001699", - "Head and Neck Squamous Cell Carcinoma | ACH-001701", - "Head and Neck Squamous Cell Carcinoma | ACH-002029", - "Head and Neck Squamous Cell Carcinoma | ACH-002030", - "Head and Neck Squamous Cell Carcinoma | ACH-002042", - "Head and Neck Squamous Cell Carcinoma | ACH-002043", - "Head and Neck Squamous Cell Carcinoma | ACH-002044", - "Head and Neck Squamous Cell Carcinoma | ACH-002045", - "Head and Neck Squamous Cell Carcinoma | ACH-002212", - "Head and Neck Squamous Cell Carcinoma | ACH-002249", - 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true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true - ] - }, - { - "title": "PCA Highlighted: Salivary Carcinoma" - } - ], - "label": "Salivary Carcinoma", - "method": "update" - } - ], - "direction": "down", - "showactive": true, - "x": 1.15, - "xanchor": "left", - "y": 1.15, - "yanchor": "top" - } - ], - "width": 1500, - "xaxis": { - "title": { - "text": "PCA1" - } - }, - "yaxis": { - "title": { - "text": "PCA2" - } - } - } - } - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import plotly.express as px\n", - "import plotly.graph_objects as go\n", - "from sklearn.decomposition import PCA\n", - "from sklearn.preprocessing import StandardScaler\n", - "\n", - "# Prepare PCA input (excluding non-numeric columns)\n", - "pca_input = combined_df[gene_cols].apply(pd.to_numeric, errors=\"coerce\")\n", - "pca = PCA(n_components=2, random_state=0)\n", - "pca_embedding = pca.fit_transform(pca_input)\n", - "\n", - "# Add PCA components to the dataframe\n", - "combined_df[\"PCA1\"] = pca_embedding[:, 0]\n", - "combined_df[\"PCA2\"] = pca_embedding[:, 1]\n", - "\n", - "# Prepare color map for each cancer type\n", - "cancer_types = combined_df[\"OncotreePrimaryDisease\"].unique()\n", - "color_map = (\n", - " px.colors.qualitative.Plotly\n", - " + px.colors.qualitative.Light24\n", - " + px.colors.qualitative.Dark24\n", - ")\n", - "highlight_color_map = {\n", - " cancer: color_map[i % len(color_map)] for i, cancer in enumerate(cancer_types)\n", - "}\n", - "\n", - "# Create one trace per cancer type\n", - "traces = []\n", - "for cancer in cancer_types:\n", - " df_subset = combined_df[combined_df[\"OncotreePrimaryDisease\"] == cancer]\n", - " trace = go.Scatter(\n", - " x=df_subset[\"PCA1\"],\n", - " y=df_subset[\"PCA2\"],\n", - " mode=\"markers\",\n", - " name=cancer,\n", - " marker=dict(size=7),\n", - " text=[f\"{cancer} | {model_id}\" for model_id in df_subset[\"ModelID\"]],\n", - " hoverinfo=\"text\",\n", - " )\n", - " traces.append(trace)\n", - "\n", - "# Create dropdown buttons\n", - "dropdown_buttons = []\n", - "\n", - "for i, cancer in enumerate(cancer_types):\n", - " # Make all grey except the selected one\n", - " visibility = [True] * len(cancer_types)\n", - " colors = [\"lightgrey\"] * len(cancer_types)\n", - " colors[i] = highlight_color_map[cancer]\n", - "\n", - " button = dict(\n", - " method=\"update\",\n", - " label=cancer,\n", - " args=[\n", - " {\n", - " \"visible\": visibility,\n", - " \"marker\": [{\"color\": colors[j]} for j in range(len(cancer_types))],\n", - " },\n", - " {\"title\": f\"PCA Highlighted: {cancer}\"},\n", - " ],\n", - " )\n", - " dropdown_buttons.append(button)\n", - "\n", - "# Add a button to show all with normal colors\n", - "default_colors = [highlight_color_map[cancer] for cancer in cancer_types]\n", - "dropdown_buttons.insert(\n", - " 0,\n", - " dict(\n", - " method=\"update\",\n", - " label=\"Show All\",\n", - " args=[\n", - " {\n", - " \"visible\": [True] * len(cancer_types),\n", - " \"marker\": [\n", - " {\"color\": default_colors[j]} for j in range(len(cancer_types))\n", - " ],\n", - " },\n", - " {\"title\": \"PCA of DepMap Single Gene Data\"},\n", - " ],\n", - " ),\n", - ")\n", - "\n", - "# Create the figure\n", - "fig = go.Figure(data=traces)\n", - "\n", - "# Set default colors\n", - "for i, trace in enumerate(fig.data):\n", - " trace.marker.color = default_colors[i]\n", - "\n", - "fig.update_layout(\n", - " title=\"PCA of DepMap Single Gene Data\",\n", - " xaxis_title=\"PCA1\",\n", - " yaxis_title=\"PCA2\",\n", - " updatemenus=[\n", - " {\n", - " \"buttons\": dropdown_buttons,\n", - " \"direction\": \"down\",\n", - " \"showactive\": True,\n", - " \"x\": 1.15,\n", - " \"xanchor\": \"left\",\n", - " \"y\": 1.15,\n", - " \"yanchor\": \"top\",\n", - " }\n", - " ],\n", - " width=1500,\n", - " height=800,\n", - ")\n", - "\n", - "fig.show()\n", - "fig.write_html(\"achilles_pca.html\")" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "gene_dependency_representations_real", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.8" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/9.webapp/1.latent-umaps(1).ipynb b/9.webapp/1.latent-umaps(1).ipynb deleted file mode 100644 index c21af55..0000000 --- a/9.webapp/1.latent-umaps(1).ipynb +++ /dev/null @@ -1,86709 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import colorsys\n", - "import pathlib\n", - "import random\n", - "\n", - "import ipywidgets as widgets\n", - "import pandas as pd\n", - "import plotly.express as px\n", - "import plotly.graph_objs as go\n", - "from sklearn.decomposition import PCA" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "cancer_type_input_file = pathlib.Path(\"../0.data-download/data/Model.parquet\")\n", - "cancer_type_df = pd.read_parquet(cancer_type_input_file)\n", - "\n", - "reactome_dims = pathlib.Path(\n", - " \"../5.drug-dependency/results/all_reactome_results.parquet\"\n", - ")\n", - "reactome_df = pd.read_parquet(reactome_dims)\n", - "\n", - "corum_dims = pathlib.Path(\"../5.drug-dependency/results/all_corum_results.parquet\")\n", - "corum_df = pd.read_parquet(corum_dims)\n", - "\n", - "drug_dims = pathlib.Path(\"../5.drug-dependency/results/all_drug_results.parquet\")\n", - "drug_df = pd.read_parquet(drug_dims)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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    ModelIDmodellatent_dim_totalinitseedOncotreePrimaryDiseasezlatent_scorereactome_pathwaynes_scorepathway_score
    0ACH-000001betatcvae1641154917792Ovarian Epithelial Tumor10.306144Formation Of Incision Complex In GG-NER R-HSA-...3.2473450.306144
    1ACH-000001betatcvae250501796030Ovarian Epithelial Tumor10.657242Citric Acid (TCA) Cycle And Respiratory Electr...inf0.657242
    2ACH-000001betatcvae9001590696690Ovarian Epithelial Tumor10.455570Polymerase Switching On C-strand Of Telomere R...2.9176800.455570
    3ACH-000001betavae534066919116Ovarian Epithelial Tumor10.000000RHOC GTPase Cycle R-HSA-90131063.1494550.000000
    4ACH-000001betavae1021507182516Ovarian Epithelial Tumor10.159076Nephrin Family Interactions R-HSA-3737532.5826870.159076
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    " - ], - "text/plain": [ - " ModelID model latent_dim_total init seed \\\n", - "0 ACH-000001 betatcvae 16 4 1154917792 \n", - "1 ACH-000001 betatcvae 25 0 501796030 \n", - "2 ACH-000001 betatcvae 90 0 1590696690 \n", - "3 ACH-000001 betavae 5 3 4066919116 \n", - "4 ACH-000001 betavae 10 2 1507182516 \n", - "\n", - " OncotreePrimaryDisease z latent_score \\\n", - "0 Ovarian Epithelial Tumor 1 0.306144 \n", - "1 Ovarian Epithelial Tumor 1 0.657242 \n", - "2 Ovarian Epithelial Tumor 1 0.455570 \n", - "3 Ovarian Epithelial Tumor 1 0.000000 \n", - "4 Ovarian Epithelial Tumor 1 0.159076 \n", - "\n", - " reactome_pathway nes_score pathway_score \n", - "0 Formation Of Incision Complex In GG-NER R-HSA-... 3.247345 0.306144 \n", - "1 Citric Acid (TCA) Cycle And Respiratory Electr... inf 0.657242 \n", - "2 Polymerase Switching On C-strand Of Telomere R... 2.917680 0.455570 \n", - "3 RHOC GTPase Cycle R-HSA-9013106 3.149455 0.000000 \n", - "4 Nephrin Family Interactions R-HSA-373753 2.582687 0.159076 " - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "reactome_df.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "# Step 2: Subset based on matching keys\n", - "subset_keys = [\"model\", \"latent_dim_total\", \"init\", \"z\"]\n", - "\n", - "# Replace latent identifiers with pathway\n", - "reactome_df[\"feature\"] = reactome_df[\"reactome_pathway\"]\n", - "reactome_df = reactome_df.drop(\n", - " columns=[\"model\", \"latent_dim_total\", \"init\", \"seed\", \"z\", \"reactome_pathway\"]\n", - ")\n", - "\n", - "corum_df[\"feature\"] = corum_df[\"reactome_pathway\"]\n", - "corum_df = corum_df.drop(\n", - " columns=[\"model\", \"latent_dim_total\", \"init\", \"seed\", \"z\", \"reactome_pathway\"]\n", - ")\n", - "\n", - "drug_df[\"feature\"] = drug_df[\"name\"]\n", - "drug_df = drug_df.drop(\n", - " columns=[\"model\", \"latent_dim_total\", \"init\", \"seed\", \"z\", \"name\"]\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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    ModelIDOncotreePrimaryDiseaselatent_scorepearson_correlationpathway_scorefeature
    597ACH-000004Acute Myeloid Leukemia0.543216-0.2639620.54321610-deacetylbaccatin
    716ACH-000004Acute Myeloid Leukemia0.740212-0.2529450.7402122,3-DCPE
    457ACH-000004Acute Myeloid Leukemia0.832806-0.2753880.8328063-deazaneplanocin-A
    678ACH-000004Acute Myeloid Leukemia0.641957-0.3206670.6419579-aminoacridine
    444ACH-000004Acute Myeloid Leukemia0.546763-0.2626310.546763ACY-1215
    \n", - "
    " - ], - "text/plain": [ - " ModelID OncotreePrimaryDisease latent_score pearson_correlation \\\n", - "597 ACH-000004 Acute Myeloid Leukemia 0.543216 -0.263962 \n", - "716 ACH-000004 Acute Myeloid Leukemia 0.740212 -0.252945 \n", - "457 ACH-000004 Acute Myeloid Leukemia 0.832806 -0.275388 \n", - "678 ACH-000004 Acute Myeloid Leukemia 0.641957 -0.320667 \n", - "444 ACH-000004 Acute Myeloid Leukemia 0.546763 -0.262631 \n", - "\n", - " pathway_score feature \n", - "597 0.543216 10-deacetylbaccatin \n", - "716 0.740212 2,3-DCPE \n", - "457 0.832806 3-deazaneplanocin-A \n", - "678 0.641957 9-aminoacridine \n", - "444 0.546763 ACY-1215 " - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "drug_df_sorted = drug_df.sort_values(\n", - " by=[\"OncotreePrimaryDisease\", \"ModelID\", \"feature\"], ascending=True\n", - ")\n", - "drug_df_sorted.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "# Create a unique column name by combining feature and source\n", - "meta_cols = [\"ModelID\", \"OncotreePrimaryDisease\"]\n", - "reactome_meta = reactome_df[meta_cols].drop_duplicates()\n", - "corum_meta = corum_df[meta_cols].drop_duplicates()\n", - "drug_meta = drug_df[meta_cols].drop_duplicates()\n", - "\n", - "# Pivot to wide format\n", - "reactome_matrix = reactome_df.pivot(\n", - " index=\"ModelID\", columns=\"feature\", values=\"latent_score\"\n", - ")\n", - "corum_matrix = corum_df.pivot(index=\"ModelID\", columns=\"feature\", values=\"latent_score\")\n", - "drug_matrix = drug_df.pivot(index=\"ModelID\", columns=\"feature\", values=\"latent_score\")\n", - "\n", - "# Join metadata back to each matrix\n", - "reactome_matrix = reactome_matrix.merge(reactome_meta, on=\"ModelID\", how=\"left\")\n", - "corum_matrix = corum_matrix.merge(corum_meta, on=\"ModelID\", how=\"left\")\n", - "drug_matrix = drug_matrix.merge(drug_meta, on=\"ModelID\", how=\"left\")" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "def generate_random_palette(num_colors, seed=12):\n", - " # Generate random colors with varied lightness and saturation\n", - " random.seed(seed)\n", - "\n", - " colors = []\n", - "\n", - " for _ in range(num_colors):\n", - " h = random.random() # Random hue between 0 and 1\n", - " l = random.uniform(0.2, 0.8) # Lightness between 0.3 and 0.9 for contrast\n", - " s = random.uniform(0.5, 1.0) # Saturation between 0.6 and 1.0 for vivid colors\n", - " color = colorsys.hls_to_rgb(h, l, s) # Convert HLS to RGB color\n", - " colors.append(color)\n", - "\n", - " return colors" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "def make_dropdown_pca_with_selection(df, title=\"PCA Interactive Plot\"):\n", - " out = widgets.Output() # Create a fresh output for this plot!\n", - "\n", - " # Prepare PCA input\n", - " pca_input = df.drop(\n", - " columns=[\"OncotreePrimaryDisease\", \"source\", \"ModelID\"], errors=\"ignore\"\n", - " ).fillna(0)\n", - " pca = PCA(n_components=2, random_state=0)\n", - " embedding = pca.fit_transform(pca_input)\n", - "\n", - " # Add PCA coordinates to the dataframe\n", - " df[\"PCA1\"] = embedding[:, 0]\n", - " df[\"PCA2\"] = embedding[:, 1]\n", - "\n", - " # Prepare color map for each cancer type\n", - " cancer_types = df[\"OncotreePrimaryDisease\"].unique()\n", - " color_map = (\n", - " px.colors.qualitative.Plotly\n", - " + px.colors.qualitative.Light24\n", - " + px.colors.qualitative.Dark24\n", - " )\n", - " highlight_color_map = {\n", - " cancer: color_map[i % len(color_map)] for i, cancer in enumerate(cancer_types)\n", - " }\n", - "\n", - " # Create one trace per cancer type\n", - " traces = []\n", - " for cancer in cancer_types:\n", - " df_subset = df[df[\"OncotreePrimaryDisease\"] == cancer]\n", - " trace = go.Scattergl(\n", - " x=df_subset[\"PCA1\"],\n", - " y=df_subset[\"PCA2\"],\n", - " mode=\"markers\",\n", - " name=cancer,\n", - " marker=dict(size=7, color=highlight_color_map[cancer]),\n", - " text=[f\"{cancer} | {model_id}\" for model_id in df_subset[\"ModelID\"]],\n", - " customdata=df_subset[\"ModelID\"], # Attach ModelID to customdata\n", - " hoverinfo=\"text\",\n", - " )\n", - " traces.append(trace)\n", - "\n", - " # Dropdown buttons to highlight cancer types\n", - " dropdown_buttons = []\n", - " for i, cancer in enumerate(cancer_types):\n", - " visibility = [True] * len(cancer_types)\n", - " colors = [\"lightgrey\"] * len(cancer_types)\n", - " colors[i] = highlight_color_map[cancer]\n", - "\n", - " button = dict(\n", - " method=\"update\",\n", - " label=cancer,\n", - " args=[\n", - " {\n", - " \"visible\": visibility,\n", - " \"marker\": [{\"color\": colors[j]} for j in range(len(cancer_types))],\n", - " },\n", - " {\"title\": f\"PCA Highlighted: {cancer}\"},\n", - " ],\n", - " )\n", - " dropdown_buttons.append(button)\n", - "\n", - " # Default color button\n", - " default_colors = [highlight_color_map[cancer] for cancer in cancer_types]\n", - " dropdown_buttons.insert(\n", - " 0,\n", - " dict(\n", - " method=\"update\",\n", - " label=\"Show All\",\n", - " args=[\n", - " {\n", - " \"visible\": [True] * len(cancer_types),\n", - " \"marker\": [\n", - " {\"color\": default_colors[j]} for j in range(len(cancer_types))\n", - " ],\n", - " },\n", - " {\"title\": title},\n", - " ],\n", - " ),\n", - " )\n", - "\n", - " fig = go.Figure(data=traces)\n", - "\n", - " for i, trace in enumerate(fig.data):\n", - " trace.marker.color = default_colors[i]\n", - "\n", - " fig.update_layout(\n", - " title=title,\n", - " xaxis_title=\"PCA1\",\n", - " yaxis_title=\"PCA2\",\n", - " updatemenus=[\n", - " {\n", - " \"buttons\": dropdown_buttons,\n", - " \"direction\": \"down\",\n", - " \"showactive\": True,\n", - " \"x\": 1.15,\n", - " \"xanchor\": \"left\",\n", - " \"y\": 1.15,\n", - " \"yanchor\": \"top\",\n", - " }\n", - " ],\n", - " dragmode=\"lasso\", # Ensure Lasso is enabled\n", - " width=1500,\n", - " height=800,\n", - " )\n", - "\n", - " return fig, out # Return both the figure and the output widget for selection" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.plotly.v1+json": { - "config": { - "plotlyServerURL": "https://plot.ly" - }, - "data": [ - { - "customdata": [ - "ACH-000001", - "ACH-000013", - "ACH-000048", - "ACH-000103", - "ACH-000116", - "ACH-000123", - "ACH-000132", - "ACH-000237", - "ACH-000256", - "ACH-000278", - "ACH-000280", - "ACH-000291", - "ACH-000308", - "ACH-000324", - "ACH-000430", - "ACH-000460", - "ACH-000520", - "ACH-000524", - "ACH-000527", - "ACH-000542", - "ACH-000584", - "ACH-000608", - "ACH-000646", - "ACH-000657", - "ACH-000663", - "ACH-000688", - "ACH-000696", - "ACH-000701", - "ACH-000704", - "ACH-000713", - "ACH-000719", - "ACH-000796", - "ACH-000811", - "ACH-000885", - "ACH-000906", 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ACH-000280", - "Ovarian Epithelial Tumor | ACH-000291", - "Ovarian Epithelial Tumor | ACH-000308", - "Ovarian Epithelial Tumor | ACH-000324", - "Ovarian Epithelial Tumor | ACH-000430", - "Ovarian Epithelial Tumor | ACH-000460", - "Ovarian Epithelial Tumor | ACH-000520", - "Ovarian Epithelial Tumor | ACH-000524", - "Ovarian Epithelial Tumor | ACH-000527", - "Ovarian Epithelial Tumor | ACH-000542", - "Ovarian Epithelial Tumor | ACH-000584", - "Ovarian Epithelial Tumor | ACH-000608", - "Ovarian Epithelial Tumor | ACH-000646", - "Ovarian Epithelial Tumor | ACH-000657", - "Ovarian Epithelial Tumor | ACH-000663", - "Ovarian Epithelial Tumor | ACH-000688", - "Ovarian Epithelial Tumor | ACH-000696", - "Ovarian Epithelial Tumor | ACH-000701", - "Ovarian Epithelial Tumor | ACH-000704", - "Ovarian Epithelial Tumor | ACH-000713", - "Ovarian Epithelial Tumor | ACH-000719", - "Ovarian Epithelial Tumor | ACH-000796", - "Ovarian Epithelial Tumor | ACH-000811", - "Ovarian Epithelial Tumor | ACH-000885", - "Ovarian Epithelial Tumor | ACH-000906", - "Ovarian Epithelial Tumor | ACH-000936", - "Ovarian Epithelial Tumor | ACH-000947", - "Ovarian Epithelial Tumor | ACH-000962", - "Ovarian Epithelial Tumor | ACH-000966", - "Ovarian Epithelial Tumor | ACH-001048", - "Ovarian Epithelial Tumor | ACH-001063", - "Ovarian Epithelial Tumor | ACH-001145", - "Ovarian Epithelial Tumor | ACH-001151", - "Ovarian Epithelial Tumor | ACH-001278", - "Ovarian Epithelial Tumor | ACH-001279", - "Ovarian Epithelial Tumor | ACH-001340", - "Ovarian Epithelial Tumor | ACH-001370", - "Ovarian Epithelial Tumor | ACH-001403", - "Ovarian Epithelial Tumor | ACH-001418", - "Ovarian Epithelial Tumor | ACH-001628", - "Ovarian Epithelial Tumor | ACH-001630", - "Ovarian Epithelial Tumor | ACH-001632", - "Ovarian Epithelial Tumor | ACH-001719", - "Ovarian Epithelial Tumor | ACH-001991", - "Ovarian Epithelial Tumor | ACH-002140", - "Ovarian Epithelial Tumor | ACH-002181", - "Ovarian Epithelial Tumor | ACH-002183", - "Ovarian Epithelial Tumor | ACH-002486", - "Ovarian Epithelial Tumor | ACH-002524" - ], - "type": "scattergl", - "x": { - "bdata": "e4r5vXb+GEB3ZKhALgRQvzJvbj+zPJhAjuwfPx0F7r/s1PLAO+TywArKyD9QREE/sscBwMD76j9xNJdAA/IrQO14272HxvLAujMCQKPC8sDw4wNAr9TywI2/H8AMsvLAswDFPnB1pMAiym5AzegdwIiS0D8zZOU+ic/QvkXWZL9RyVPAhGu0QB/Tk0Beduw/74jkQNR3MUCgV+Y/osfywEW/8sDWK0VAzNcXP0e68sDsgZRA/7fywCK+8sAozPLAgK+iP1y98sDew/LAgtrywAni8sDkMKpAqLnywO/O8sAm6PLATQBxQMayjj8=", - "dtype": "f4" - }, - "y": { - "bdata": "up2uvu/orT/bEiK+/2xov8Jb2T8iOVm/OmQPQMi4l0D42aq/Mcuqv5bRO0BrxbA/dRoevryEBEDZ6Rg/b/3WvrOXCUAEdau/7DXjP/k+q7+V/Ba/wHSrv3Pdlj1Qfau/PiokQF6QM0Aafg9AafNoP09yCD+ACR++jcqlP4wGkr6AcEBA0kouP5xabD/5aj+/Y+rsvwkpMz+tetU+H/Sqvz0Jq78g3nw//1PCPxmDq7/vg308a0Krv0Bnq7/5Aau/IhtOv/tfq78i0qq/yraqv6Z5qr/wRQvAUZ2rv4Djqr9FmKq/kqGwP3VBeD4=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000004", - "ACH-000005", - "ACH-000045", - "ACH-000113", - "ACH-000146", - "ACH-000168", - "ACH-000190", - "ACH-000195", - "ACH-000263", - "ACH-000294", - "ACH-000336", - "ACH-000362", - "ACH-000387", - "ACH-000406", - "ACH-000498", - "ACH-000557", - "ACH-000602", - "ACH-000770", - "ACH-001036", - "ACH-001129", - "ACH-001574", - "ACH-001577", - "ACH-001613", - "ACH-001618", - "ACH-001647", - "ACH-001656" - ], - "hoverinfo": "text", - "marker": { - "color": "#EF553B", - "size": 7 - }, - "mode": "markers", - "name": "Acute Myeloid Leukemia", - "text": [ - "Acute Myeloid Leukemia | ACH-000004", - "Acute Myeloid Leukemia | ACH-000005", - "Acute Myeloid Leukemia | ACH-000045", - "Acute Myeloid Leukemia | ACH-000113", - "Acute Myeloid Leukemia | ACH-000146", - "Acute Myeloid Leukemia | ACH-000168", - "Acute Myeloid Leukemia | ACH-000190", - "Acute Myeloid Leukemia | ACH-000195", - "Acute Myeloid Leukemia | ACH-000263", - "Acute Myeloid Leukemia | ACH-000294", - "Acute Myeloid Leukemia | ACH-000336", - "Acute Myeloid Leukemia | ACH-000362", - "Acute Myeloid Leukemia | ACH-000387", - "Acute Myeloid Leukemia | ACH-000406", - "Acute Myeloid Leukemia | ACH-000498", - "Acute Myeloid Leukemia | ACH-000557", - "Acute Myeloid Leukemia | ACH-000602", - "Acute Myeloid Leukemia | ACH-000770", - "Acute Myeloid Leukemia | ACH-001036", - "Acute Myeloid Leukemia | ACH-001129", - "Acute Myeloid Leukemia | ACH-001574", - "Acute Myeloid Leukemia | ACH-001577", - "Acute Myeloid Leukemia | ACH-001613", - "Acute Myeloid Leukemia | ACH-001618", - "Acute Myeloid Leukemia | ACH-001647", - "Acute Myeloid Leukemia | ACH-001656" - ], - "type": "scattergl", - "x": { - "bdata": "CJ/fP16jlT6TIrpAinkNQfzmdD6qGBi+C4skQLKkgT+lXzK/dFkmQJUt60Dc5rlAK434P0vczUCLIpk+4IwBwECUFEDt+pNAGDlGQOkUvb37sMRAtpkHQIODlUC0oEJAVFKOQL2JhEA=", - "dtype": "f4" - }, - "y": { - "bdata": "PxwGwL8xqL9U0oXAV4GbwBxNPMDLXgrAdhBnPvxjjb/64PG/C68qwACzkMBSwYXA0JwNwOuhesCgd/Y84oBMwOLsN8B/ZHLAV731vwxmR7/VaHfAJSQDwDgYGsA/xQjAlARnwAezc8A=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000007", - "ACH-000009", - "ACH-000202", - 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- }, - "mode": "markers", - "name": "Colorectal Adenocarcinoma", - "text": [ - "Colorectal Adenocarcinoma | ACH-000007", - "Colorectal Adenocarcinoma | ACH-000009", - "Colorectal Adenocarcinoma | ACH-000202", - "Colorectal Adenocarcinoma | ACH-000249", - "Colorectal Adenocarcinoma | ACH-000252", - "Colorectal Adenocarcinoma | ACH-000253", - "Colorectal Adenocarcinoma | ACH-000286", - "Colorectal Adenocarcinoma | ACH-000296", - "Colorectal Adenocarcinoma | ACH-000350", - "Colorectal Adenocarcinoma | ACH-000381", - "Colorectal Adenocarcinoma | ACH-000403", - "Colorectal Adenocarcinoma | ACH-000421", - "Colorectal Adenocarcinoma | ACH-000467", - "Colorectal Adenocarcinoma | ACH-000470", - "Colorectal Adenocarcinoma | ACH-000489", - "Colorectal Adenocarcinoma | ACH-000491", - "Colorectal Adenocarcinoma | ACH-000501", - "Colorectal Adenocarcinoma | ACH-000532", - "Colorectal Adenocarcinoma | ACH-000552", - "Colorectal Adenocarcinoma | ACH-000565", - "Colorectal Adenocarcinoma | ACH-000651", - "Colorectal Adenocarcinoma | ACH-000683", - "Colorectal Adenocarcinoma | ACH-000722", - "Colorectal Adenocarcinoma | ACH-000798", - "Colorectal Adenocarcinoma | ACH-000820", - "Colorectal Adenocarcinoma | ACH-000926", - "Colorectal Adenocarcinoma | ACH-000935", - "Colorectal Adenocarcinoma | ACH-000943", - "Colorectal Adenocarcinoma | ACH-000950", - "Colorectal Adenocarcinoma | ACH-000957", - "Colorectal Adenocarcinoma | ACH-000958", - "Colorectal Adenocarcinoma | ACH-000959", - "Colorectal Adenocarcinoma | ACH-000963", - "Colorectal Adenocarcinoma | ACH-000969", - "Colorectal Adenocarcinoma | ACH-000970", - "Colorectal Adenocarcinoma | ACH-000971", - "Colorectal Adenocarcinoma | ACH-000985", - "Colorectal Adenocarcinoma | ACH-000986", - "Colorectal Adenocarcinoma | ACH-000991", - "Colorectal Adenocarcinoma | ACH-000997", - "Colorectal Adenocarcinoma | ACH-001039", - "Colorectal Adenocarcinoma | ACH-001061", - "Colorectal Adenocarcinoma | ACH-001081", - "Colorectal Adenocarcinoma | ACH-001345", - "Colorectal Adenocarcinoma | ACH-001399", - "Colorectal Adenocarcinoma | ACH-001454", - "Colorectal Adenocarcinoma | ACH-001458", - "Colorectal Adenocarcinoma | ACH-001459", - "Colorectal Adenocarcinoma | ACH-001460", - "Colorectal Adenocarcinoma | ACH-001461", - "Colorectal Adenocarcinoma | ACH-001786", - "Colorectal Adenocarcinoma | ACH-002024", - "Colorectal Adenocarcinoma | ACH-002025", - "Colorectal Adenocarcinoma | ACH-002233", - "Colorectal Adenocarcinoma | ACH-002535", - "Colorectal Adenocarcinoma | ACH-002654", - "Colorectal Adenocarcinoma | ACH-002659", - "Colorectal Adenocarcinoma | ACH-002660", - "Colorectal Adenocarcinoma | ACH-002662", - "Colorectal Adenocarcinoma | ACH-002664", - "Colorectal Adenocarcinoma | ACH-002669" - ], - "type": "scattergl", - "x": { - "bdata": 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"ACH-000741", - "ACH-000753", - "ACH-000802", - "ACH-000834", - "ACH-000862", - "ACH-000896", - "ACH-000905", - "ACH-001183", - "ACH-001407", - "ACH-001409", - "ACH-001412", - "ACH-001413", - "ACH-001414", - "ACH-001415", - "ACH-001416" - ], - "hoverinfo": "text", - "marker": { - "color": "#AB63FA", - "size": 7 - }, - "mode": "markers", - "name": "Bladder Urothelial Carcinoma", - "text": [ - "Bladder Urothelial Carcinoma | ACH-000011", - "Bladder Urothelial Carcinoma | ACH-000018", - "Bladder Urothelial Carcinoma | ACH-000026", - "Bladder Urothelial Carcinoma | ACH-000127", - "Bladder Urothelial Carcinoma | ACH-000142", - "Bladder Urothelial Carcinoma | ACH-000242", - "Bladder Urothelial Carcinoma | ACH-000396", - "Bladder Urothelial Carcinoma | ACH-000473", - "Bladder Urothelial Carcinoma | ACH-000486", - "Bladder Urothelial Carcinoma | ACH-000522", - "Bladder Urothelial Carcinoma | ACH-000545", - "Bladder Urothelial Carcinoma | ACH-000547", - "Bladder Urothelial Carcinoma | ACH-000593", - "Bladder Urothelial Carcinoma | ACH-000720", - "Bladder Urothelial Carcinoma | ACH-000724", - "Bladder Urothelial Carcinoma | ACH-000741", - "Bladder Urothelial Carcinoma | ACH-000753", - "Bladder Urothelial Carcinoma | ACH-000802", - "Bladder Urothelial Carcinoma | ACH-000834", - "Bladder Urothelial Carcinoma | ACH-000862", - "Bladder Urothelial Carcinoma | ACH-000896", - "Bladder Urothelial Carcinoma | ACH-000905", - "Bladder Urothelial Carcinoma | ACH-001183", - "Bladder Urothelial Carcinoma | ACH-001407", - "Bladder Urothelial Carcinoma | ACH-001409", - "Bladder Urothelial Carcinoma | ACH-001412", - "Bladder Urothelial Carcinoma | ACH-001413", - "Bladder Urothelial Carcinoma | ACH-001414", - "Bladder Urothelial Carcinoma | ACH-001415", - "Bladder Urothelial Carcinoma | ACH-001416" - ], - "type": "scattergl", - "x": { - "bdata": 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"ACH-000585", - "ACH-000587", - "ACH-000589", - "ACH-000596", - "ACH-000627", - "ACH-000638", - "ACH-000662", - "ACH-000665", - "ACH-000666", - "ACH-000667", - "ACH-000672", - "ACH-000677", - "ACH-000681", - "ACH-000700", - "ACH-000706", - "ACH-000718", - "ACH-000747", - "ACH-000757", - "ACH-000766", - "ACH-000769", - "ACH-000774", - "ACH-000781", - "ACH-000785", - "ACH-000787", - "ACH-000791", - "ACH-000826", - "ACH-000837", - "ACH-000840", - "ACH-000841", - "ACH-000843", - "ACH-000845", - "ACH-000851", - "ACH-000853", - "ACH-000858", - "ACH-000860", - "ACH-000861", - "ACH-000867", - "ACH-000869", - "ACH-000872", - "ACH-000878", - "ACH-000886", - "ACH-000888", - "ACH-000894", - "ACH-000900", - "ACH-000901", - "ACH-000916", - "ACH-000921", - "ACH-000924", - "ACH-000929", - "ACH-000945", - "ACH-000975", - "ACH-000980", - "ACH-001075", - "ACH-001137", - "ACH-001233", - "ACH-002035", - "ACH-002156", - "ACH-002522", - "ACH-002526", - "ACH-002531", - "ACH-002650", - "ACH-003012" - ], - "hoverinfo": "text", - "marker": { - "color": "#FFA15A", - "size": 7 - }, - "mode": "markers", - "name": "Non-Small Cell Lung Cancer", - "text": [ - "Non-Small Cell Lung Cancer | ACH-000012", - "Non-Small Cell Lung Cancer | ACH-000015", - "Non-Small Cell Lung Cancer | ACH-000021", - "Non-Small Cell Lung Cancer | ACH-000029", - "Non-Small Cell Lung Cancer | ACH-000030", - "Non-Small Cell Lung Cancer | ACH-000035", - "Non-Small Cell Lung Cancer | ACH-000143", - "Non-Small Cell Lung Cancer | ACH-000161", - "Non-Small Cell Lung Cancer | ACH-000176", - "Non-Small Cell Lung Cancer | ACH-000251", - "Non-Small Cell Lung Cancer | ACH-000261", - "Non-Small Cell Lung Cancer | ACH-000264", - "Non-Small Cell Lung Cancer | ACH-000311", - "Non-Small Cell Lung Cancer | ACH-000337", - "Non-Small Cell Lung Cancer | ACH-000339", - "Non-Small Cell Lung Cancer | ACH-000343", - "Non-Small Cell Lung Cancer | ACH-000378", - "Non-Small Cell Lung Cancer | ACH-000390", - "Non-Small Cell Lung Cancer | ACH-000395", - "Non-Small Cell Lung Cancer | ACH-000414", - "Non-Small Cell Lung Cancer | ACH-000416", - "Non-Small Cell Lung Cancer | ACH-000434", - "Non-Small Cell Lung Cancer | ACH-000438", - "Non-Small Cell Lung Cancer | ACH-000442", - "Non-Small Cell Lung Cancer | ACH-000444", - "Non-Small Cell Lung Cancer | ACH-000448", - "Non-Small Cell Lung Cancer | ACH-000454", - "Non-Small Cell Lung Cancer | ACH-000463", - "Non-Small Cell Lung Cancer | ACH-000481", - "Non-Small Cell Lung Cancer | ACH-000496", - "Non-Small Cell Lung Cancer | ACH-000510", - "Non-Small Cell Lung Cancer | ACH-000511", - "Non-Small Cell Lung Cancer | ACH-000521", - "Non-Small Cell Lung Cancer | ACH-000528", - "Non-Small Cell Lung Cancer | ACH-000562", - "Non-Small Cell Lung Cancer | ACH-000563", - "Non-Small Cell Lung Cancer | ACH-000585", - "Non-Small Cell Lung Cancer | ACH-000587", - "Non-Small Cell Lung Cancer | ACH-000589", - "Non-Small Cell Lung Cancer | ACH-000596", - "Non-Small Cell Lung Cancer | ACH-000627", - "Non-Small Cell Lung Cancer | ACH-000638", - "Non-Small Cell Lung Cancer | ACH-000662", - "Non-Small Cell Lung Cancer | ACH-000665", - "Non-Small Cell Lung Cancer | ACH-000666", - "Non-Small Cell Lung Cancer | ACH-000667", - "Non-Small Cell Lung Cancer | ACH-000672", - "Non-Small Cell Lung Cancer | ACH-000677", - "Non-Small Cell Lung Cancer | ACH-000681", - "Non-Small Cell Lung Cancer | ACH-000700", - "Non-Small Cell Lung Cancer | ACH-000706", - "Non-Small Cell Lung Cancer | ACH-000718", - "Non-Small Cell Lung Cancer | ACH-000747", - "Non-Small Cell Lung Cancer | ACH-000757", - "Non-Small Cell Lung Cancer | ACH-000766", - "Non-Small Cell Lung Cancer | ACH-000769", - "Non-Small Cell Lung Cancer | ACH-000774", - "Non-Small Cell Lung Cancer | ACH-000781", - "Non-Small Cell Lung Cancer | ACH-000785", - "Non-Small Cell Lung Cancer | ACH-000787", - "Non-Small Cell Lung Cancer | ACH-000791", - "Non-Small Cell Lung Cancer | ACH-000826", - "Non-Small Cell Lung Cancer | ACH-000837", - "Non-Small Cell Lung Cancer | ACH-000840", - "Non-Small Cell Lung Cancer | ACH-000841", - "Non-Small Cell Lung Cancer | ACH-000843", - "Non-Small Cell Lung Cancer | ACH-000845", - "Non-Small Cell Lung Cancer | ACH-000851", - "Non-Small Cell Lung Cancer | ACH-000853", - "Non-Small Cell Lung Cancer | ACH-000858", - "Non-Small Cell Lung Cancer | ACH-000860", - "Non-Small Cell Lung Cancer | ACH-000861", - "Non-Small Cell Lung Cancer | ACH-000867", - "Non-Small Cell Lung Cancer | ACH-000869", - "Non-Small Cell Lung Cancer | ACH-000872", - "Non-Small Cell Lung Cancer | ACH-000878", - "Non-Small Cell Lung Cancer | ACH-000886", - "Non-Small Cell Lung Cancer | ACH-000888", - "Non-Small Cell Lung Cancer | ACH-000894", - "Non-Small Cell Lung Cancer | ACH-000900", - "Non-Small Cell Lung Cancer | ACH-000901", - "Non-Small Cell Lung Cancer | ACH-000916", - "Non-Small Cell Lung Cancer | ACH-000921", - "Non-Small Cell Lung Cancer | ACH-000924", - "Non-Small Cell Lung Cancer | ACH-000929", - "Non-Small Cell Lung Cancer | ACH-000945", - "Non-Small Cell Lung Cancer | ACH-000975", - "Non-Small Cell Lung Cancer | ACH-000980", - "Non-Small Cell Lung Cancer | ACH-001075", - "Non-Small Cell Lung Cancer | ACH-001137", - "Non-Small Cell Lung Cancer | ACH-001233", - "Non-Small Cell Lung Cancer | ACH-002035", - "Non-Small Cell Lung Cancer | ACH-002156", - "Non-Small Cell Lung Cancer | ACH-002522", - "Non-Small Cell Lung Cancer | ACH-002526", - "Non-Small Cell Lung Cancer | ACH-002531", - "Non-Small Cell Lung Cancer | ACH-002650", - "Non-Small Cell Lung Cancer | ACH-003012" - ], - "type": "scattergl", - "x": { - "bdata": 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"ACH-000827", - "ACH-000881", - "ACH-000882", - "ACH-000884", - "ACH-000899", - "ACH-000915", - "ACH-000968", - "ACH-001041", - "ACH-001190", - "ACH-001239", - "ACH-001522", - "ACH-001563", - "ACH-001566", - "ACH-001567", - "ACH-001568", - "ACH-001570", - "ACH-001645", - "ACH-001970", - "ACH-001972", - "ACH-001973", - "ACH-001975", - "ACH-001982", - "ACH-001986", - "ACH-001990", - "ACH-002001", - "ACH-002002", - "ACH-002003", - "ACH-002004", - "ACH-002005", - "ACH-002084", - "ACH-002143", - "ACH-002458", - "ACH-002460", - "ACH-002461", - "ACH-002508", - "ACH-002510", - "ACH-002511", - "ACH-002512", - "ACH-002847", - "ACH-002928" - ], - "hoverinfo": "text", - "marker": { - "color": "#19D3F3", - "size": 7 - }, - "mode": "markers", - "name": "Melanoma", - "text": [ - "Melanoma | ACH-000014", - "Melanoma | ACH-000219", - "Melanoma | ACH-000274", - "Melanoma | ACH-000304", - "Melanoma | ACH-000322", - "Melanoma | ACH-000348", - "Melanoma | ACH-000401", - "Melanoma | ACH-000404", - "Melanoma | ACH-000425", - "Melanoma | ACH-000441", - "Melanoma | ACH-000450", - "Melanoma | ACH-000458", - "Melanoma | ACH-000477", - "Melanoma | ACH-000550", - "Melanoma | ACH-000579", - "Melanoma | ACH-000580", - "Melanoma | ACH-000614", - "Melanoma | ACH-000632", - "Melanoma | ACH-000661", - "Melanoma | ACH-000765", - "Melanoma | ACH-000788", - "Melanoma | ACH-000799", - "Melanoma | ACH-000801", - "Melanoma | ACH-000805", - "Melanoma | ACH-000810", - "Melanoma | ACH-000822", - "Melanoma | ACH-000827", - "Melanoma | ACH-000881", - "Melanoma | ACH-000882", - "Melanoma | ACH-000884", - "Melanoma | ACH-000899", - "Melanoma | ACH-000915", - "Melanoma | ACH-000968", - "Melanoma | ACH-001041", - "Melanoma | ACH-001190", - "Melanoma | ACH-001239", - "Melanoma | ACH-001522", - "Melanoma | ACH-001563", - "Melanoma | ACH-001566", - "Melanoma | ACH-001567", - "Melanoma | ACH-001568", - "Melanoma | ACH-001570", - "Melanoma | ACH-001645", - "Melanoma | ACH-001970", - "Melanoma | ACH-001972", - "Melanoma | ACH-001973", - "Melanoma | ACH-001975", - "Melanoma | ACH-001982", - "Melanoma | ACH-001986", - "Melanoma | ACH-001990", - "Melanoma | ACH-002001", - "Melanoma | ACH-002002", - "Melanoma | ACH-002003", - "Melanoma | ACH-002004", - "Melanoma | ACH-002005", - "Melanoma | ACH-002084", - "Melanoma | ACH-002143", - "Melanoma | ACH-002458", - "Melanoma | ACH-002460", - "Melanoma | ACH-002461", - "Melanoma | ACH-002508", - "Melanoma | ACH-002510", - "Melanoma | ACH-002511", - "Melanoma | ACH-002512", - "Melanoma | ACH-002847", - "Melanoma | ACH-002928" - ], - "type": "scattergl", - "x": { - "bdata": "7FguQHmL30A+qSDA8ygIPyhld0CrGKS/lgovQOSw8sDf0vLA5OaQQDLM8sDNs/LA9c2LPb0bEsC82/LAty3WvUNfc0BUbh1ANrPywAKysD8wpNE/1uCfvCPZ8sAykL4/dFanPvkxJ8D4G6I/1idpQLe8lkAYiltA1dDywOh/k0CW3YFAJnsiQG6/nL/vi35AYyK1P8/Y8sDq3fLA2OHywEPW8sB4w/LAAW70vX24CEDqtPLA/LvywPfA8sCaEGJALhuHQFgLrEDeeZFAz9DVQG8nC0DmyvLAma1oQP3jDr9cfDnAqgojQNYVFkB+fTU++15nvyDZdEAK217Auim3PktPfb0rfhvA", - "dtype": "f4" - }, - "y": { - "bdata": 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"ACH-001393", - "ACH-001394", - "ACH-001396", - "ACH-001419", - "ACH-001662", - "ACH-001683", - "ACH-001819", - "ACH-002179", - "ACH-002399", - "ACH-002401" - ], - "hoverinfo": "text", - "marker": { - "color": "#FF6692", - "size": 7 - }, - "mode": "markers", - "name": "Invasive Breast Carcinoma", - "text": [ - "Invasive Breast Carcinoma | ACH-000017", - "Invasive Breast Carcinoma | ACH-000019", - "Invasive Breast Carcinoma | ACH-000028", - "Invasive Breast Carcinoma | ACH-000097", - "Invasive Breast Carcinoma | ACH-000111", - "Invasive Breast Carcinoma | ACH-000147", - "Invasive Breast Carcinoma | ACH-000148", - "Invasive Breast Carcinoma | ACH-000212", - "Invasive Breast Carcinoma | ACH-000223", - "Invasive Breast Carcinoma | ACH-000248", - "Invasive Breast Carcinoma | ACH-000258", - "Invasive Breast Carcinoma | ACH-000276", - "Invasive Breast Carcinoma | ACH-000277", - "Invasive Breast Carcinoma | ACH-000288", - "Invasive Breast Carcinoma | ACH-000330", - "Invasive Breast Carcinoma | ACH-000352", - "Invasive Breast Carcinoma | ACH-000374", - "Invasive Breast Carcinoma | ACH-000554", - "Invasive Breast Carcinoma | ACH-000573", - "Invasive Breast Carcinoma | ACH-000621", - "Invasive Breast Carcinoma | ACH-000668", - "Invasive Breast Carcinoma | ACH-000699", - "Invasive Breast Carcinoma | ACH-000711", - "Invasive Breast Carcinoma | ACH-000721", - "Invasive Breast Carcinoma | ACH-000768", - "Invasive Breast Carcinoma | ACH-000783", - "Invasive Breast Carcinoma | ACH-000849", - "Invasive Breast Carcinoma | ACH-000856", - "Invasive Breast Carcinoma | ACH-000876", - "Invasive Breast Carcinoma | ACH-000910", - "Invasive Breast Carcinoma | ACH-000934", - "Invasive Breast Carcinoma | ACH-001065", - "Invasive Breast Carcinoma | ACH-001388", - "Invasive Breast Carcinoma | ACH-001389", - "Invasive Breast Carcinoma | ACH-001390", - "Invasive Breast Carcinoma | ACH-001391", - "Invasive Breast Carcinoma | ACH-001392", - "Invasive Breast Carcinoma | ACH-001393", - "Invasive Breast Carcinoma | ACH-001394", - "Invasive Breast Carcinoma | ACH-001396", - "Invasive Breast Carcinoma | ACH-001419", - "Invasive Breast Carcinoma | ACH-001662", - "Invasive Breast Carcinoma | ACH-001683", - "Invasive Breast Carcinoma | ACH-001819", - "Invasive Breast Carcinoma | ACH-002179", - "Invasive Breast Carcinoma | ACH-002399", - "Invasive Breast Carcinoma | ACH-002401" - ], - "type": "scattergl", - "x": { - "bdata": "rkW1vVsoAEC1uoxAFfaQPyCmQ0DKLFpAbvxLPyOzmz+cVMO/HdnmP3/4gr+78l2/4kURPS1q7z87dn0/WEV5P8gN6z/dOwzAAqDbPxi3YMB1QIq/UP/2v/OVE0B8c05ABCWeP5jKOsAQ9GZA6EPrQCD1eb9wwn1AgExdwCFbr0BMPAvAzsvywIwbxz+MbTPArtLywFrW8sCez/LAeu3ywG3mAz+T0LS+WhW8PonUvb9DUUdA7QmoPxqJEkA=", - "dtype": "f4" - }, - "y": { - "bdata": "2bE+v8uRlr/uW82/IfMhv8F8AcB+tZi/C1nlP9Abtz7lxHy9p5q1v5IsjT5cP4Y/GMIpv20cMkDw29G+SpiMvwIcrb6yKO2/piLDPkJOoj/6oYy/zqSpP1OKkr+gFWi/qcpCvgkCPL9qFEa/gxMJPEUssr/+thPAkVHSv+bVCsAyckg/nJ2qv1hXXT8Xl0k/Ewurv+Oyqr/OFKu/Z7+qv9uNGD7hwHY8PX7uvh4BAL9aYB7AyrsqvkJNu70=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000022", - "ACH-000023", - "ACH-000042", - "ACH-000060", - "ACH-000085", - "ACH-000093", - "ACH-000094", - "ACH-000114", - "ACH-000118", - "ACH-000138", - "ACH-000139", - "ACH-000155", - "ACH-000164", - "ACH-000178", - "ACH-000213", - "ACH-000222", - "ACH-000235", - "ACH-000243", - "ACH-000265", - "ACH-000266", - "ACH-000281", - "ACH-000307", - "ACH-000320", - "ACH-000332", - "ACH-000354", - "ACH-000417", - "ACH-000468", - "ACH-000502", - "ACH-000517", - "ACH-000535", - "ACH-000599", - "ACH-000601", - "ACH-000652", - "ACH-001098", - "ACH-001107", - "ACH-001353", - "ACH-001375", - "ACH-001377", - "ACH-001379", - "ACH-001380", - "ACH-001382", - "ACH-001999", - "ACH-002039", - "ACH-002186", - "ACH-002672" - ], - "hoverinfo": "text", - "marker": { - "color": "#B6E880", - "size": 7 - }, - "mode": "markers", - "name": "Pancreatic Adenocarcinoma", - "text": [ - "Pancreatic Adenocarcinoma | ACH-000022", - "Pancreatic Adenocarcinoma | ACH-000023", - "Pancreatic Adenocarcinoma | ACH-000042", - "Pancreatic Adenocarcinoma | ACH-000060", - "Pancreatic Adenocarcinoma | ACH-000085", - "Pancreatic Adenocarcinoma | ACH-000093", - "Pancreatic Adenocarcinoma | ACH-000094", - "Pancreatic Adenocarcinoma | ACH-000114", - "Pancreatic Adenocarcinoma | ACH-000118", - "Pancreatic Adenocarcinoma | ACH-000138", - "Pancreatic Adenocarcinoma | ACH-000139", - "Pancreatic Adenocarcinoma | ACH-000155", - "Pancreatic Adenocarcinoma | ACH-000164", - "Pancreatic Adenocarcinoma | ACH-000178", - "Pancreatic Adenocarcinoma | ACH-000213", - "Pancreatic Adenocarcinoma | ACH-000222", - "Pancreatic Adenocarcinoma | ACH-000235", - "Pancreatic Adenocarcinoma | ACH-000243", - "Pancreatic Adenocarcinoma | ACH-000265", - "Pancreatic Adenocarcinoma | ACH-000266", - "Pancreatic Adenocarcinoma | ACH-000281", - "Pancreatic Adenocarcinoma | ACH-000307", - "Pancreatic Adenocarcinoma | ACH-000320", - "Pancreatic Adenocarcinoma | ACH-000332", - "Pancreatic Adenocarcinoma | ACH-000354", - "Pancreatic Adenocarcinoma | ACH-000417", - "Pancreatic Adenocarcinoma | ACH-000468", - "Pancreatic Adenocarcinoma | ACH-000502", - "Pancreatic Adenocarcinoma | ACH-000517", - "Pancreatic Adenocarcinoma | ACH-000535", - "Pancreatic Adenocarcinoma | ACH-000599", - "Pancreatic Adenocarcinoma | ACH-000601", - "Pancreatic Adenocarcinoma | ACH-000652", - "Pancreatic Adenocarcinoma | ACH-001098", - "Pancreatic Adenocarcinoma | ACH-001107", - "Pancreatic Adenocarcinoma | ACH-001353", - "Pancreatic Adenocarcinoma | ACH-001375", - "Pancreatic Adenocarcinoma | ACH-001377", - "Pancreatic Adenocarcinoma | ACH-001379", - "Pancreatic Adenocarcinoma | ACH-001380", - "Pancreatic Adenocarcinoma | ACH-001382", - "Pancreatic Adenocarcinoma | ACH-001999", - "Pancreatic Adenocarcinoma | ACH-002039", - "Pancreatic Adenocarcinoma | ACH-002186", - "Pancreatic Adenocarcinoma | ACH-002672" - ], - "type": "scattergl", - "x": { - "bdata": 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"ACH-000660", - "ACH-000697", - "ACH-000714", - "ACH-000763", - "ACH-000817", - "ACH-000821", - "ACH-000829", - "ACH-000838", - "ACH-000889", - "ACH-000914", - "ACH-000944", - "ACH-001450", - "ACH-001498", - "ACH-001533", - "ACH-001539", - "ACH-001616", - "ACH-001634", - "ACH-001639", - "ACH-001677", - "ACH-001707", - "ACH-001709", - "ACH-002055", - "ACH-002062", - "ACH-002214", - "ACH-002215", - "ACH-002478", - "ACH-002485", - "ACH-002500", - "ACH-002677", - "ACH-002678" - ], - "hoverinfo": "text", - "marker": { - "color": "#FF97FF", - "size": 7 - }, - "mode": "markers", - "name": "Mature B-Cell Neoplasms", - "text": [ - "Mature B-Cell Neoplasms | ACH-000024", - "Mature B-Cell Neoplasms | ACH-000106", - "Mature B-Cell Neoplasms | ACH-000124", - "Mature B-Cell Neoplasms | ACH-000167", - "Mature B-Cell Neoplasms | ACH-000183", - "Mature B-Cell Neoplasms | ACH-000204", - "Mature B-Cell Neoplasms | ACH-000271", - "Mature B-Cell Neoplasms | ACH-000315", - "Mature B-Cell Neoplasms | ACH-000334", - "Mature B-Cell Neoplasms | ACH-000346", - "Mature B-Cell Neoplasms | ACH-000363", - "Mature B-Cell Neoplasms | ACH-000365", - "Mature B-Cell Neoplasms | ACH-000371", - "Mature B-Cell Neoplasms | ACH-000398", - "Mature B-Cell Neoplasms | ACH-000402", - "Mature B-Cell Neoplasms | ACH-000405", - "Mature B-Cell Neoplasms | ACH-000426", - "Mature B-Cell Neoplasms | ACH-000436", - "Mature B-Cell Neoplasms | ACH-000512", - "Mature B-Cell Neoplasms | ACH-000541", - "Mature B-Cell Neoplasms | ACH-000567", - "Mature B-Cell Neoplasms | ACH-000576", - "Mature B-Cell Neoplasms | ACH-000588", - "Mature B-Cell Neoplasms | ACH-000653", - "Mature B-Cell Neoplasms | ACH-000654", - "Mature B-Cell Neoplasms | ACH-000656", - "Mature B-Cell Neoplasms | ACH-000660", - "Mature B-Cell Neoplasms | ACH-000697", - "Mature B-Cell Neoplasms | ACH-000714", - "Mature B-Cell Neoplasms | ACH-000763", - "Mature B-Cell Neoplasms | ACH-000817", - "Mature B-Cell Neoplasms | ACH-000821", - "Mature B-Cell Neoplasms | ACH-000829", - "Mature B-Cell Neoplasms | ACH-000838", - "Mature B-Cell Neoplasms | ACH-000889", - "Mature B-Cell Neoplasms | ACH-000914", - "Mature B-Cell Neoplasms | ACH-000944", - "Mature B-Cell Neoplasms | ACH-001450", - "Mature B-Cell Neoplasms | ACH-001498", - "Mature B-Cell Neoplasms | ACH-001533", - "Mature B-Cell Neoplasms | ACH-001539", - "Mature B-Cell Neoplasms | ACH-001616", - "Mature B-Cell Neoplasms | ACH-001634", - "Mature B-Cell Neoplasms | ACH-001639", - "Mature B-Cell Neoplasms | ACH-001677", - "Mature B-Cell Neoplasms | ACH-001707", - "Mature B-Cell Neoplasms | ACH-001709", - "Mature B-Cell Neoplasms | ACH-002055", - "Mature B-Cell Neoplasms | ACH-002062", - "Mature B-Cell Neoplasms | ACH-002214", - "Mature B-Cell Neoplasms | ACH-002215", - "Mature B-Cell Neoplasms | ACH-002478", - "Mature B-Cell Neoplasms | ACH-002485", - "Mature B-Cell Neoplasms | ACH-002500", - "Mature B-Cell Neoplasms | ACH-002677", - "Mature B-Cell Neoplasms | ACH-002678" - ], - 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ACH-001067", - "Meningothelial Tumor | ACH-002070" - ], - "type": "scattergl", - "x": { - "bdata": "28RMQHnG8sDmH4I/", - "dtype": "f4" - }, - "y": { - "bdata": "nxIiQJ+aqr9v4ds/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000036", - "ACH-000040", - "ACH-000067", - "ACH-000075", - "ACH-000098", - "ACH-000128", - "ACH-000137", - "ACH-000152", - "ACH-000200", - "ACH-000208", - "ACH-000215", - "ACH-000231", - "ACH-000232", - "ACH-000244", - "ACH-000269", - "ACH-000273", - "ACH-000323", - "ACH-000329", - "ACH-000368", - "ACH-000370", - "ACH-000376", - "ACH-000389", - "ACH-000437", - "ACH-000445", - "ACH-000455", - "ACH-000464", - "ACH-000469", - "ACH-000479", - "ACH-000504", - "ACH-000558", - "ACH-000570", - "ACH-000571", - "ACH-000591", - "ACH-000592", - "ACH-000595", - "ACH-000609", - "ACH-000622", - "ACH-000623", - "ACH-000631", - "ACH-000634", - "ACH-000655", - "ACH-000673", - "ACH-000676", - "ACH-000738", - "ACH-000756", - "ACH-000760", - "ACH-000807", - "ACH-000819", - "ACH-000863", - "ACH-000887", - "ACH-001016", - "ACH-001126", - "ACH-001172", - "ACH-001329", - "ACH-001605", - "ACH-001606", - "ACH-001608", - "ACH-001609", - "ACH-001610", - "ACH-001611", - "ACH-001622", - "ACH-001623", - "ACH-001624", - "ACH-002228", - "ACH-002229", - "ACH-002230", - "ACH-002257", - "ACH-002269", - "ACH-002304", - "ACH-002680" - ], - "hoverinfo": "text", - "marker": { - "color": "#FD3216", - "size": 7 - }, - "mode": "markers", - "name": "Diffuse Glioma", - "text": [ - "Diffuse Glioma | ACH-000036", - "Diffuse Glioma | ACH-000040", - "Diffuse Glioma | ACH-000067", - "Diffuse Glioma | ACH-000075", - "Diffuse Glioma | ACH-000098", - "Diffuse Glioma | ACH-000128", - "Diffuse Glioma | ACH-000137", - "Diffuse Glioma | ACH-000152", - "Diffuse Glioma | ACH-000200", - "Diffuse Glioma | ACH-000208", - "Diffuse Glioma | ACH-000215", - "Diffuse Glioma | ACH-000231", - "Diffuse Glioma | ACH-000232", - "Diffuse Glioma | ACH-000244", - "Diffuse Glioma | ACH-000269", - "Diffuse Glioma | ACH-000273", - "Diffuse Glioma | ACH-000323", - "Diffuse Glioma | ACH-000329", - "Diffuse Glioma | ACH-000368", - "Diffuse Glioma | ACH-000370", - "Diffuse Glioma | ACH-000376", - "Diffuse Glioma | ACH-000389", - "Diffuse Glioma | ACH-000437", - "Diffuse Glioma | ACH-000445", - "Diffuse Glioma | ACH-000455", - "Diffuse Glioma | ACH-000464", - "Diffuse Glioma | ACH-000469", - "Diffuse Glioma | ACH-000479", - "Diffuse Glioma | ACH-000504", - "Diffuse Glioma | ACH-000558", - "Diffuse Glioma | ACH-000570", - "Diffuse Glioma | ACH-000571", - "Diffuse Glioma | ACH-000591", - "Diffuse Glioma | ACH-000592", - "Diffuse Glioma | ACH-000595", - "Diffuse Glioma | ACH-000609", - "Diffuse Glioma | ACH-000622", - "Diffuse Glioma | ACH-000623", - "Diffuse Glioma | ACH-000631", - "Diffuse Glioma | ACH-000634", - "Diffuse Glioma | ACH-000655", - "Diffuse Glioma | ACH-000673", - "Diffuse Glioma | ACH-000676", - "Diffuse Glioma | ACH-000738", - "Diffuse Glioma | ACH-000756", - "Diffuse Glioma | ACH-000760", - "Diffuse Glioma | ACH-000807", - "Diffuse Glioma | ACH-000819", - "Diffuse Glioma | ACH-000863", - "Diffuse Glioma | ACH-000887", - "Diffuse Glioma | ACH-001016", - "Diffuse Glioma | ACH-001126", - "Diffuse Glioma | ACH-001172", - "Diffuse Glioma | ACH-001329", - "Diffuse Glioma | ACH-001605", - "Diffuse Glioma | ACH-001606", - "Diffuse Glioma | ACH-001608", - "Diffuse Glioma | ACH-001609", - "Diffuse Glioma | ACH-001610", - "Diffuse Glioma | ACH-001611", - "Diffuse Glioma | ACH-001622", - "Diffuse Glioma | ACH-001623", - "Diffuse Glioma | ACH-001624", - "Diffuse Glioma | ACH-002228", - "Diffuse Glioma | ACH-002229", - "Diffuse Glioma | ACH-002230", - "Diffuse Glioma | ACH-002257", - "Diffuse Glioma | ACH-002269", - "Diffuse Glioma | ACH-002304", - "Diffuse Glioma | ACH-002680" - ], - "type": "scattergl", - "x": { - "bdata": 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[ - "Sarcoma, NOS | ACH-000037" - ], - "type": "scattergl", - "x": { - "bdata": "P0j4vw==", - "dtype": "f4" - }, - "y": { - "bdata": "yalAQA==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000039", - "ACH-000041", - "ACH-000052", - "ACH-000087", - "ACH-000210", - "ACH-000279", - "ACH-000391", - "ACH-000424", - "ACH-000499", - "ACH-001029", - "ACH-001038", - "ACH-001192", - "ACH-001193", - "ACH-001205", - "ACH-001283", - "ACH-001430", - "ACH-001431", - "ACH-002105", - "ACH-002106", - "ACH-002109", - "ACH-002110", - "ACH-002114", - "ACH-002116", - "ACH-002119", - "ACH-002160" - ], - "hoverinfo": "text", - "marker": { - "color": "#6A76FC", - "size": 7 - }, - "mode": "markers", - "name": "Ewing Sarcoma", - "text": [ - "Ewing Sarcoma | ACH-000039", - "Ewing Sarcoma | ACH-000041", - "Ewing Sarcoma | ACH-000052", - "Ewing Sarcoma | ACH-000087", - "Ewing Sarcoma | ACH-000210", - "Ewing Sarcoma | ACH-000279", - "Ewing Sarcoma | ACH-000391", - "Ewing Sarcoma | ACH-000424", - "Ewing Sarcoma | ACH-000499", - "Ewing Sarcoma | ACH-001029", - "Ewing Sarcoma | ACH-001038", - "Ewing Sarcoma | ACH-001192", - "Ewing Sarcoma | ACH-001193", - "Ewing Sarcoma | ACH-001205", - "Ewing Sarcoma | ACH-001283", - "Ewing Sarcoma | ACH-001430", - "Ewing Sarcoma | ACH-001431", - "Ewing Sarcoma | ACH-002105", - "Ewing Sarcoma | ACH-002106", - "Ewing Sarcoma | ACH-002109", - "Ewing Sarcoma | ACH-002110", - "Ewing Sarcoma | ACH-002114", - "Ewing Sarcoma | ACH-002116", - "Ewing Sarcoma | ACH-002119", - "Ewing Sarcoma | ACH-002160" - ], - "type": "scattergl", - "x": { - "bdata": "/wQSv7AlDb3bRMc+yCtKQOPfhT986IZAAj6OQCvLu0AnEVdADYStQHagTUDuKeo/G0GIP47ntz/g1CFAAqWKP1SgBkCcbHU/J7CIQOQ79z8jCM1ALs/ywJ3w8sBIC7FAhNuoQA==", - "dtype": "f4" - }, - "y": { - "bdata": "IXZBP4dmHb4FDwpA7+bKvkKtt75+OHm/UULXPw9Wiz/OXy8/OH50P0YH7b9y5B4/IKjGP47Tpb2pkLI+6oPIPvlNur5i51pA5uLuvzqBhz8Jrtm9eJ+qv/hpqr8LSEc/4wmlvg==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000047", - "ACH-000144", - "ACH-000216", - "ACH-000239", - "ACH-000247", - "ACH-000255", - "ACH-000303", - "ACH-000325", - "ACH-000344", - "ACH-000356", - "ACH-000383", - "ACH-000427", - "ACH-000466", - "ACH-000485", - "ACH-000507", - "ACH-000581", - "ACH-000616", - "ACH-000633", - "ACH-000736", - "ACH-000746", - "ACH-000758", - "ACH-000764", - "ACH-000793", - "ACH-000847", - "ACH-000880", - "ACH-000898", - "ACH-000911", - "ACH-000919", - "ACH-000932", - "ACH-000948", - "ACH-001368", - "ACH-001496", - "ACH-001497", - "ACH-001500", - "ACH-001544", - "ACH-001653", - "ACH-001654", - "ACH-001664", - "ACH-002141", - "ACH-002161", - "ACH-002202", - "ACH-002446", - "ACH-002705", - "ACH-002706" - ], - "hoverinfo": "text", - "marker": { - "color": "#FED4C4", - "size": 7 - }, - "mode": "markers", - "name": "Esophagogastric Adenocarcinoma", - "text": [ - "Esophagogastric Adenocarcinoma | ACH-000047", - "Esophagogastric Adenocarcinoma | ACH-000144", - "Esophagogastric Adenocarcinoma | ACH-000216", - "Esophagogastric Adenocarcinoma | ACH-000239", - "Esophagogastric Adenocarcinoma | ACH-000247", - "Esophagogastric Adenocarcinoma | ACH-000255", - "Esophagogastric Adenocarcinoma | ACH-000303", - "Esophagogastric Adenocarcinoma | ACH-000325", - "Esophagogastric Adenocarcinoma | ACH-000344", - "Esophagogastric Adenocarcinoma | ACH-000356", - "Esophagogastric Adenocarcinoma | ACH-000383", - "Esophagogastric Adenocarcinoma | ACH-000427", - "Esophagogastric Adenocarcinoma | ACH-000466", - "Esophagogastric Adenocarcinoma | ACH-000485", - "Esophagogastric Adenocarcinoma | ACH-000507", - "Esophagogastric Adenocarcinoma | ACH-000581", - "Esophagogastric Adenocarcinoma | ACH-000616", - "Esophagogastric Adenocarcinoma | ACH-000633", - "Esophagogastric Adenocarcinoma | ACH-000736", - "Esophagogastric Adenocarcinoma | ACH-000746", - "Esophagogastric Adenocarcinoma | ACH-000758", - "Esophagogastric Adenocarcinoma | ACH-000764", - "Esophagogastric Adenocarcinoma | ACH-000793", - "Esophagogastric Adenocarcinoma | ACH-000847", - "Esophagogastric Adenocarcinoma | ACH-000880", - "Esophagogastric Adenocarcinoma | ACH-000898", - "Esophagogastric Adenocarcinoma | ACH-000911", - "Esophagogastric Adenocarcinoma | ACH-000919", - "Esophagogastric Adenocarcinoma | ACH-000932", - "Esophagogastric Adenocarcinoma | ACH-000948", - "Esophagogastric Adenocarcinoma | ACH-001368", - "Esophagogastric Adenocarcinoma | ACH-001496", - "Esophagogastric Adenocarcinoma | ACH-001497", - "Esophagogastric Adenocarcinoma | ACH-001500", - "Esophagogastric Adenocarcinoma | ACH-001544", - "Esophagogastric Adenocarcinoma | ACH-001653", - "Esophagogastric Adenocarcinoma | ACH-001654", - "Esophagogastric Adenocarcinoma | ACH-001664", - "Esophagogastric Adenocarcinoma | ACH-002141", - "Esophagogastric Adenocarcinoma | ACH-002161", - "Esophagogastric Adenocarcinoma | ACH-002202", - "Esophagogastric Adenocarcinoma | ACH-002446", - "Esophagogastric Adenocarcinoma | ACH-002705", - "Esophagogastric Adenocarcinoma | ACH-002706" - ], - "type": "scattergl", - "x": { - "bdata": "KoaZQC9qNMBw1tA/jXZwvdRGM0CQRqg/qqQNQHFKaEA+XU0/QySWP2aYA70+vPLA0QapvpPCBEBPEINAa5HKP3I5Bb8/nlNAS45eQJ5Dqj9d00tAUsTywLk9V0ALwvLAwCWMQNPURT/CqHhAbIHPP9eYf0CSKWRAZMUnQGiUdj+6a38/0I5OQJx+8b6tEPs/BXkBQNnFo0C1QKZAcmweQLj4GEC/AEBAIDotQFyygEA=", - "dtype": "f4" - }, - "y": { - "bdata": "AGfAv1HNsT7J2oA/1BMQPfTowL+UAxZA/U0avyNRPsAAwJA/3xu/vqk24r+rcau/4AgrQOu9nb+kqtW/OfgTwMB4B0AdwZW/ZH3+v514H8AyYZK/t6+qv+/uJ8Dj5qq/wtBDvro4/L9y65m/0dqmvq/wCcCEp22/P3IJwCJc6b8WUdy/3156PwCYyr9u+J2/6QsaQJqvSsBhSBHAhFpRv34Rhr407t++hIfGvoyKM78=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000053", - "ACH-000101", - "ACH-000226", - "ACH-000233", - "ACH-000338", - "ACH-000664", - "ACH-000773", - "ACH-001111", - "ACH-001119", - "ACH-001737" - ], - "hoverinfo": "text", - "marker": { - "color": "#FE00CE", - "size": 7 - }, - "mode": "markers", - "name": "Mature T and NK Neoplasms", - "text": [ - "Mature T and NK Neoplasms | ACH-000053", - "Mature T and NK Neoplasms | ACH-000101", - "Mature T and NK Neoplasms | ACH-000226", - "Mature T and NK Neoplasms | ACH-000233", - "Mature T and NK Neoplasms | ACH-000338", - "Mature T and NK Neoplasms | ACH-000664", - "Mature T and NK Neoplasms | ACH-000773", - "Mature T and NK Neoplasms | ACH-001111", - "Mature T and NK Neoplasms | ACH-001119", - "Mature T and NK Neoplasms | ACH-001737" - ], - "type": "scattergl", - "x": { - "bdata": "kZnlP2+nqEBMknFAuvBdQGr/jj9RsuJAmrENQOb/+z++WrK/hmjrPw==", - "dtype": "f4" - }, - "y": { - "bdata": "tmFQwKdKgMAN1j3AB/4hwLk+Or8kLIHAvropwMsj378zGhe/0hKxvg==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000054" - ], - "hoverinfo": "text", - "marker": { - "color": "#0DF9FF", - "size": 7 - }, - "mode": "markers", - "name": "Fibrosarcoma", - "text": [ - "Fibrosarcoma | ACH-000054" - ], - "type": "scattergl", - "x": { - "bdata": "PNxYPw==", - "dtype": "f4" - }, - "y": { - "bdata": "DSHFPw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000055", - "ACH-000095", - "ACH-000160", - "ACH-000211", - "ACH-000776", - "ACH-001020", - "ACH-001028", - "ACH-001031", - "ACH-001033", - "ACH-001053", - "ACH-001054", - "ACH-001232", - "ACH-001289", - "ACH-001670", - "ACH-001711" - ], - "hoverinfo": "text", - "marker": { - "color": "#F6F926", - "size": 7 - }, - "mode": "markers", - "name": "Embryonal Tumor", - "text": [ - "Embryonal Tumor | ACH-000055", - "Embryonal Tumor | ACH-000095", - "Embryonal Tumor | ACH-000160", - "Embryonal Tumor | ACH-000211", - "Embryonal Tumor | ACH-000776", - "Embryonal Tumor | ACH-001020", - "Embryonal Tumor | ACH-001028", - "Embryonal Tumor | ACH-001031", - "Embryonal Tumor | ACH-001033", - "Embryonal Tumor | ACH-001053", - "Embryonal Tumor | ACH-001054", - "Embryonal Tumor | ACH-001232", - "Embryonal Tumor | ACH-001289", - "Embryonal Tumor | ACH-001670", - "Embryonal Tumor | ACH-001711" - ], - "type": "scattergl", - "x": { - "bdata": "ibw6QBroEkA4irRAfyyLPZb46D+ejrw/0uaPQJ17kEBURLY/J0DBP77nl0CjfDe9KxjUP/8xOkCFPRVA", - "dtype": "f4" - }, - "y": { - "bdata": "0WiPvyMvKb8AIUM/ENcrQI1QfT/FTaI/7yUfv9/oYz/PRRE/uqc+vmJit79VYYVAs9OKviGNGT+/kg0/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000070", - "ACH-000151", - "ACH-000782", - "ACH-000922", - "ACH-000938", - "ACH-000960", - "ACH-001484", - "ACH-001520", - "ACH-001669", - "ACH-001735", - "ACH-001736", - "ACH-001993", - "ACH-002059" - ], - "hoverinfo": "text", - "marker": { - "color": "#FF9616", - "size": 7 - }, - "mode": "markers", - "name": "B-Lymphoblastic Leukemia/Lymphoma", - "text": [ - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000070", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000151", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000782", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000922", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000938", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000960", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001484", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001520", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001669", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001735", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001736", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001993", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-002059" - ], - "type": "scattergl", - "x": { - "bdata": "eseKQDzO9j+rn3lALfbDQH0Ko0A+wYpAkSFnQMFolkChZ7tA2M9NQDSNy0Cd//w/hnqAQA==", - "dtype": "f4" - }, - "y": { - "bdata": "so+AwHF9b8AWLHnATSSYwLuiocAAvYrA1lhHwKBpWsBjKIvANv+JwFY3nsDjc0fAuUFAwA==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000074", - "ACH-000076", - "ACH-000198", - "ACH-000295", - "ACH-000326", - "ACH-000551", - "ACH-000604", - "ACH-000920", - "ACH-000983", - "ACH-002061" - ], - "hoverinfo": "text", - "marker": { - "color": "#479B55", - "size": 7 - }, - "mode": "markers", - "name": "Myeloproliferative Neoplasms", - "text": [ - "Myeloproliferative Neoplasms | ACH-000074", - "Myeloproliferative Neoplasms | ACH-000076", - "Myeloproliferative Neoplasms | ACH-000198", - "Myeloproliferative Neoplasms | ACH-000295", - "Myeloproliferative Neoplasms | ACH-000326", - "Myeloproliferative Neoplasms | ACH-000551", - "Myeloproliferative Neoplasms | ACH-000604", - "Myeloproliferative Neoplasms | ACH-000920", - "Myeloproliferative Neoplasms | ACH-000983", - "Myeloproliferative Neoplasms | ACH-002061" - ], - "type": "scattergl", - "x": { - "bdata": "y4VSQKHkfkCcTfFACYRtP2RbjUA2u25AEyctQKPzlD9a4qlAwRBtQA==", - "dtype": "f4" - }, - "y": { - "bdata": "2f9GwOTuL8AlO5zAdLUgwKg8XMC82UjAr2sKwEFHmL/URoXAujoxwA==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000077", - "ACH-000583", - "ACH-001197", - "ACH-001642" - ], - "hoverinfo": "text", - "marker": { - "color": "#EEA6FB", - "size": 7 - }, - "mode": "markers", - "name": "Non-Hodgkin Lymphoma", - "text": [ - "Non-Hodgkin Lymphoma | ACH-000077", - "Non-Hodgkin Lymphoma | ACH-000583", - "Non-Hodgkin Lymphoma | ACH-001197", - "Non-Hodgkin Lymphoma | ACH-001642" - ], - "type": "scattergl", - "x": { - "bdata": "RAV+QLuy8sBfUS1AmUrJPw==", - "dtype": "f4" - }, - "y": { - "bdata": "nuzZv5vMq7/8YULAFh0GwA==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000078", - "ACH-000099", - "ACH-000120", - "ACH-000149", - "ACH-000203", - "ACH-000227", - "ACH-000259", - "ACH-000260", - "ACH-000310", - "ACH-000312", - "ACH-000341", - "ACH-000366", - "ACH-000804", - "ACH-001188", - "ACH-001300", - "ACH-001301", - "ACH-001302", - "ACH-001303", - "ACH-001338", - "ACH-001344", - "ACH-001354", - "ACH-001366", - "ACH-001367", - "ACH-001481", - "ACH-001548", - "ACH-001603", - "ACH-001674", - "ACH-002080", - "ACH-002083", - "ACH-002261", - "ACH-002278", - "ACH-002280", - "ACH-002282", - "ACH-002283", - "ACH-002284", - "ACH-002285", - "ACH-002922" - ], - "hoverinfo": "text", - "marker": { - "color": "#DC587D", - "size": 7 - }, - "mode": "markers", - "name": "Neuroblastoma", - "text": [ - "Neuroblastoma | ACH-000078", - "Neuroblastoma | ACH-000099", - "Neuroblastoma | ACH-000120", - "Neuroblastoma | ACH-000149", - "Neuroblastoma | ACH-000203", - "Neuroblastoma | ACH-000227", - "Neuroblastoma | ACH-000259", - "Neuroblastoma | ACH-000260", - "Neuroblastoma | ACH-000310", - "Neuroblastoma | ACH-000312", - "Neuroblastoma | ACH-000341", - "Neuroblastoma | ACH-000366", - "Neuroblastoma | ACH-000804", - "Neuroblastoma | ACH-001188", - "Neuroblastoma | ACH-001300", - "Neuroblastoma | ACH-001301", - "Neuroblastoma | ACH-001302", - "Neuroblastoma | ACH-001303", - "Neuroblastoma | ACH-001338", - "Neuroblastoma | ACH-001344", - "Neuroblastoma | ACH-001354", - "Neuroblastoma | ACH-001366", - "Neuroblastoma | ACH-001367", - "Neuroblastoma | ACH-001481", - "Neuroblastoma | ACH-001548", - "Neuroblastoma | ACH-001603", - "Neuroblastoma | ACH-001674", - "Neuroblastoma | ACH-002080", - "Neuroblastoma | ACH-002083", - "Neuroblastoma | ACH-002261", - "Neuroblastoma | ACH-002278", - "Neuroblastoma | ACH-002280", - "Neuroblastoma | ACH-002282", - "Neuroblastoma | ACH-002283", - "Neuroblastoma | ACH-002284", - "Neuroblastoma | ACH-002285", - "Neuroblastoma | ACH-002922" - ], - "type": "scattergl", - "x": { - "bdata": "UFyKP4JEekBzgac/o8FAQPj7Kb77VQzAUhuzQJnPHUC9svW/1R/IPx4gbTs0E/o/gnmLQIEiL0B3vHdAjkHHvjGtbj9/mB0+5haEQLW5BD+KJ8U/APQwQG/1VECjwjc9n6V4PiH+JEAEaUpAl8jywFYHpUC0cpxAUqGKQOQFiECHcV1A/XIjQPTd8sAnQQlBSiFVQA==", - "dtype": "f4" - }, - "y": { - "bdata": "hVWhvtdvWr8hXNE/WGtiPyQrFT8T/Ri/tm2fv7sP3z9pcyc+2AmPv0ZyfT/xAyi+6YkPv5cqiT/9Vnq+VaizP1X1Xr6pb0c+yob4v2iexj8lOA29fNvCvouDfL9Saw1AFR4pP8loBD4gwNK/UGirv8a0F0D0g5y/rK+5vv39Zb9aLn++Ldu1P5LOqr/ph/M+WT6Wvw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000082", - "ACH-000359", - "ACH-000364", - "ACH-000410", - "ACH-000748", - "ACH-001001", - "ACH-001526", - "ACH-001715", - "ACH-001814", - "ACH-002067", - "ACH-002069", - "ACH-002471", - "ACH-002834" - ], - "hoverinfo": "text", - "marker": { - "color": "#D626FF", - "size": 7 - }, - "mode": "markers", - "name": "Osteosarcoma", - "text": [ - "Osteosarcoma | ACH-000082", - "Osteosarcoma | ACH-000359", - "Osteosarcoma | ACH-000364", - "Osteosarcoma | ACH-000410", - "Osteosarcoma | ACH-000748", - "Osteosarcoma | ACH-001001", - "Osteosarcoma | ACH-001526", - "Osteosarcoma | ACH-001715", - "Osteosarcoma | ACH-001814", - "Osteosarcoma | ACH-002067", - "Osteosarcoma | ACH-002069", - "Osteosarcoma | ACH-002471", - "Osteosarcoma | ACH-002834" - ], - "type": "scattergl", - "x": { - "bdata": "EnVawMOUMcDiTxpADp+MP5wg7z+jKbNAbqTPvwOL5r9wLgvALquoP1StSr6meHK+RtzywA==", - "dtype": "f4" - }, - "y": { - "bdata": "QxswQIzgH0DaOTlAKN31P82cl0AWuxu/S8kEQNwSFEDOGFtA84k5P90HaEDuvf8/dQ+qvw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000086", - "ACH-000092", - "ACH-000153", - "ACH-000319", - "ACH-000331", - "ACH-000335", - "ACH-000367", - "ACH-000569", - "ACH-000645", - "ACH-000648", - "ACH-001547", - "ACH-001555", - "ACH-001556", - "ACH-001557", - "ACH-001558", - "ACH-001559", - "ACH-001560", - "ACH-001562", - "ACH-001977", - "ACH-001992", - "ACH-002033" - ], - "hoverinfo": "text", - "marker": { - "color": "#6E899C", - "size": 7 - }, - "mode": "markers", - "name": "Pleural Mesothelioma", - "text": [ - "Pleural Mesothelioma | ACH-000086", - "Pleural Mesothelioma | ACH-000092", - "Pleural Mesothelioma | ACH-000153", - "Pleural Mesothelioma | ACH-000319", - "Pleural Mesothelioma | ACH-000331", - "Pleural Mesothelioma | ACH-000335", - "Pleural Mesothelioma | ACH-000367", - "Pleural Mesothelioma | ACH-000569", - "Pleural Mesothelioma | ACH-000645", - "Pleural Mesothelioma | ACH-000648", - "Pleural Mesothelioma | ACH-001547", - "Pleural Mesothelioma | ACH-001555", - "Pleural Mesothelioma | ACH-001556", - "Pleural Mesothelioma | ACH-001557", - "Pleural Mesothelioma | ACH-001558", - "Pleural Mesothelioma | ACH-001559", - "Pleural Mesothelioma | ACH-001560", - "Pleural Mesothelioma | ACH-001562", - "Pleural Mesothelioma | ACH-001977", - "Pleural Mesothelioma | ACH-001992", - "Pleural Mesothelioma | ACH-002033" - ], - "type": "scattergl", - "x": { - "bdata": "ImwZQIuoAcBTe7K/QTeqv+c9OD+dNw5AOMfywPV0TD91Ce2/yq6OP5m5Kr8eA6U97IXOP8afVD+J2fLAgsLywHra8sBIxfLAF79+QAAuQkAv6zbA", - "dtype": "f4" - }, - "y": { - "bdata": "5XcEQIBPJEDI01ZAspNiQOJKGkDeEPs+VP+rv165bz8TVD9AFGYNQG1BfkDfRzVA49qIP+baNEDeyqq/H46qv3ilqr8dnaq/dlcHv35Zej+R9oc/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000090", - "ACH-000115", - "ACH-000956", - "ACH-000977", - "ACH-000979", - "ACH-001422", - "ACH-001627", - "ACH-001648", - "ACH-001649" - ], - "hoverinfo": "text", - "marker": { - "color": "#00B5F7", - "size": 7 - }, - "mode": "markers", - "name": "Prostate Adenocarcinoma", - "text": [ - "Prostate Adenocarcinoma | ACH-000090", - "Prostate Adenocarcinoma | ACH-000115", - "Prostate Adenocarcinoma | ACH-000956", - "Prostate Adenocarcinoma | ACH-000977", - "Prostate Adenocarcinoma | ACH-000979", - "Prostate Adenocarcinoma | ACH-001422", - "Prostate Adenocarcinoma | ACH-001627", - "Prostate Adenocarcinoma | ACH-001648", - "Prostate Adenocarcinoma | ACH-001649" - ], - "type": "scattergl", - "x": { - "bdata": "Qx5RPLnXUsAjDwBAGFSZQBp4mz+jInPAhLrywHHG8sC75fLA", - "dtype": "f4" - }, - "y": { - "bdata": "CzfJP0aODz4te76/ZnG/vxHlbj8DVC+/hC6rv6wSq7/FGau/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000096", - "ACH-000172", - "ACH-000533", - "ACH-000597", - "ACH-001099", - "ACH-001128", - "ACH-001211", - "ACH-001212", - "ACH-001532" - ], - "hoverinfo": "text", - "marker": { - "color": "#B68E00", - "size": 7 - }, - "mode": "markers", - "name": "Rhabdoid Cancer", - "text": [ - "Rhabdoid Cancer | ACH-000096", - "Rhabdoid Cancer | ACH-000172", - "Rhabdoid Cancer | ACH-000533", - "Rhabdoid Cancer | ACH-000597", - "Rhabdoid Cancer | ACH-001099", - "Rhabdoid Cancer | ACH-001128", - "Rhabdoid Cancer | ACH-001211", - "Rhabdoid Cancer | ACH-001212", - "Rhabdoid Cancer | ACH-001532" - ], - "type": "scattergl", - "x": { - "bdata": "KC8dQOZq5T92lqdAPdU+QBx0s0AjmglAIPAaQM3byz+GFZ9A", - "dtype": "f4" - }, - "y": { - "bdata": 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"qXQqQFUJJkC3nuo/NOU5QIYyA7/KMpdAOpZ7QNwtOECMSsU/giAaQOOIFECPO25A37yjQA==", - "dtype": "f4" - }, - "y": { - "bdata": "bPFCvwcwqT1p1Gs/EpI+vhoIfkDJjea+1rBhv2kaMT9o7AY++0vrvp/xsz8YnZS/nOiovg==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000108", - "ACH-000685" - ], - "hoverinfo": "text", - "marker": { - "color": "#FF0092", - "size": 7 - }, - "mode": "markers", - "name": "Adenosquamous Carcinoma of the Pancreas", - "text": [ - "Adenosquamous Carcinoma of the Pancreas | ACH-000108", - "Adenosquamous Carcinoma of the Pancreas | ACH-000685" - ], - "type": "scattergl", - "x": { - "bdata": "lUUdwEgzN0A=", - "dtype": "f4" - }, - "y": { - "bdata": "nnF5P1tXFUA=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000133", - "ACH-001310", - "ACH-001453", - "ACH-002210", - "ACH-002247", - "ACH-002462", - "ACH-002463", - "ACH-002464", - "ACH-002465", - "ACH-002467" - ], - "hoverinfo": "text", - "marker": { - "color": "#22FFA7", - "size": 7 - }, - "mode": "markers", - "name": "Non-Cancerous", - "text": [ - "Non-Cancerous | ACH-000133", - "Non-Cancerous | ACH-001310", - "Non-Cancerous | ACH-001453", - "Non-Cancerous | ACH-002210", - "Non-Cancerous | ACH-002247", - "Non-Cancerous | ACH-002462", - "Non-Cancerous | ACH-002463", - "Non-Cancerous | ACH-002464", - "Non-Cancerous | ACH-002465", - "Non-Cancerous | ACH-002467" - ], - "type": "scattergl", - "x": { - "bdata": "xpyUPBm98sAHz1w/koekQLDJ8sDb3vLA+NnywMPV8sCF1PLAB9/ywA==", - "dtype": "f4" - }, - "y": { - "bdata": "DslqQBMhq7+sQA1A/LdgwGbCqr8mIqu/sUyrv90brL+yi6u/ylOrvw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000141", - "ACH-001607", - "ACH-001619", - "ACH-001850", - "ACH-001861", - "ACH-001961" - ], - "hoverinfo": "text", - "marker": { - "color": "#E3EE9E", - "size": 7 - }, - "mode": "markers", - "name": "Intracholecystic Papillary Neoplasm", - "text": [ - "Intracholecystic Papillary Neoplasm | ACH-000141", - "Intracholecystic Papillary Neoplasm | ACH-001607", - "Intracholecystic Papillary Neoplasm | ACH-001619", - "Intracholecystic Papillary Neoplasm | ACH-001850", - "Intracholecystic Papillary Neoplasm | ACH-001861", - "Intracholecystic Papillary Neoplasm | ACH-001961" - ], - "type": "scattergl", - "x": { - "bdata": "xNbywAldL0DOXdq/eU8xQJ6x8sBfE/s/", - "dtype": "f4" - }, - "y": { - "bdata": "kQmrvzzujL+Vag1AmPI2vuvxqr8/nh6/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000145", - "ACH-000505", - "ACH-002785" - ], - "hoverinfo": "text", - "marker": { - "color": "#86CE00", - "size": 7 - }, - "mode": "markers", - "name": "Leiomyosarcoma", - "text": [ - "Leiomyosarcoma | ACH-000145", - "Leiomyosarcoma | ACH-000505", - "Leiomyosarcoma | ACH-002785" - ], - "type": "scattergl", - "x": { - "bdata": "AiMRwNwxQ8C4Iey/", - "dtype": "f4" - }, - "y": { - "bdata": "GXs6QN11QkAodWw/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000159", - "ACH-000189", - "ACH-000234", - "ACH-000246", - "ACH-000250", - "ACH-000262", - "ACH-000272", - "ACH-000313", - "ACH-000317", - "ACH-000375", - "ACH-000385", - "ACH-000411", - "ACH-000433", - "ACH-000459", - "ACH-000484", - "ACH-000495", - "ACH-000649", - "ACH-000684", - "ACH-000709", - "ACH-000792", - "ACH-000907", - "ACH-001163", - "ACH-001194", - "ACH-001398", - "ACH-001687", - "ACH-001688", - "ACH-002150", - "ACH-002189", - "ACH-002533" - ], - "hoverinfo": "text", - "marker": { - "color": "#BC7196", - "size": 7 - }, - "mode": "markers", - "name": "Renal Cell Carcinoma", - "text": [ - "Renal Cell Carcinoma | ACH-000159", - "Renal Cell Carcinoma | ACH-000189", - "Renal Cell Carcinoma | ACH-000234", - "Renal Cell Carcinoma | ACH-000246", - "Renal Cell Carcinoma | ACH-000250", - "Renal Cell Carcinoma | ACH-000262", - "Renal Cell Carcinoma | ACH-000272", - "Renal Cell Carcinoma | ACH-000313", - "Renal Cell Carcinoma | ACH-000317", - "Renal Cell Carcinoma | ACH-000375", - "Renal Cell Carcinoma | ACH-000385", - "Renal Cell Carcinoma | ACH-000411", - "Renal Cell Carcinoma | ACH-000433", - "Renal Cell Carcinoma | ACH-000459", - "Renal Cell Carcinoma | ACH-000484", - "Renal Cell Carcinoma | ACH-000495", - "Renal Cell Carcinoma | ACH-000649", - "Renal Cell Carcinoma | ACH-000684", - "Renal Cell Carcinoma | ACH-000709", - "Renal Cell Carcinoma | ACH-000792", - "Renal Cell Carcinoma | ACH-000907", - "Renal Cell Carcinoma | ACH-001163", - "Renal Cell Carcinoma | ACH-001194", - "Renal Cell Carcinoma | ACH-001398", - "Renal Cell Carcinoma | ACH-001687", - "Renal Cell Carcinoma | ACH-001688", - "Renal Cell Carcinoma | ACH-002150", - "Renal Cell Carcinoma | ACH-002189", - "Renal Cell Carcinoma | ACH-002533" - ], - "type": "scattergl", - "x": { - "bdata": "iFm1v3ff8sAKpB7Aq8DywNyv8sDQt/LAuc7ywHSHOcC5u/LA1OV1QGs+Sz4ieps/xIBtv98pvMDy3fLAQgjFv3ZD8T+uFQu/i+YkwNTE9T5Kv1XAiGOqPxC88sDIc1e+osTywHTC8sD2wfLAQBpXwKOMQkA=", - "dtype": "f4" - }, - "y": { - "bdata": "OxmZPwgTq7/qY0pAPJCrvwpCq78hFqu/W+mqv9ODC0AUj6u/bEubPN+NCkAVYhNAqhhKQEdNJj/ayaq/Ro4xQGIKEkDuC1NAoYcUQMJHj0BzcXFAY2Wuvzz4qr91Vm8/9E6rv7Owq79U8aq/EakbQH3cXb4=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000163", - "ACH-000181", - "ACH-000188", - "ACH-000207", - "ACH-000228", - "ACH-000238", - "ACH-000415", - "ACH-000472", - "ACH-000500", - "ACH-000503", - "ACH-000518", - "ACH-000546", - "ACH-000548", - "ACH-000549", - "ACH-000606", - "ACH-000618", - "ACH-000619", - "ACH-000630", - "ACH-000682", - "ACH-000732", - "ACH-000735", - "ACH-000740", - "ACH-000762", - "ACH-000771", - "ACH-000778", - "ACH-000794", - "ACH-000832", - "ACH-000836", - "ACH-000846", - "ACH-001228", - "ACH-001229", - "ACH-001331", - "ACH-001332", - "ACH-001346", - "ACH-001347", - "ACH-001385", - "ACH-001509", - "ACH-001510", - "ACH-001511", - "ACH-001542", - "ACH-001543", - "ACH-001625", - "ACH-001626", - "ACH-001641", - "ACH-001675", - "ACH-001690", - "ACH-001691", - "ACH-001692", - "ACH-001694", - "ACH-001695", - "ACH-001696", - "ACH-001698", - "ACH-001699", - "ACH-001701", - "ACH-002029", - "ACH-002030", - "ACH-002042", - "ACH-002043", - "ACH-002044", - "ACH-002045", - "ACH-002212", - "ACH-002249", - "ACH-002250", - "ACH-002251", - "ACH-002265", - "ACH-002294", - "ACH-002295", - "ACH-002296", - "ACH-002297", - "ACH-002298", - "ACH-002305" - ], - "hoverinfo": "text", - "marker": { - "color": "#7E7DCD", - "size": 7 - }, - "mode": "markers", - "name": "Head and Neck Squamous Cell Carcinoma", - "text": [ - "Head and Neck Squamous Cell Carcinoma | ACH-000163", - "Head and Neck Squamous Cell Carcinoma | ACH-000181", - "Head and Neck Squamous Cell Carcinoma | ACH-000188", - "Head and Neck Squamous Cell Carcinoma | ACH-000207", - "Head and Neck Squamous Cell Carcinoma | ACH-000228", - "Head and Neck Squamous Cell Carcinoma | ACH-000238", - "Head and Neck Squamous Cell Carcinoma | ACH-000415", - "Head and Neck Squamous Cell Carcinoma | ACH-000472", - "Head and Neck Squamous Cell Carcinoma | ACH-000500", - "Head and Neck Squamous Cell Carcinoma | ACH-000503", - "Head and Neck Squamous Cell Carcinoma | ACH-000518", - "Head and Neck Squamous Cell Carcinoma | ACH-000546", - "Head and Neck Squamous Cell Carcinoma | ACH-000548", - "Head and Neck Squamous Cell Carcinoma | ACH-000549", - "Head and Neck Squamous Cell Carcinoma | ACH-000606", - "Head and Neck Squamous Cell Carcinoma | ACH-000618", - "Head and Neck Squamous Cell Carcinoma | ACH-000619", - "Head and Neck Squamous Cell Carcinoma | ACH-000630", - "Head and Neck Squamous Cell Carcinoma | ACH-000682", - "Head and Neck Squamous Cell Carcinoma | ACH-000732", - "Head and Neck Squamous Cell Carcinoma | ACH-000735", - "Head and Neck Squamous Cell Carcinoma | ACH-000740", - "Head and Neck Squamous Cell Carcinoma | ACH-000762", - "Head and Neck Squamous Cell Carcinoma | ACH-000771", - "Head and Neck Squamous Cell Carcinoma | ACH-000778", - "Head and Neck Squamous Cell Carcinoma | ACH-000794", - "Head and Neck Squamous Cell Carcinoma | ACH-000832", - "Head and Neck Squamous Cell Carcinoma | ACH-000836", - "Head and Neck Squamous Cell Carcinoma | ACH-000846", - "Head and Neck Squamous Cell Carcinoma | ACH-001228", - "Head and Neck Squamous Cell Carcinoma | ACH-001229", - "Head and Neck Squamous Cell Carcinoma | ACH-001331", - "Head and Neck Squamous Cell Carcinoma | ACH-001332", - "Head and Neck Squamous Cell Carcinoma | ACH-001346", - "Head and Neck Squamous Cell Carcinoma | ACH-001347", - "Head and Neck Squamous Cell Carcinoma | ACH-001385", - "Head and Neck Squamous Cell Carcinoma | ACH-001509", - "Head and Neck Squamous Cell Carcinoma | ACH-001510", - "Head and Neck Squamous Cell Carcinoma | ACH-001511", - "Head and Neck Squamous Cell Carcinoma | ACH-001542", - "Head and Neck Squamous Cell Carcinoma | ACH-001543", - "Head and Neck Squamous Cell Carcinoma | ACH-001625", - "Head and Neck Squamous Cell Carcinoma | ACH-001626", - "Head and Neck Squamous Cell Carcinoma | ACH-001641", - "Head and Neck Squamous Cell Carcinoma | ACH-001675", - "Head and Neck Squamous Cell Carcinoma | ACH-001690", - "Head and Neck Squamous Cell Carcinoma | ACH-001691", - "Head and Neck Squamous Cell Carcinoma | ACH-001692", - "Head and Neck Squamous Cell Carcinoma | ACH-001694", - "Head and Neck Squamous Cell Carcinoma | ACH-001695", - "Head and Neck Squamous Cell Carcinoma | ACH-001696", - "Head and Neck Squamous Cell Carcinoma | ACH-001698", - "Head and Neck Squamous Cell Carcinoma | ACH-001699", - "Head and Neck Squamous Cell Carcinoma | ACH-001701", - "Head and Neck Squamous Cell Carcinoma | ACH-002029", - "Head and Neck Squamous Cell Carcinoma | ACH-002030", - "Head and Neck Squamous Cell Carcinoma | ACH-002042", - "Head and Neck Squamous Cell Carcinoma | ACH-002043", - "Head and Neck Squamous Cell Carcinoma | ACH-002044", - "Head and Neck Squamous Cell Carcinoma | ACH-002045", - "Head and Neck Squamous Cell Carcinoma | ACH-002212", - "Head and Neck Squamous Cell Carcinoma | ACH-002249", - "Head and Neck Squamous Cell Carcinoma | ACH-002250", - "Head and Neck Squamous Cell Carcinoma | ACH-002251", - "Head and Neck Squamous Cell Carcinoma | ACH-002265", - "Head and Neck Squamous Cell Carcinoma | ACH-002294", - "Head and Neck Squamous Cell Carcinoma | ACH-002295", - "Head and Neck Squamous Cell Carcinoma | ACH-002296", - "Head and Neck Squamous Cell Carcinoma | ACH-002297", - "Head and Neck Squamous Cell Carcinoma | ACH-002298", - "Head and Neck Squamous Cell Carcinoma | ACH-002305" - ], - "type": "scattergl", - "x": { - "bdata": "IlGvvfQ1rj/+Wb4/CczywC3o8sDUZmg/Fc/ywNEWkL8miAq/gLzywGasUEBEnixAWAGtv2w/8j+UJCZA63GiQIxzOEBWUhFAuCM8QB6qiD8oYVA/biaNP3cUQD8GvfLAjmXHv2QIBEATP6lAaVzUP4N3dEB7Kay/Ir0FQHDX8sBG1PLAd6DTP/Zj4T/pHsFAiDIYv4mo0T89dJi/E8WIQOim4D9Z8h7AReAgwDTR8sCmq8M/wLBMQP6TZL6D24ZA7bUoQNzz3T/Olt0/WO3fP1LDr0DlxilAERaaQFm9WkDcLt6/dAYmQAUmw0AugRdA0crywJVHQUAtz5Y/7nsMQKnM8sAlGvA/7RfwvQ99o0A2/UBAYQNrQOfe8sA=", - "dtype": "f4" - }, - "y": { - "bdata": "GJd0QLfCtD7qTL8/ACGrvy7Sqr9HojZAoHiqvwnABUAbFLA/7Pqqvy7S0T+fPd0+DkzhPynzJD8zb5c/TeGVvoNAjT+L2JRA36UuP5P0lT9lVuc/TBaAPxcmvj/iSqu/NnMBQOGDnj+4bZY/Dg9NP6JfTz6fpJQ/zLOUPr9zqr+8Kau//ckQQEI2sj9gq6O/3xUjQL5GOkB2HSNAZWhsP+oy6j8p8dc/j5yOP+oRq7+2LTNACjiIP5RGnUCCpl0/QSWjP4T1Pz8BSxBA5hEDQKQ+BL/aqEI/1JE6PyzLaD/65Pw/KT7qPeWiGMDxEb8+WAGrv8Kq2D+dLn49Ay4FQGeDq7/skk0/GjTzP7PQJz/S91k/0Gp5PXLQqr8=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000174", - "ACH-000191", - "ACH-001306", - "ACH-001307", - "ACH-001356", - "ACH-001443", - "ACH-002041" - ], - "hoverinfo": "text", - "marker": { - "color": "#FC6955", - "size": 7 - }, - "mode": "markers", - "name": "Anaplastic Thyroid Cancer", - "text": [ - "Anaplastic Thyroid Cancer | ACH-000174", - "Anaplastic Thyroid Cancer | ACH-000191", - "Anaplastic Thyroid Cancer | ACH-001306", - "Anaplastic Thyroid Cancer | ACH-001307", - "Anaplastic Thyroid Cancer | ACH-001356", - "Anaplastic Thyroid Cancer | ACH-001443", - "Anaplastic Thyroid Cancer | ACH-002041" - ], - "type": "scattergl", - "x": { - "bdata": "Jcs/P0u0kz+XX2K/r5sPwM9wZsACtIc9nYvUvg==", - "dtype": "f4" - }, - "y": { - "bdata": "HsMGQOEBA0BZpnZA/JHSP1cDWj8AVPA/VXRpQA==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000182", - "ACH-000377", - "ACH-001862", - "ACH-002023" - ], - "hoverinfo": "text", - "marker": { - "color": "#E48F72", - "size": 7 - }, - "mode": "markers", - "name": "Ampullary Carcinoma", - "text": [ - "Ampullary Carcinoma | ACH-000182", - "Ampullary Carcinoma | ACH-000377", - "Ampullary Carcinoma | ACH-001862", - "Ampullary Carcinoma | ACH-002023" - ], - "type": "scattergl", - "x": { - "bdata": "4szywHC08sArakG/uNjiPw==", - "dtype": "f4" - }, - "y": { - "bdata": "Ceuqv1E3q7+AyuM+Zu6Dvw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000187", - "ACH-000257", - "ACH-000290", - "ACH-000292", - "ACH-000355", - "ACH-000431", - "ACH-000514", - "ACH-000515", - "ACH-000525", - "ACH-000559", - "ACH-000639", - "ACH-000695", - "ACH-000698", - "ACH-000749", - "ACH-000767", - "ACH-000775", - "ACH-000790", - "ACH-000800", - "ACH-000866", - "ACH-000871", - "ACH-000890", - "ACH-000912", - "ACH-001386", - "ACH-001549", - "ACH-002051", - "ACH-002052", - "ACH-002077" - ], - "hoverinfo": "text", - "marker": { - "color": "#2E91E5", - "size": 7 - }, - "mode": "markers", - "name": "Lung Neuroendocrine Tumor", - "text": [ - "Lung Neuroendocrine Tumor | ACH-000187", - "Lung Neuroendocrine Tumor | ACH-000257", - "Lung Neuroendocrine Tumor | ACH-000290", - "Lung Neuroendocrine Tumor | ACH-000292", - "Lung Neuroendocrine Tumor | ACH-000355", - "Lung Neuroendocrine Tumor | ACH-000431", - "Lung Neuroendocrine Tumor | ACH-000514", - "Lung Neuroendocrine Tumor | ACH-000515", - "Lung Neuroendocrine Tumor | ACH-000525", - "Lung Neuroendocrine Tumor | ACH-000559", - "Lung Neuroendocrine Tumor | ACH-000639", - "Lung Neuroendocrine Tumor | ACH-000695", - "Lung Neuroendocrine Tumor | ACH-000698", - "Lung Neuroendocrine Tumor | ACH-000749", - "Lung Neuroendocrine Tumor | ACH-000767", - "Lung Neuroendocrine Tumor | ACH-000775", - "Lung Neuroendocrine Tumor | ACH-000790", - "Lung Neuroendocrine Tumor | ACH-000800", - "Lung Neuroendocrine Tumor | ACH-000866", - "Lung Neuroendocrine Tumor | ACH-000871", - "Lung Neuroendocrine Tumor | ACH-000890", - "Lung Neuroendocrine Tumor | ACH-000912", - "Lung Neuroendocrine Tumor | ACH-001386", - "Lung Neuroendocrine Tumor | ACH-001549", - "Lung Neuroendocrine Tumor | ACH-002051", - "Lung Neuroendocrine Tumor | ACH-002052", - "Lung Neuroendocrine Tumor | ACH-002077" - ], - "type": "scattergl", - "x": { - "bdata": "uHgBQAA+jr25G9s/tuWaQBpOk0BCgcM+JtRXv3mmDECGrrc/IOyMvxmujEDMhaO/eYg2QEhLLEDDtoS/S00RQOwqP0D1SdI/T2iUQGJriUCh/FK/rjcYQMKIzj6R3zE/vd0ewNk42L50XLe/", - "dtype": "f4" - }, - "y": { - "bdata": "2GMzwLV+lr8WegjA9hkIP+jXQb9Q0ia/0HCvvx2Utr8ybai/ljV2v/K0Q8CgKEm/OjIswHEVb77S1dm/n1qwvnGvzb+q0pc/qrHdvw+Bo7/PY0JASD81PwcNr7/nd6S/lxyhv3Xs0L/LuB2/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000192", - "ACH-000293", - "ACH-000302", - "ACH-000397", - "ACH-000407", - "ACH-000435", - "ACH-000831", - "ACH-000864", - "ACH-000879", - "ACH-000928", - "ACH-000941", - "ACH-000946", - "ACH-000961", - "ACH-000965", - "ACH-000972", - "ACH-000974", - "ACH-000978", - "ACH-000984", - "ACH-000988", - "ACH-000993", - "ACH-000994", - "ACH-000996", - "ACH-001495", - "ACH-001517", - "ACH-001518", - "ACH-002026", - "ACH-002027", - "ACH-002046" - ], - "hoverinfo": "text", - "marker": { - "color": "#E15F99", - "size": 7 - }, - "mode": "markers", - "name": "Endometrial Carcinoma", - "text": [ - "Endometrial Carcinoma | ACH-000192", - "Endometrial Carcinoma | ACH-000293", - "Endometrial Carcinoma | ACH-000302", - "Endometrial Carcinoma | ACH-000397", - "Endometrial Carcinoma | ACH-000407", - "Endometrial Carcinoma | ACH-000435", - "Endometrial Carcinoma | ACH-000831", - "Endometrial Carcinoma | ACH-000864", - "Endometrial Carcinoma | ACH-000879", - "Endometrial Carcinoma | ACH-000928", - "Endometrial Carcinoma | ACH-000941", - "Endometrial Carcinoma | ACH-000946", - "Endometrial Carcinoma | ACH-000961", - "Endometrial Carcinoma | ACH-000965", - "Endometrial Carcinoma | ACH-000972", - "Endometrial Carcinoma | ACH-000974", - "Endometrial Carcinoma | ACH-000978", - "Endometrial Carcinoma | ACH-000984", - "Endometrial Carcinoma | ACH-000988", - "Endometrial Carcinoma | ACH-000993", - "Endometrial Carcinoma | ACH-000994", - "Endometrial Carcinoma | ACH-000996", - "Endometrial Carcinoma | ACH-001495", - "Endometrial Carcinoma | ACH-001517", - "Endometrial Carcinoma | ACH-001518", - "Endometrial Carcinoma | ACH-002026", - "Endometrial Carcinoma | ACH-002027", - "Endometrial Carcinoma | ACH-002046" - ], - "type": "scattergl", - "x": { - "bdata": "ZTcuwCzRLsDBcVu8TuEAv6aAtT6YD3W/drbywG21EEDZ3V5AYZFaQApj+L+P3RtA+REyQJp7sUCL2PLA+pRWQPJwzT7YVuW/uXrFve9fMT6uyPLAnf2dviX/wr8mBHHAIuHywKrySUDSLbQ/gCDwvg==", - "dtype": "f4" - }, - "y": { - "bdata": 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ACH-001538", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001673", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001834", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001835", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001836", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001838", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001839", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001841", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001842", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001843", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001844", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001848", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001849", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001852", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001856", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001857", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001858", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001863", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001864", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001959", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001960", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001997", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-002647" - ], - "type": "scattergl", - "x": { - "bdata": "ZMDywAfM8sBKwvLADe+SvmLwqz4XkTI/RcdRPxyIZ0Dx4fLAmN7ywJ3W8sBY2PLABdTywD7H8sAkF9C+I9TywCbF8sC20PLA4dDywE4jjEBZWJc/X6zxP2OY5j/Lz/LAeBorP/twtEDSSwZADKvywBTK8j8=", - "dtype": "f4" - }, - "y": { - "bdata": "s1qrv2/Xqr+SB6u/GzU/P067pj/+rilAUp4iQGwmJcCdZKq/KLaqv6b7qr+V7aq/cwqrv08Aq79vQg5A4CurvzmHq7/Za6u/swerv9PDxz6JI+Y/7ATPPddm1z1Zuqq/leADvndMBb91KwRAjLWrv41Kxj8=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000217", - "ACH-000221", - "ACH-000316", - "ACH-000361", - "ACH-000393", - "ACH-000420", - "ACH-000422", - "ACH-000471", - "ACH-000475", - "ACH-000476", - "ACH-000478", - "ACH-000480", - "ACH-000483", - "ACH-000493", - "ACH-000537", - "ACH-000577", - "ACH-000620", - "ACH-000734", - "ACH-000848", - "ACH-001318", - "ACH-002523" - ], - "hoverinfo": "text", - "marker": { - "color": "#DA16FF", - "size": 7 - }, - "mode": "markers", - "name": "Hepatocellular Carcinoma", - "text": [ - "Hepatocellular Carcinoma | ACH-000217", - "Hepatocellular Carcinoma | ACH-000221", - "Hepatocellular Carcinoma | ACH-000316", - "Hepatocellular Carcinoma | ACH-000361", - "Hepatocellular Carcinoma | ACH-000393", - "Hepatocellular Carcinoma | ACH-000420", - "Hepatocellular Carcinoma | ACH-000422", - "Hepatocellular Carcinoma | ACH-000471", - "Hepatocellular Carcinoma | ACH-000475", - "Hepatocellular Carcinoma | ACH-000476", - "Hepatocellular Carcinoma | ACH-000478", - "Hepatocellular Carcinoma | ACH-000480", - "Hepatocellular Carcinoma | ACH-000483", - "Hepatocellular Carcinoma | ACH-000493", - "Hepatocellular Carcinoma | ACH-000537", - "Hepatocellular Carcinoma | ACH-000577", - "Hepatocellular Carcinoma | ACH-000620", - "Hepatocellular Carcinoma | ACH-000734", - "Hepatocellular Carcinoma | ACH-000848", - "Hepatocellular Carcinoma | ACH-001318", - "Hepatocellular Carcinoma | ACH-002523" - ], - "type": "scattergl", - "x": { - "bdata": "C8IYQLSbnEDLQwM/r8ouP+Q1TcCdpbq/DVD+P7pqHj4X2yxANUxjv0J6rb/+zlVAXTfFv25pzD3xjsU/7iBvwPY/4T8dmIlAexSEQA6oE0Bx5sM/", - "dtype": "f4" - }, - "y": { - "bdata": "+cqaPv8JDr9wwItAC26nP0F4U0AfMS9AdtCGQP6lSEDZxE0+olJoP7t6OkAF5ck/AaBSQDY4N0D/ygJAuZ4eQCMOyzviuRK/DDxpv71zDD/7PpdA", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000305", - "ACH-000318", - "ACH-000408", - "ACH-000452", - "ACH-000488", - "ACH-000544", - "ACH-000561", - "ACH-000605", - "ACH-000637", - "ACH-000647", - "ACH-000693", - "ACH-000694", - "ACH-000717", - "ACH-000777", - "ACH-000784", - "ACH-000809", - "ACH-000823", - "ACH-000824", - "ACH-000855", - "ACH-000865", - "ACH-000873", - "ACH-000917", - "ACH-002243", - "ACH-002263" - ], - "hoverinfo": "text", - "marker": { - "color": "#222A2A", - "size": 7 - }, - "mode": "markers", - "name": "Esophageal Squamous Cell Carcinoma", - "text": [ - "Esophageal Squamous Cell Carcinoma | ACH-000305", - "Esophageal Squamous Cell Carcinoma | ACH-000318", - "Esophageal Squamous Cell Carcinoma | ACH-000408", - "Esophageal Squamous Cell Carcinoma | ACH-000452", - "Esophageal Squamous Cell Carcinoma | ACH-000488", - "Esophageal Squamous Cell Carcinoma | ACH-000544", - "Esophageal Squamous Cell Carcinoma | ACH-000561", - "Esophageal Squamous Cell Carcinoma | ACH-000605", - "Esophageal Squamous Cell Carcinoma | ACH-000637", - "Esophageal Squamous Cell Carcinoma | ACH-000647", - "Esophageal Squamous Cell Carcinoma | ACH-000693", - "Esophageal Squamous Cell Carcinoma | ACH-000694", - "Esophageal Squamous Cell Carcinoma | ACH-000717", - "Esophageal Squamous Cell Carcinoma | ACH-000777", - "Esophageal Squamous Cell Carcinoma | ACH-000784", - "Esophageal Squamous Cell Carcinoma | ACH-000809", - "Esophageal Squamous Cell Carcinoma | ACH-000823", - "Esophageal Squamous Cell Carcinoma | ACH-000824", - "Esophageal Squamous Cell Carcinoma | ACH-000855", - "Esophageal Squamous Cell Carcinoma | ACH-000865", - "Esophageal Squamous Cell Carcinoma | ACH-000873", - "Esophageal Squamous Cell Carcinoma | ACH-000917", - "Esophageal Squamous Cell Carcinoma | ACH-002243", - "Esophageal Squamous Cell Carcinoma | ACH-002263" - ], - "type": "scattergl", - "x": { - "bdata": "ApApP+4tBEA2dR1A6dCDvErrtEDU7yxAeWvtP8TxlT+nhmM+eqbqviH4sEA8uShAkQIsPCHEF0ASU1pARmB7QEn/VkA62qs/VtxSQEpAPUA7GURAE9Y+QD/G9D8/4CJA", - "dtype": "f4" - }, - "y": { - "bdata": "mT2SPxgRJj+bFio/Yj31P5jeLb9vaaw/NxiGvbg1oD+0YQxAX34GP5Z9sz6CQk0/XYjcP+1QYj8JJBI/TxfQvqSHD70Yrak/KBlHP16K9T9/oBa/E4ghv5xF4j9DLd6+", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000456" - ], - "hoverinfo": "text", - "marker": { - "color": "#B68100", - "size": 7 - }, - "mode": "markers", - "name": "Poorly Differentiated Thyroid Cancer", - "text": [ - "Poorly Differentiated Thyroid Cancer | ACH-000456" - ], - "type": "scattergl", - "x": { - "bdata": "nIl3QA==", - "dtype": "f4" - }, - "y": { - "bdata": "2VjDPw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000487" - ], - "hoverinfo": "text", - "marker": { - "color": "#750D86", - "size": 7 - }, - "mode": "markers", - "name": "Myelodysplastic Syndromes", - "text": [ - "Myelodysplastic Syndromes | ACH-000487" - ], - "type": "scattergl", - "x": { - "bdata": "rGq5QA==", - "dtype": "f4" - }, - "y": { - "bdata": "BrWFwA==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000490", - "ACH-000556", - "ACH-001333", - "ACH-001334", - "ACH-001335", - "ACH-001336", - "ACH-001360", - "ACH-001402", - "ACH-001451", - "ACH-001515", - "ACH-001651", - "ACH-001652", - "ACH-002020" - ], - "hoverinfo": "text", - "marker": { - "color": "#EB663B", - "size": 7 - }, - "mode": "markers", - "name": "Cervical Squamous Cell Carcinoma", - "text": [ - "Cervical Squamous Cell Carcinoma | ACH-000490", - "Cervical Squamous Cell Carcinoma | ACH-000556", - "Cervical Squamous Cell Carcinoma | ACH-001333", - "Cervical Squamous Cell Carcinoma | ACH-001334", - "Cervical Squamous Cell Carcinoma | ACH-001335", - "Cervical Squamous Cell Carcinoma | ACH-001336", - "Cervical Squamous Cell Carcinoma | ACH-001360", - "Cervical Squamous Cell Carcinoma | ACH-001402", - "Cervical Squamous Cell Carcinoma | ACH-001451", - "Cervical Squamous Cell Carcinoma | ACH-001515", - "Cervical Squamous Cell Carcinoma | ACH-001651", - "Cervical Squamous Cell Carcinoma | ACH-001652", - "Cervical Squamous Cell Carcinoma | ACH-002020" - ], - "type": "scattergl", - "x": { - "bdata": "B5f2P2pOGT+EsDxATgaiQCSpDEBchKc/GaKtwDv4jkC20fLAii1XPgVSicCURY4/l5ESvg==", - "dtype": "f4" - }, - "y": { - "bdata": "/tQJQBUDUr9ZPTA/43edv3antj7vgIU/8cQjPZvjnb+gFqu/qgDYvrDJEr9TNcI/Ay7KPQ==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000516" - ], - "hoverinfo": "text", - "marker": { - "color": "#511CFB", - "size": 7 - }, - "mode": "markers", - "name": "Chondrosarcoma", - "text": [ - "Chondrosarcoma | ACH-000516" - ], - "type": "scattergl", - "x": { - "bdata": "y2Y7wA==", - "dtype": "f4" - }, - "y": { - "bdata": "Ouh3QA==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000624", - "ACH-000725", - "ACH-000859" - ], - "hoverinfo": "text", - "marker": { - "color": "#00A08B", - "size": 7 - }, - "mode": "markers", - "name": "Breast Ductal Carcinoma In Situ", - "text": [ - "Breast Ductal Carcinoma In Situ | ACH-000624", - "Breast Ductal Carcinoma In Situ | ACH-000725", - "Breast Ductal Carcinoma In Situ | ACH-000859" - ], - "type": "scattergl", - "x": { - "bdata": "nx+eP9yqMMCoX4W+", - "dtype": "f4" - }, - "y": { - "bdata": "aReMv1W6fr808+U9", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000671", - "ACH-000739" - ], - "hoverinfo": "text", - "marker": { - "color": "#FB00D1", - "size": 7 - }, - "mode": "markers", - "name": "Hepatoblastoma", - "text": [ - "Hepatoblastoma | ACH-000671", - "Hepatoblastoma | ACH-000739" - ], - "type": "scattergl", - "x": { - "bdata": "li6PQKDngz8=", - "dtype": "f4" - }, - "y": { - "bdata": "UBloPzV9XL0=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000702", - "ACH-000754", - "ACH-001685" - ], - "hoverinfo": "text", - "marker": { - "color": "#FC0080", - "size": 7 - }, - "mode": "markers", - "name": "Hodgkin Lymphoma", - "text": [ - "Hodgkin Lymphoma | ACH-000702", - "Hodgkin Lymphoma | ACH-000754", - "Hodgkin Lymphoma | ACH-001685" - ], - "type": "scattergl", - "x": { - "bdata": "2a2yPvcujD+LipC/", - "dtype": "f4" - }, - "y": { - "bdata": "Icz9v9uCN8A6VBbA", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000716", - "ACH-000903", - "ACH-001528" - ], - "hoverinfo": "text", - "marker": { - "color": "#B2828D", - "size": 7 - }, - "mode": "markers", - "name": "Well-Differentiated Thyroid Cancer", - "text": [ - 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ACH-001279", - "Ovarian Epithelial Tumor | ACH-001340", - "Ovarian Epithelial Tumor | ACH-001370", - "Ovarian Epithelial Tumor | ACH-001403", - "Ovarian Epithelial Tumor | ACH-001418", - "Ovarian Epithelial Tumor | ACH-001628", - "Ovarian Epithelial Tumor | ACH-001630", - "Ovarian Epithelial Tumor | ACH-001632", - "Ovarian Epithelial Tumor | ACH-001719", - "Ovarian Epithelial Tumor | ACH-001991", - "Ovarian Epithelial Tumor | ACH-002140", - "Ovarian Epithelial Tumor | ACH-002181", - "Ovarian Epithelial Tumor | ACH-002183", - "Ovarian Epithelial Tumor | ACH-002486", - "Ovarian Epithelial Tumor | ACH-002524" - ], - "type": "scattergl", - "x": { - "bdata": "g5SPPYArWj+gudY/1jelvT6A2T5ba8Q/2qRVPgnTEr+HAzzAalU5wGyEEz/R0Yw+6zkAv+1vGj/EPrw/QxlwP1iZMz2PjDXAP2A3PxdHM8DIkUo/hs5AwHBaOL8r4izAVf4qPqKV4r+Xipc/Sg0wv3n3Lz+lS5M+iz2lvQuhBr6zHIi/91neP7B+uz/GJCk/oh8QQJe1eD/PDjc/IGI3wI5uNcBQeHM/2u+SPkZeL8Dzarg/0r8ywGNxNcDxtDrAc1gIP1JBNcAdDC/Amf03wHZGOMCuGt4/gakzwKsnNMDqFzLAoaSWP4Dm+j4=", - "dtype": "f4" - 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"Acute Myeloid Leukemia | ACH-000005", - "Acute Myeloid Leukemia | ACH-000045", - "Acute Myeloid Leukemia | ACH-000113", - "Acute Myeloid Leukemia | ACH-000146", - "Acute Myeloid Leukemia | ACH-000168", - "Acute Myeloid Leukemia | ACH-000190", - "Acute Myeloid Leukemia | ACH-000195", - "Acute Myeloid Leukemia | ACH-000263", - "Acute Myeloid Leukemia | ACH-000294", - "Acute Myeloid Leukemia | ACH-000336", - "Acute Myeloid Leukemia | ACH-000362", - "Acute Myeloid Leukemia | ACH-000387", - "Acute Myeloid Leukemia | ACH-000406", - "Acute Myeloid Leukemia | ACH-000498", - "Acute Myeloid Leukemia | ACH-000557", - "Acute Myeloid Leukemia | ACH-000602", - "Acute Myeloid Leukemia | ACH-000770", - "Acute Myeloid Leukemia | ACH-001036", - "Acute Myeloid Leukemia | ACH-001129", - "Acute Myeloid Leukemia | ACH-001574", - "Acute Myeloid Leukemia | ACH-001577", - "Acute Myeloid Leukemia | ACH-001613", - "Acute Myeloid Leukemia | ACH-001618", - "Acute Myeloid Leukemia | ACH-001647", - "Acute Myeloid Leukemia | ACH-001656" - ], - "type": "scattergl", - "x": { - "bdata": "+rUtP7CYfz5NbAJAteo1QOzUmz4B0Y0+5V1pP/Gv5D5HgAA9LuCBP36kG0DGEPo/fyxAP3IIBUABT0c+xvPLvrMdaT/0gtQ/sLqMP+z03j3cfgFAwiVjP4xd1T9NRpA/p8zGP66bvj8=", - "dtype": "f4" - }, - "y": { - "bdata": "fSqVvoqDgj4Dgpy/juD3v1/Pzj1XiaI+4ZrAvd0ht7yWIi0/lm4VvyHyxL+S/MC/SSGivmv4s7/snhI/AwyDP6EKuL4dhI6/Ze8Bv2mSGT877p+/GyJAvgI7YL/braG+3WqFv/SBYr8=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000007", - "ACH-000009", - "ACH-000202", - "ACH-000249", - "ACH-000252", - "ACH-000253", - "ACH-000286", - "ACH-000296", - "ACH-000350", - "ACH-000381", - "ACH-000403", - "ACH-000421", - "ACH-000467", - "ACH-000470", - "ACH-000489", - "ACH-000491", - "ACH-000501", - "ACH-000532", - "ACH-000552", - "ACH-000565", - "ACH-000651", - "ACH-000683", - "ACH-000722", - "ACH-000798", - "ACH-000820", - "ACH-000926", - "ACH-000935", - "ACH-000943", - "ACH-000950", - "ACH-000957", - "ACH-000958", - "ACH-000959", - "ACH-000963", - "ACH-000969", - "ACH-000970", - "ACH-000971", - "ACH-000985", - "ACH-000986", - "ACH-000991", - "ACH-000997", - "ACH-001039", - "ACH-001061", - "ACH-001081", - "ACH-001345", - "ACH-001399", - "ACH-001454", - "ACH-001458", - "ACH-001459", - "ACH-001460", - "ACH-001461", - "ACH-001786", - "ACH-002024", - "ACH-002025", - "ACH-002233", - "ACH-002535", - "ACH-002654", - "ACH-002659", - "ACH-002660", - "ACH-002662", - "ACH-002664", - "ACH-002669" - ], - "hoverinfo": "text", - "marker": { - "color": "#00CC96", - "size": 7 - }, - "mode": "markers", - "name": "Colorectal Adenocarcinoma", - "text": [ - "Colorectal Adenocarcinoma | ACH-000007", - "Colorectal Adenocarcinoma | ACH-000009", - "Colorectal Adenocarcinoma | ACH-000202", - "Colorectal Adenocarcinoma | ACH-000249", - "Colorectal Adenocarcinoma | ACH-000252", - "Colorectal Adenocarcinoma | ACH-000253", - "Colorectal Adenocarcinoma | ACH-000286", - "Colorectal Adenocarcinoma | ACH-000296", - "Colorectal Adenocarcinoma | ACH-000350", - "Colorectal Adenocarcinoma | ACH-000381", - "Colorectal Adenocarcinoma | ACH-000403", - "Colorectal Adenocarcinoma | ACH-000421", - "Colorectal Adenocarcinoma | ACH-000467", - "Colorectal Adenocarcinoma | ACH-000470", - "Colorectal Adenocarcinoma | ACH-000489", - "Colorectal Adenocarcinoma | ACH-000491", - "Colorectal Adenocarcinoma | ACH-000501", - "Colorectal Adenocarcinoma | ACH-000532", - "Colorectal Adenocarcinoma | ACH-000552", - "Colorectal Adenocarcinoma | ACH-000565", - "Colorectal Adenocarcinoma | ACH-000651", - "Colorectal Adenocarcinoma | ACH-000683", - "Colorectal Adenocarcinoma | ACH-000722", - "Colorectal Adenocarcinoma | ACH-000798", - "Colorectal Adenocarcinoma | ACH-000820", - "Colorectal Adenocarcinoma | ACH-000926", - "Colorectal Adenocarcinoma | ACH-000935", - "Colorectal Adenocarcinoma | ACH-000943", - "Colorectal Adenocarcinoma | ACH-000950", - "Colorectal Adenocarcinoma | ACH-000957", - "Colorectal Adenocarcinoma | ACH-000958", - "Colorectal Adenocarcinoma | ACH-000959", - "Colorectal Adenocarcinoma | ACH-000963", - "Colorectal Adenocarcinoma | ACH-000969", - "Colorectal Adenocarcinoma | ACH-000970", - "Colorectal Adenocarcinoma | ACH-000971", - "Colorectal Adenocarcinoma | ACH-000985", - "Colorectal Adenocarcinoma | ACH-000986", - "Colorectal Adenocarcinoma | ACH-000991", - "Colorectal Adenocarcinoma | ACH-000997", - "Colorectal Adenocarcinoma | ACH-001039", - "Colorectal Adenocarcinoma | ACH-001061", - "Colorectal Adenocarcinoma | ACH-001081", - "Colorectal Adenocarcinoma | ACH-001345", - "Colorectal Adenocarcinoma | ACH-001399", - "Colorectal Adenocarcinoma | ACH-001454", - "Colorectal Adenocarcinoma | ACH-001458", - "Colorectal Adenocarcinoma | ACH-001459", - "Colorectal Adenocarcinoma | ACH-001460", - "Colorectal Adenocarcinoma | ACH-001461", - "Colorectal Adenocarcinoma | ACH-001786", - "Colorectal Adenocarcinoma | ACH-002024", - "Colorectal Adenocarcinoma | ACH-002025", - "Colorectal Adenocarcinoma | ACH-002233", - "Colorectal Adenocarcinoma | ACH-002535", - "Colorectal Adenocarcinoma | ACH-002654", - "Colorectal Adenocarcinoma | ACH-002659", - "Colorectal Adenocarcinoma | ACH-002660", - "Colorectal Adenocarcinoma | ACH-002662", - "Colorectal Adenocarcinoma | ACH-002664", - "Colorectal Adenocarcinoma | ACH-002669" - ], - "type": "scattergl", - "x": { - "bdata": "PymxP45Yoz4BxwM/+201wGAqhj7ijvY+bYa7PnhHzT42tje/GhldP3uN1b6scWO+6iEywOTrkr7E8pc+ucK/PBi9LL71Hrs+WTVAP4WQBz+njIs/vx4uvmFcWj+Q5DXA6R1VPpc7NsCDETLA+EQowPHLnj/msLA/tzE3P5gddT9pEAS/fCk1wIRqBT8dDgA/u+EQP4yBMMA/+s8+T5+qPwnFgj9ZgN0/ISs4wNjFiz+9cdo+2CUGvwKQ8D6RKPs+fDmjP6ATPr81wMy8TwDPPuztMMDLObw+4EHJPoJMmb2/xKA/lYO0Psb+pD8FHWY/po1qPw==", - "dtype": "f4" - }, - "y": { - "bdata": 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Carcinoma", - "text": [ - "Bladder Urothelial Carcinoma | ACH-000011", - "Bladder Urothelial Carcinoma | ACH-000018", - "Bladder Urothelial Carcinoma | ACH-000026", - "Bladder Urothelial Carcinoma | ACH-000127", - "Bladder Urothelial Carcinoma | ACH-000142", - "Bladder Urothelial Carcinoma | ACH-000242", - "Bladder Urothelial Carcinoma | ACH-000396", - "Bladder Urothelial Carcinoma | ACH-000473", - "Bladder Urothelial Carcinoma | ACH-000486", - "Bladder Urothelial Carcinoma | ACH-000522", - "Bladder Urothelial Carcinoma | ACH-000545", - "Bladder Urothelial Carcinoma | ACH-000547", - "Bladder Urothelial Carcinoma | ACH-000593", - "Bladder Urothelial Carcinoma | ACH-000720", - "Bladder Urothelial Carcinoma | ACH-000724", - "Bladder Urothelial Carcinoma | ACH-000741", - "Bladder Urothelial Carcinoma | ACH-000753", - "Bladder Urothelial Carcinoma | ACH-000802", - "Bladder Urothelial Carcinoma | ACH-000834", - "Bladder Urothelial Carcinoma | ACH-000862", - "Bladder Urothelial Carcinoma | ACH-000896", - "Bladder Urothelial Carcinoma | ACH-000905", - "Bladder Urothelial Carcinoma | ACH-001183", - "Bladder Urothelial Carcinoma | ACH-001407", - "Bladder Urothelial Carcinoma | ACH-001409", - "Bladder Urothelial Carcinoma | ACH-001412", - "Bladder Urothelial Carcinoma | ACH-001413", - "Bladder Urothelial Carcinoma | ACH-001414", - "Bladder Urothelial Carcinoma | ACH-001415", - "Bladder Urothelial Carcinoma | ACH-001416" - ], - "type": "scattergl", - "x": { - "bdata": "a2SrPrsmbT434gA/Qaa4P1Xo/D4Llu8+CH/EvjAUNcCJSoQ/qZ0xwDF4NMARPDg/xVvqPuCvGz8/dia/19TnPp5AqT+pI4E/LESYP1jkNsB/cws/wgE8P8iyMsDVYDDAB1Y4wDj+OMB5/TTAWjQxwFA5PMCxYjjA", - "dtype": "f4" - }, - "y": { - "bdata": "b7urPpHvAT/Xy4k+JvUqv/EiTj4zFbQ+qLeXPzyRQL9XeIi+DA1jv4KJS79VsTk+JwS+PkJSXj7bj60/AvspPqV3Br+9eyS+icPhvtheKL/TSyw+/WKyO/p0Yb+cn4O/4Tkcv+jiCb/SOUG/1sd5v+zryr53hxu/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000012", - "ACH-000015", - "ACH-000021", - "ACH-000029", - "ACH-000030", - "ACH-000035", - "ACH-000143", - "ACH-000161", - "ACH-000176", - "ACH-000251", - "ACH-000261", - "ACH-000264", - "ACH-000311", - "ACH-000337", - "ACH-000339", - "ACH-000343", - "ACH-000378", - "ACH-000390", - "ACH-000395", - "ACH-000414", - "ACH-000416", - "ACH-000434", - "ACH-000438", - "ACH-000442", - "ACH-000444", - "ACH-000448", - "ACH-000454", - "ACH-000463", - "ACH-000481", - "ACH-000496", - "ACH-000510", - "ACH-000511", - "ACH-000521", - "ACH-000528", - "ACH-000562", - "ACH-000563", - "ACH-000585", - "ACH-000587", - "ACH-000589", - "ACH-000596", - "ACH-000627", - "ACH-000638", - "ACH-000662", - "ACH-000665", - "ACH-000666", - "ACH-000667", - "ACH-000672", - "ACH-000677", - "ACH-000681", - "ACH-000700", - "ACH-000706", - "ACH-000718", - "ACH-000747", - "ACH-000757", - "ACH-000766", - "ACH-000769", - "ACH-000774", - "ACH-000781", - "ACH-000785", - "ACH-000787", - "ACH-000791", - "ACH-000826", - "ACH-000837", - "ACH-000840", - "ACH-000841", - "ACH-000843", - "ACH-000845", - "ACH-000851", - "ACH-000853", - "ACH-000858", - "ACH-000860", - "ACH-000861", - "ACH-000867", - "ACH-000869", - "ACH-000872", - "ACH-000878", - "ACH-000886", - "ACH-000888", - "ACH-000894", - "ACH-000900", - "ACH-000901", - "ACH-000916", - "ACH-000921", - "ACH-000924", - "ACH-000929", - "ACH-000945", - "ACH-000975", - "ACH-000980", - "ACH-001075", - "ACH-001137", - "ACH-001233", - "ACH-002035", - "ACH-002156", - "ACH-002522", - "ACH-002526", - "ACH-002531", - "ACH-002650", - "ACH-003012" - ], - "hoverinfo": "text", - "marker": { - "color": "#FFA15A", - "size": 7 - }, - "mode": "markers", - "name": "Non-Small Cell Lung Cancer", - "text": [ - "Non-Small Cell Lung Cancer | ACH-000012", - "Non-Small Cell Lung Cancer | ACH-000015", - "Non-Small Cell Lung Cancer | ACH-000021", - "Non-Small Cell Lung Cancer | ACH-000029", - "Non-Small Cell Lung Cancer | ACH-000030", - "Non-Small Cell Lung Cancer | ACH-000035", - "Non-Small Cell Lung Cancer | ACH-000143", - "Non-Small Cell Lung Cancer | ACH-000161", - "Non-Small Cell Lung Cancer | ACH-000176", - "Non-Small Cell Lung Cancer | ACH-000251", - "Non-Small Cell Lung Cancer | ACH-000261", - "Non-Small Cell Lung Cancer | ACH-000264", - "Non-Small Cell Lung Cancer | ACH-000311", - "Non-Small Cell Lung Cancer | ACH-000337", - "Non-Small Cell Lung Cancer | ACH-000339", - "Non-Small Cell Lung Cancer | ACH-000343", - "Non-Small Cell Lung Cancer | ACH-000378", - "Non-Small Cell Lung Cancer | ACH-000390", - "Non-Small Cell Lung Cancer | ACH-000395", - "Non-Small Cell Lung Cancer | ACH-000414", - "Non-Small Cell Lung Cancer | ACH-000416", - "Non-Small Cell Lung Cancer | ACH-000434", - "Non-Small Cell Lung Cancer | ACH-000438", - "Non-Small Cell Lung Cancer | ACH-000442", - "Non-Small Cell Lung Cancer | ACH-000444", - "Non-Small Cell Lung Cancer | ACH-000448", - "Non-Small Cell Lung Cancer | ACH-000454", - "Non-Small Cell Lung Cancer | ACH-000463", - "Non-Small Cell Lung Cancer | ACH-000481", - "Non-Small Cell Lung Cancer | ACH-000496", - "Non-Small Cell Lung Cancer | ACH-000510", - "Non-Small Cell Lung Cancer | ACH-000511", - "Non-Small Cell Lung Cancer | ACH-000521", - "Non-Small Cell Lung Cancer | ACH-000528", - "Non-Small Cell Lung Cancer | ACH-000562", - "Non-Small Cell Lung Cancer | ACH-000563", - "Non-Small Cell Lung Cancer | ACH-000585", - "Non-Small Cell Lung Cancer | ACH-000587", - "Non-Small Cell Lung Cancer | ACH-000589", - "Non-Small Cell Lung Cancer | ACH-000596", - "Non-Small Cell Lung Cancer | ACH-000627", - "Non-Small Cell Lung Cancer | ACH-000638", - "Non-Small Cell Lung Cancer | ACH-000662", - "Non-Small Cell Lung Cancer | ACH-000665", - "Non-Small Cell Lung Cancer | ACH-000666", - "Non-Small Cell Lung Cancer | ACH-000667", - "Non-Small Cell Lung Cancer | ACH-000672", - "Non-Small Cell Lung Cancer | ACH-000677", - "Non-Small Cell Lung Cancer | ACH-000681", - "Non-Small Cell Lung Cancer | ACH-000700", - "Non-Small Cell Lung Cancer | ACH-000706", - "Non-Small Cell Lung Cancer | ACH-000718", - "Non-Small Cell Lung Cancer | ACH-000747", - "Non-Small Cell Lung Cancer | ACH-000757", - "Non-Small Cell Lung Cancer | ACH-000766", - "Non-Small Cell Lung Cancer | ACH-000769", - "Non-Small Cell Lung Cancer | ACH-000774", - "Non-Small Cell Lung Cancer | ACH-000781", - "Non-Small Cell Lung Cancer | ACH-000785", - "Non-Small Cell Lung Cancer | ACH-000787", - "Non-Small Cell Lung Cancer | ACH-000791", - "Non-Small Cell Lung Cancer | ACH-000826", - "Non-Small Cell Lung Cancer | ACH-000837", - "Non-Small Cell Lung Cancer | ACH-000840", - "Non-Small Cell Lung Cancer | ACH-000841", - "Non-Small Cell Lung Cancer | ACH-000843", - "Non-Small Cell Lung Cancer | ACH-000845", - "Non-Small Cell Lung Cancer | ACH-000851", - "Non-Small Cell Lung Cancer | ACH-000853", - "Non-Small Cell Lung Cancer | ACH-000858", - "Non-Small Cell Lung Cancer | ACH-000860", - "Non-Small Cell Lung Cancer | ACH-000861", - "Non-Small Cell Lung Cancer | ACH-000867", - "Non-Small Cell Lung Cancer | ACH-000869", - "Non-Small Cell Lung Cancer | ACH-000872", - "Non-Small Cell Lung Cancer | ACH-000878", - "Non-Small Cell Lung Cancer | ACH-000886", - "Non-Small Cell Lung Cancer | ACH-000888", - "Non-Small Cell Lung Cancer | ACH-000894", - "Non-Small Cell Lung Cancer | ACH-000900", - "Non-Small Cell Lung Cancer | ACH-000901", - "Non-Small Cell Lung Cancer | ACH-000916", - "Non-Small Cell Lung Cancer | ACH-000921", - "Non-Small Cell Lung Cancer | ACH-000924", - "Non-Small Cell Lung Cancer | ACH-000929", - "Non-Small Cell Lung Cancer | ACH-000945", - "Non-Small Cell Lung Cancer | ACH-000975", - "Non-Small Cell Lung Cancer | ACH-000980", - "Non-Small Cell Lung Cancer | ACH-001075", - "Non-Small Cell Lung Cancer | ACH-001137", - "Non-Small Cell Lung Cancer | ACH-001233", - "Non-Small Cell Lung Cancer | ACH-002035", - "Non-Small Cell Lung Cancer | ACH-002156", - "Non-Small Cell Lung Cancer | ACH-002522", - "Non-Small Cell Lung Cancer | ACH-002526", - "Non-Small Cell Lung Cancer | ACH-002531", - "Non-Small Cell Lung Cancer | ACH-002650", - "Non-Small Cell Lung Cancer | ACH-003012" - ], - "type": "scattergl", - "x": { - "bdata": "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", - "dtype": "f4" - }, - "y": { - "bdata": 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"ACH-000827", - "ACH-000881", - "ACH-000882", - "ACH-000884", - "ACH-000899", - "ACH-000915", - "ACH-000968", - "ACH-001041", - "ACH-001190", - "ACH-001239", - "ACH-001522", - "ACH-001563", - "ACH-001566", - "ACH-001567", - "ACH-001568", - "ACH-001570", - "ACH-001645", - "ACH-001970", - "ACH-001972", - "ACH-001973", - "ACH-001975", - "ACH-001982", - "ACH-001986", - "ACH-001990", - "ACH-002001", - "ACH-002002", - "ACH-002003", - "ACH-002004", - "ACH-002005", - "ACH-002084", - "ACH-002143", - "ACH-002458", - "ACH-002460", - "ACH-002461", - "ACH-002508", - "ACH-002510", - "ACH-002511", - "ACH-002512", - "ACH-002847", - "ACH-002928" - ], - "hoverinfo": "text", - "marker": { - "color": "#19D3F3", - "size": 7 - }, - "mode": "markers", - "name": "Melanoma", - "text": [ - "Melanoma | ACH-000014", - "Melanoma | ACH-000219", - "Melanoma | ACH-000274", - "Melanoma | ACH-000304", - "Melanoma | ACH-000322", - "Melanoma | ACH-000348", - "Melanoma | ACH-000401", - "Melanoma | ACH-000404", - "Melanoma | ACH-000425", - "Melanoma | ACH-000441", - "Melanoma | ACH-000450", - "Melanoma | ACH-000458", - "Melanoma | ACH-000477", - "Melanoma | ACH-000550", - "Melanoma | ACH-000579", - "Melanoma | ACH-000580", - "Melanoma | ACH-000614", - "Melanoma | ACH-000632", - "Melanoma | ACH-000661", - "Melanoma | ACH-000765", - "Melanoma | ACH-000788", - "Melanoma | ACH-000799", - "Melanoma | ACH-000801", - "Melanoma | ACH-000805", - "Melanoma | ACH-000810", - "Melanoma | ACH-000822", - "Melanoma | ACH-000827", - "Melanoma | ACH-000881", - "Melanoma | ACH-000882", - "Melanoma | ACH-000884", - "Melanoma | ACH-000899", - "Melanoma | ACH-000915", - "Melanoma | ACH-000968", - "Melanoma | ACH-001041", - "Melanoma | ACH-001190", - "Melanoma | ACH-001239", - "Melanoma | ACH-001522", - "Melanoma | ACH-001563", - "Melanoma | ACH-001566", - "Melanoma | ACH-001567", - "Melanoma | ACH-001568", - "Melanoma | ACH-001570", - "Melanoma | ACH-001645", - "Melanoma | ACH-001970", - "Melanoma | ACH-001972", - "Melanoma | ACH-001973", - "Melanoma | ACH-001975", - "Melanoma | ACH-001982", - "Melanoma | ACH-001986", - "Melanoma | ACH-001990", - "Melanoma | ACH-002001", - "Melanoma | ACH-002002", - "Melanoma | ACH-002003", - "Melanoma | ACH-002004", - "Melanoma | ACH-002005", - "Melanoma | ACH-002084", - "Melanoma | ACH-002143", - "Melanoma | ACH-002458", - "Melanoma | ACH-002460", - "Melanoma | ACH-002461", - "Melanoma | ACH-002508", - "Melanoma | ACH-002510", - "Melanoma | ACH-002511", - "Melanoma | ACH-002512", - "Melanoma | ACH-002847", - "Melanoma | ACH-002928" - ], - "type": "scattergl", - "x": { - "bdata": "wIZwPwrOCUCZ4C6/IkRkPknklz+lRba+GRFjP70HM8ChWDTAD8S2P2WHMMApJDPAxRvdPQ4HLb9umDbA2HjgPZLpnj/KWE4/6rMwwLF6CD+hPgQ/agByPeDZMsD2ExU/fql2PrH1S7/AbQM/yHCfP0Djyj9SMo8/rjkwwM/cuz+22KE/q09PP06whb53SaA/iiwFP/XxM8BTXTPAdxw0wJYwNsCtMTDAkv8aPtl4PD9OxCrAOuMxwOYoLsBDp5M/ZNOyP0OEzT81d7s/pPQHQJBsQj9ekjTAj4qTP1Bahr2KFoO/GqlfP/GyWj+PEDQ9yrKcvs6dnD/lyne/WH4OPhGo5zvh/D+/", - "dtype": "f4" - }, - "y": { - "bdata": 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"ACH-001393", - "ACH-001394", - "ACH-001396", - "ACH-001419", - "ACH-001662", - "ACH-001683", - "ACH-001819", - "ACH-002179", - "ACH-002399", - "ACH-002401" - ], - "hoverinfo": "text", - "marker": { - "color": "#FF6692", - "size": 7 - }, - "mode": "markers", - "name": "Invasive Breast Carcinoma", - "text": [ - "Invasive Breast Carcinoma | ACH-000017", - "Invasive Breast Carcinoma | ACH-000019", - "Invasive Breast Carcinoma | ACH-000028", - "Invasive Breast Carcinoma | ACH-000097", - "Invasive Breast Carcinoma | ACH-000111", - "Invasive Breast Carcinoma | ACH-000147", - "Invasive Breast Carcinoma | ACH-000148", - "Invasive Breast Carcinoma | ACH-000212", - "Invasive Breast Carcinoma | ACH-000223", - "Invasive Breast Carcinoma | ACH-000248", - "Invasive Breast Carcinoma | ACH-000258", - "Invasive Breast Carcinoma | ACH-000276", - "Invasive Breast Carcinoma | ACH-000277", - "Invasive Breast Carcinoma | ACH-000288", - "Invasive Breast Carcinoma | ACH-000330", - "Invasive Breast Carcinoma | ACH-000352", - "Invasive Breast Carcinoma | ACH-000374", - "Invasive Breast Carcinoma | ACH-000554", - "Invasive Breast Carcinoma | ACH-000573", - "Invasive Breast Carcinoma | ACH-000621", - "Invasive Breast Carcinoma | ACH-000668", - "Invasive Breast Carcinoma | ACH-000699", - "Invasive Breast Carcinoma | ACH-000711", - "Invasive Breast Carcinoma | ACH-000721", - "Invasive Breast Carcinoma | ACH-000768", - "Invasive Breast Carcinoma | ACH-000783", - "Invasive Breast Carcinoma | ACH-000849", - "Invasive Breast Carcinoma | ACH-000856", - "Invasive Breast Carcinoma | ACH-000876", - "Invasive Breast Carcinoma | ACH-000910", - "Invasive Breast Carcinoma | ACH-000934", - "Invasive Breast Carcinoma | ACH-001065", - "Invasive Breast Carcinoma | ACH-001388", - "Invasive Breast Carcinoma | ACH-001389", - "Invasive Breast Carcinoma | ACH-001390", - "Invasive Breast Carcinoma | ACH-001391", - "Invasive Breast Carcinoma | ACH-001392", - "Invasive Breast Carcinoma | ACH-001393", - "Invasive Breast Carcinoma | ACH-001394", - "Invasive Breast Carcinoma | ACH-001396", - "Invasive Breast Carcinoma | ACH-001419", - "Invasive Breast Carcinoma | ACH-001662", - "Invasive Breast Carcinoma | ACH-001683", - "Invasive Breast Carcinoma | ACH-001819", - "Invasive Breast Carcinoma | ACH-002179", - "Invasive Breast Carcinoma | ACH-002399", - "Invasive Breast Carcinoma | ACH-002401" - ], - "type": "scattergl", - "x": { - "bdata": "ty4IPkG2SD8wkr8/Ryr7PkxfkD9HrpU/IPKMPqLb2T4Fr8O+ytY0P0QcMb7ZmfC9A2nIPaU9CT9dRwM/j3f1Pn+ZQD+I5xW/Au0TP5Rfg7+4vfa98V0Rv7zDQD+lpYw/NtbjPg4COb+uRZk/opENQJd7OL6hX68/WUptv2iQ5D/GtQ2/EwUxwISDFz/XVEq/CU45wIwoM8CkKDjAlWA6wIppcj4a2PO8CDtuPg4osr78rY8/dS78PqoWUj8=", - "dtype": "f4" - }, - "y": { - "bdata": "Pn1sPuZ3PLzIXkW/BV3lPYBms76TddK+pDbtPq6BCD7e5zU/fnWpvY1JPT/QlUY/rZikPsJqtj7nbsy8ZuQNO2XTj70nfpI/EuTkOwR9vj8NS1I/TsFmP8s+qr4YUuS+RFMePkBkij/VOJu+WTSav+K/Uz+AuBu/Ny/YP9ZqV79KupE/Up58v/OMmD6NHKg/2BIHv5xSYr+PRCG/j23ZvhyXpT4rOfE+mKyxPsvJJD+q0uS+/zWcPseZIL4=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000022", - "ACH-000023", - "ACH-000042", - "ACH-000060", - "ACH-000085", - "ACH-000093", - "ACH-000094", - "ACH-000114", - "ACH-000118", - "ACH-000138", - "ACH-000139", - "ACH-000155", - "ACH-000164", - "ACH-000178", - "ACH-000213", - "ACH-000222", - "ACH-000235", - "ACH-000243", - "ACH-000265", - "ACH-000266", - "ACH-000281", - "ACH-000307", - "ACH-000320", - "ACH-000332", - "ACH-000354", - "ACH-000417", - "ACH-000468", - "ACH-000502", - "ACH-000517", - "ACH-000535", - "ACH-000599", - "ACH-000601", - "ACH-000652", - "ACH-001098", - "ACH-001107", - "ACH-001353", - "ACH-001375", - "ACH-001377", - "ACH-001379", - "ACH-001380", - "ACH-001382", - "ACH-001999", - "ACH-002039", - "ACH-002186", - "ACH-002672" - ], - "hoverinfo": "text", - "marker": { - "color": "#B6E880", - "size": 7 - }, - "mode": "markers", - "name": "Pancreatic Adenocarcinoma", - "text": [ - "Pancreatic Adenocarcinoma | ACH-000022", - "Pancreatic Adenocarcinoma | ACH-000023", - "Pancreatic Adenocarcinoma | ACH-000042", - "Pancreatic Adenocarcinoma | ACH-000060", - "Pancreatic Adenocarcinoma | ACH-000085", - "Pancreatic Adenocarcinoma | ACH-000093", - "Pancreatic Adenocarcinoma | ACH-000094", - "Pancreatic Adenocarcinoma | ACH-000114", - "Pancreatic Adenocarcinoma | ACH-000118", - "Pancreatic Adenocarcinoma | ACH-000138", - "Pancreatic Adenocarcinoma | ACH-000139", - "Pancreatic Adenocarcinoma | ACH-000155", - "Pancreatic Adenocarcinoma | ACH-000164", - "Pancreatic Adenocarcinoma | ACH-000178", - "Pancreatic Adenocarcinoma | ACH-000213", - "Pancreatic Adenocarcinoma | ACH-000222", - "Pancreatic Adenocarcinoma | ACH-000235", - "Pancreatic Adenocarcinoma | ACH-000243", - "Pancreatic Adenocarcinoma | ACH-000265", - "Pancreatic Adenocarcinoma | ACH-000266", - "Pancreatic Adenocarcinoma | ACH-000281", - "Pancreatic Adenocarcinoma | ACH-000307", - "Pancreatic Adenocarcinoma | ACH-000320", - "Pancreatic Adenocarcinoma | ACH-000332", - "Pancreatic Adenocarcinoma | ACH-000354", - "Pancreatic Adenocarcinoma | ACH-000417", - "Pancreatic Adenocarcinoma | ACH-000468", - "Pancreatic Adenocarcinoma | ACH-000502", - "Pancreatic Adenocarcinoma | ACH-000517", - "Pancreatic Adenocarcinoma | ACH-000535", - "Pancreatic Adenocarcinoma | ACH-000599", - "Pancreatic Adenocarcinoma | ACH-000601", - "Pancreatic Adenocarcinoma | ACH-000652", - "Pancreatic Adenocarcinoma | ACH-001098", - "Pancreatic Adenocarcinoma | ACH-001107", - "Pancreatic Adenocarcinoma | ACH-001353", - "Pancreatic Adenocarcinoma | ACH-001375", - "Pancreatic Adenocarcinoma | ACH-001377", - "Pancreatic Adenocarcinoma | ACH-001379", - "Pancreatic Adenocarcinoma | ACH-001380", - "Pancreatic Adenocarcinoma | ACH-001382", - "Pancreatic Adenocarcinoma | ACH-001999", - "Pancreatic Adenocarcinoma | ACH-002039", - "Pancreatic Adenocarcinoma | ACH-002186", - "Pancreatic Adenocarcinoma | ACH-002672" - ], - "type": "scattergl", - "x": { - "bdata": 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"ACH-000660", - "ACH-000697", - "ACH-000714", - "ACH-000763", - "ACH-000817", - "ACH-000821", - "ACH-000829", - "ACH-000838", - "ACH-000889", - "ACH-000914", - "ACH-000944", - "ACH-001450", - "ACH-001498", - "ACH-001533", - "ACH-001539", - "ACH-001616", - "ACH-001634", - "ACH-001639", - "ACH-001677", - "ACH-001707", - "ACH-001709", - "ACH-002055", - "ACH-002062", - "ACH-002214", - "ACH-002215", - "ACH-002478", - "ACH-002485", - "ACH-002500", - "ACH-002677", - "ACH-002678" - ], - "hoverinfo": "text", - "marker": { - "color": "#FF97FF", - "size": 7 - }, - "mode": "markers", - "name": "Mature B-Cell Neoplasms", - "text": [ - "Mature B-Cell Neoplasms | ACH-000024", - "Mature B-Cell Neoplasms | ACH-000106", - "Mature B-Cell Neoplasms | ACH-000124", - "Mature B-Cell Neoplasms | ACH-000167", - "Mature B-Cell Neoplasms | ACH-000183", - "Mature B-Cell Neoplasms | ACH-000204", - "Mature B-Cell Neoplasms | ACH-000271", - "Mature B-Cell Neoplasms | ACH-000315", - "Mature B-Cell Neoplasms | ACH-000334", - "Mature B-Cell Neoplasms | ACH-000346", - "Mature B-Cell Neoplasms | ACH-000363", - "Mature B-Cell Neoplasms | ACH-000365", - "Mature B-Cell Neoplasms | ACH-000371", - "Mature B-Cell Neoplasms | ACH-000398", - "Mature B-Cell Neoplasms | ACH-000402", - "Mature B-Cell Neoplasms | ACH-000405", - "Mature B-Cell Neoplasms | ACH-000426", - "Mature B-Cell Neoplasms | ACH-000436", - "Mature B-Cell Neoplasms | ACH-000512", - "Mature B-Cell Neoplasms | ACH-000541", - "Mature B-Cell Neoplasms | ACH-000567", - "Mature B-Cell Neoplasms | ACH-000576", - "Mature B-Cell Neoplasms | ACH-000588", - "Mature B-Cell Neoplasms | ACH-000653", - "Mature B-Cell Neoplasms | ACH-000654", - "Mature B-Cell Neoplasms | ACH-000656", - "Mature B-Cell Neoplasms | ACH-000660", - "Mature B-Cell Neoplasms | ACH-000697", - "Mature B-Cell Neoplasms | ACH-000714", - "Mature B-Cell Neoplasms | ACH-000763", - "Mature B-Cell Neoplasms | ACH-000817", - "Mature B-Cell Neoplasms | ACH-000821", - "Mature B-Cell Neoplasms | ACH-000829", - "Mature B-Cell Neoplasms | ACH-000838", - "Mature B-Cell Neoplasms | ACH-000889", - "Mature B-Cell Neoplasms | ACH-000914", - "Mature B-Cell Neoplasms | ACH-000944", - "Mature B-Cell Neoplasms | ACH-001450", - "Mature B-Cell Neoplasms | ACH-001498", - "Mature B-Cell Neoplasms | ACH-001533", - "Mature B-Cell Neoplasms | ACH-001539", - "Mature B-Cell Neoplasms | ACH-001616", - "Mature B-Cell Neoplasms | ACH-001634", - "Mature B-Cell Neoplasms | ACH-001639", - "Mature B-Cell Neoplasms | ACH-001677", - "Mature B-Cell Neoplasms | ACH-001707", - "Mature B-Cell Neoplasms | ACH-001709", - "Mature B-Cell Neoplasms | ACH-002055", - "Mature B-Cell Neoplasms | ACH-002062", - "Mature B-Cell Neoplasms | ACH-002214", - "Mature B-Cell Neoplasms | ACH-002215", - "Mature B-Cell Neoplasms | ACH-002478", - "Mature B-Cell Neoplasms | ACH-002485", - "Mature B-Cell Neoplasms | ACH-002500", - "Mature B-Cell Neoplasms | ACH-002677", - "Mature B-Cell Neoplasms | ACH-002678" - ], - "type": "scattergl", - "x": { - "bdata": "NsiSPwC+Pz8hXiFABlJxP3Eq7T/SW9w/wAEzQDOXaT8lb8+9VWLKP+b6mD4RNvc/jpa5P+24oT8SvVk/qZLSPxK1kj5r8TPAToyeP3xcVj+ROC7AL+zwPrdI3z/84ow/YJ+QP87RJ0BuqyBAn+e0P16xhj9EaDE/8datP0xhTz/h4S/ApqBKPz5uAUBjWQtA2ZPRP09ozj+RT9w/3ZYwwGjeLj88OAlAn04zwNlVij9apT8/KyAzwKiWGEDihJo/73FbP1dxBkDYKbM/TdyaPxqUiT+tY/w/kr4BQMyihT8=", - "dtype": "f4" - }, - "y": { - "bdata": "nU04v2ntF7x+Wb6/1RnFvqnEvL8mYpG/ojLzv8Sm4r6b9gU/fwQyv2iwj70GBra/J1RXv9XTD79vsFq+L5iLvy7FAb6XtVi/nFQev/6UXL66OI2/rKsivv3Nnr+ZayO/yzoRv4pO0L9PWMC/DLdev6XoJb9aGq2+dYxSv1ido74nqYq/hW7qvv5avb+cScK/JX5xv/xuWb+IfYi/Jid/vyQiOr7xoNm/D7ZUvyfjOr7MuxO+DY1jv2qC3r+FuCK/vQJjvmPjp7/JZ1e/n8k3v0jHBb9J+ai/FxLDv+Sg8r4=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000025", - "ACH-001067", - "ACH-002070" - ], - "hoverinfo": "text", - "marker": { - "color": "#FECB52", - "size": 7 - }, - "mode": "markers", - "name": "Meningothelial Tumor", - "text": [ - "Meningothelial Tumor | ACH-000025", - "Meningothelial Tumor | ACH-001067", - "Meningothelial Tumor | ACH-002070" - ], - "type": "scattergl", - "x": { - "bdata": "BkN0P2IBL8BrNME+", - "dtype": "f4" - }, - "y": { - "bdata": "dSz3vbf5iL9jX7k+", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000036", - "ACH-000040", - "ACH-000067", - "ACH-000075", - "ACH-000098", - "ACH-000128", - "ACH-000137", - "ACH-000152", - "ACH-000200", - "ACH-000208", - "ACH-000215", - "ACH-000231", - "ACH-000232", - "ACH-000244", - "ACH-000269", - "ACH-000273", - "ACH-000323", - "ACH-000329", - "ACH-000368", - "ACH-000370", - "ACH-000376", - "ACH-000389", - "ACH-000437", - "ACH-000445", - "ACH-000455", - "ACH-000464", - "ACH-000469", - "ACH-000479", - "ACH-000504", - "ACH-000558", - "ACH-000570", - "ACH-000571", - "ACH-000591", - "ACH-000592", - "ACH-000595", - "ACH-000609", - "ACH-000622", - "ACH-000623", - "ACH-000631", - "ACH-000634", - "ACH-000655", - "ACH-000673", - "ACH-000676", - "ACH-000738", - "ACH-000756", - "ACH-000760", - "ACH-000807", - "ACH-000819", - "ACH-000863", - "ACH-000887", - "ACH-001016", - "ACH-001126", - "ACH-001172", - "ACH-001329", - "ACH-001605", - "ACH-001606", - "ACH-001608", - "ACH-001609", - "ACH-001610", - "ACH-001611", - "ACH-001622", - "ACH-001623", - "ACH-001624", - "ACH-002228", - "ACH-002229", - "ACH-002230", - "ACH-002257", - "ACH-002269", - "ACH-002304", - "ACH-002680" - ], - "hoverinfo": "text", - "marker": { - "color": "#FD3216", - "size": 7 - }, - "mode": "markers", - "name": "Diffuse Glioma", - "text": [ - "Diffuse Glioma | ACH-000036", - "Diffuse Glioma | ACH-000040", - "Diffuse Glioma | ACH-000067", - "Diffuse Glioma | ACH-000075", - "Diffuse Glioma | ACH-000098", - "Diffuse Glioma | ACH-000128", - "Diffuse Glioma | ACH-000137", - "Diffuse Glioma | ACH-000152", - "Diffuse Glioma | ACH-000200", - "Diffuse Glioma | ACH-000208", - "Diffuse Glioma | ACH-000215", - "Diffuse Glioma | ACH-000231", - "Diffuse Glioma | ACH-000232", - "Diffuse Glioma | ACH-000244", - "Diffuse Glioma | ACH-000269", - "Diffuse Glioma | ACH-000273", - "Diffuse Glioma | ACH-000323", - "Diffuse Glioma | ACH-000329", - "Diffuse Glioma | ACH-000368", - "Diffuse Glioma | ACH-000370", - "Diffuse Glioma | ACH-000376", - "Diffuse Glioma | ACH-000389", - "Diffuse Glioma | ACH-000437", - "Diffuse Glioma | ACH-000445", - "Diffuse Glioma | ACH-000455", - "Diffuse Glioma | ACH-000464", - "Diffuse Glioma | ACH-000469", - "Diffuse Glioma | ACH-000479", - "Diffuse Glioma | ACH-000504", - "Diffuse Glioma | ACH-000558", - "Diffuse Glioma | ACH-000570", - "Diffuse Glioma | ACH-000571", - "Diffuse Glioma | ACH-000591", - "Diffuse Glioma | ACH-000592", - "Diffuse Glioma | ACH-000595", - "Diffuse Glioma | ACH-000609", - "Diffuse Glioma | ACH-000622", - "Diffuse Glioma | ACH-000623", - "Diffuse Glioma | ACH-000631", - "Diffuse Glioma | ACH-000634", - "Diffuse Glioma | ACH-000655", - "Diffuse Glioma | ACH-000673", - "Diffuse Glioma | ACH-000676", - "Diffuse Glioma | ACH-000738", - "Diffuse Glioma | ACH-000756", - "Diffuse Glioma | ACH-000760", - "Diffuse Glioma | ACH-000807", - "Diffuse Glioma | ACH-000819", - "Diffuse Glioma | ACH-000863", - "Diffuse Glioma | ACH-000887", - "Diffuse Glioma | ACH-001016", - "Diffuse Glioma | ACH-001126", - "Diffuse Glioma | ACH-001172", - "Diffuse Glioma | ACH-001329", - "Diffuse Glioma | ACH-001605", - "Diffuse Glioma | ACH-001606", - "Diffuse Glioma | ACH-001608", - "Diffuse Glioma | ACH-001609", - "Diffuse Glioma | ACH-001610", - "Diffuse Glioma | ACH-001611", - "Diffuse Glioma | ACH-001622", - "Diffuse Glioma | ACH-001623", - "Diffuse Glioma | ACH-001624", - "Diffuse Glioma | ACH-002228", - "Diffuse Glioma | ACH-002229", - "Diffuse Glioma | ACH-002230", - "Diffuse Glioma | ACH-002257", - "Diffuse Glioma | ACH-002269", - "Diffuse Glioma | ACH-002304", - "Diffuse Glioma | ACH-002680" - ], - "type": "scattergl", - "x": { - "bdata": 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[ - "Sarcoma, NOS | ACH-000037" - ], - "type": "scattergl", - "x": { - "bdata": "YKEUvw==", - "dtype": "f4" - }, - "y": { - "bdata": "DF+/Pw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000039", - "ACH-000041", - "ACH-000052", - "ACH-000087", - "ACH-000210", - "ACH-000279", - "ACH-000391", - "ACH-000424", - "ACH-000499", - "ACH-001029", - "ACH-001038", - "ACH-001192", - "ACH-001193", - "ACH-001205", - "ACH-001283", - "ACH-001430", - "ACH-001431", - "ACH-002105", - "ACH-002106", - "ACH-002109", - "ACH-002110", - "ACH-002114", - "ACH-002116", - "ACH-002119", - "ACH-002160" - ], - "hoverinfo": "text", - "marker": { - "color": "#6A76FC", - "size": 7 - }, - "mode": "markers", - "name": "Ewing Sarcoma", - "text": [ - "Ewing Sarcoma | ACH-000039", - "Ewing Sarcoma | ACH-000041", - "Ewing Sarcoma | ACH-000052", - "Ewing Sarcoma | ACH-000087", - "Ewing Sarcoma | ACH-000210", - "Ewing Sarcoma | ACH-000279", - "Ewing Sarcoma | ACH-000391", - "Ewing Sarcoma | ACH-000424", - "Ewing Sarcoma | ACH-000499", - "Ewing Sarcoma | ACH-001029", - "Ewing Sarcoma | ACH-001038", - "Ewing Sarcoma | ACH-001192", - "Ewing Sarcoma | ACH-001193", - "Ewing Sarcoma | ACH-001205", - "Ewing Sarcoma | ACH-001283", - "Ewing Sarcoma | ACH-001430", - "Ewing Sarcoma | ACH-001431", - "Ewing Sarcoma | ACH-002105", - "Ewing Sarcoma | ACH-002106", - "Ewing Sarcoma | ACH-002109", - "Ewing Sarcoma | ACH-002110", - "Ewing Sarcoma | ACH-002114", - "Ewing Sarcoma | ACH-002116", - "Ewing Sarcoma | ACH-002119", - "Ewing Sarcoma | ACH-002160" - ], - "type": "scattergl", - "x": { - "bdata": "5HyQve9fPT7rWWM+IvSFP54S8D4hQq4/A7vCPxxv8j+INpA/RBjTPx75kT+FYCY/TIzSPuAKID+2OWw/3FzoPtVdTj/netk+fujFPwDMQD/M+QBARHo1wD8pNcC+ouQ/VZDcPw==", - "dtype": "f4" - }, - "y": { - "bdata": "/ERmPwqqKz8gjiY/q2bgvaov5j4OhwK/nx10vpMNGr8AyXC+O3MgvzoEqb4/uoE+jpa9PmD2KT1J0K29hzjDPnaf5L0K2Dc/ZLUgv94Haj57XF2/cgY+v/J1Pb/Ctii/7+4Svw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000047", - "ACH-000144", - "ACH-000216", - "ACH-000239", - "ACH-000247", - "ACH-000255", - "ACH-000303", - "ACH-000325", - "ACH-000344", - "ACH-000356", - "ACH-000383", - "ACH-000427", - "ACH-000466", - "ACH-000485", - "ACH-000507", - "ACH-000581", - "ACH-000616", - "ACH-000633", - "ACH-000736", - "ACH-000746", - "ACH-000758", - "ACH-000764", - "ACH-000793", - "ACH-000847", - "ACH-000880", - "ACH-000898", - "ACH-000911", - "ACH-000919", - "ACH-000932", - "ACH-000948", - "ACH-001368", - "ACH-001496", - "ACH-001497", - "ACH-001500", - "ACH-001544", - "ACH-001653", - "ACH-001654", - "ACH-001664", - "ACH-002141", - "ACH-002161", - "ACH-002202", - "ACH-002446", - "ACH-002705", - "ACH-002706" - ], - "hoverinfo": "text", - "marker": { - "color": "#FED4C4", - "size": 7 - }, - "mode": "markers", - "name": "Esophagogastric Adenocarcinoma", - "text": [ - "Esophagogastric Adenocarcinoma | ACH-000047", - "Esophagogastric Adenocarcinoma | ACH-000144", - "Esophagogastric Adenocarcinoma | ACH-000216", - "Esophagogastric Adenocarcinoma | ACH-000239", - "Esophagogastric Adenocarcinoma | ACH-000247", - "Esophagogastric Adenocarcinoma | ACH-000255", - "Esophagogastric Adenocarcinoma | ACH-000303", - "Esophagogastric Adenocarcinoma | ACH-000325", - "Esophagogastric Adenocarcinoma | ACH-000344", - "Esophagogastric Adenocarcinoma | ACH-000356", - "Esophagogastric Adenocarcinoma | ACH-000383", - "Esophagogastric Adenocarcinoma | ACH-000427", - "Esophagogastric Adenocarcinoma | ACH-000466", - "Esophagogastric Adenocarcinoma | ACH-000485", - "Esophagogastric Adenocarcinoma | ACH-000507", - "Esophagogastric Adenocarcinoma | ACH-000581", - "Esophagogastric Adenocarcinoma | ACH-000616", - "Esophagogastric Adenocarcinoma | ACH-000633", - "Esophagogastric Adenocarcinoma | ACH-000736", - "Esophagogastric Adenocarcinoma | ACH-000746", - "Esophagogastric Adenocarcinoma | ACH-000758", - "Esophagogastric Adenocarcinoma | ACH-000764", - "Esophagogastric Adenocarcinoma | ACH-000793", - "Esophagogastric Adenocarcinoma | ACH-000847", - "Esophagogastric Adenocarcinoma | ACH-000880", - "Esophagogastric Adenocarcinoma | ACH-000898", - "Esophagogastric Adenocarcinoma | ACH-000911", - "Esophagogastric Adenocarcinoma | ACH-000919", - "Esophagogastric Adenocarcinoma | ACH-000932", - "Esophagogastric Adenocarcinoma | ACH-000948", - "Esophagogastric Adenocarcinoma | ACH-001368", - "Esophagogastric Adenocarcinoma | ACH-001496", - "Esophagogastric Adenocarcinoma | ACH-001497", - "Esophagogastric Adenocarcinoma | ACH-001500", - "Esophagogastric Adenocarcinoma | ACH-001544", - "Esophagogastric Adenocarcinoma | ACH-001653", - "Esophagogastric Adenocarcinoma | ACH-001654", - "Esophagogastric Adenocarcinoma | ACH-001664", - "Esophagogastric Adenocarcinoma | ACH-002141", - "Esophagogastric Adenocarcinoma | ACH-002161", - "Esophagogastric Adenocarcinoma | ACH-002202", - "Esophagogastric Adenocarcinoma | ACH-002446", - "Esophagogastric Adenocarcinoma | ACH-002705", - "Esophagogastric Adenocarcinoma | ACH-002706" - ], - "type": "scattergl", - "x": { - "bdata": "yozFPzWfT7+uzh8/IfiKPRGGhz+1ueY+QRE4P6SSnz/XTrE+JlTqPiF3AT4UozPAn5vFveLgVD+4bqo/qQYvP/bv2L2OdIo/LxaZP6/yDz+Ubow/Nv42wGf5kj/MIC/AcY63P3tm8j7W+J8/6kggP/b7tz+2/qA/VuN4P81eDD+spOI+iFKHP4KtjD2TZz4/Y2UwPyLV2z/e5OI/7tVkPwqcYz/ac4A/XT5hP6GipD8=", - "dtype": "f4" - }, - "y": { - "bdata": "0F1Iv6dvtj/qPNU9u6IaPzXfA7+959o+QgVIvWKaIL9qzHo+GNOBPuGfaz4CUFK/F20uP01TJb0XkzS/d8FYvSOCRT+XwT2+mPv1vqlOKT50V6u+3FgqvxEyDr/ap42/gMgjv3QDbL3Q8+e++R0KPpbUUr801Da//gXGvmVANL6M1H49pV9Rvq0urT7PEay9v7xMPgXXib+k9GK/INs8vurXg75LK+S+LvIDvsvnIr8=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000053", - "ACH-000101", - "ACH-000226", - "ACH-000233", - "ACH-000338", - "ACH-000664", - "ACH-000773", - "ACH-001111", - "ACH-001119", - "ACH-001737" - ], - "hoverinfo": "text", - "marker": { - "color": "#FE00CE", - "size": 7 - }, - "mode": "markers", - "name": "Mature T and NK Neoplasms", - "text": [ - "Mature T and NK Neoplasms | ACH-000053", - "Mature T and NK Neoplasms | ACH-000101", - "Mature T and NK Neoplasms | ACH-000226", - "Mature T and NK Neoplasms | ACH-000233", - "Mature T and NK Neoplasms | ACH-000338", - "Mature T and NK Neoplasms | ACH-000664", - "Mature T and NK Neoplasms | ACH-000773", - "Mature T and NK Neoplasms | ACH-001111", - "Mature T and NK Neoplasms | ACH-001119", - "Mature T and NK Neoplasms | ACH-001737" - ], - "type": "scattergl", - "x": { - "bdata": "w/RRP0TM5j9x3Lc/5rKhP7Xy/D5hARJAzPhuPxnvNz/1NZ++yX8zPw==", - "dtype": "f4" - }, - "y": { - "bdata": "CX/IvjNkh78QJlS/lw0iv6BQyT4pp62/yj3Zvoh6Cz3D43I/75TxPQ==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000054" - ], - "hoverinfo": "text", - "marker": { - "color": "#0DF9FF", - "size": 7 - }, - "mode": "markers", - "name": "Fibrosarcoma", - "text": [ - "Fibrosarcoma | ACH-000054" - ], - "type": "scattergl", - "x": { - "bdata": "Xb2cPg==", - "dtype": "f4" - }, - "y": { - "bdata": "2PABPw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000055", - "ACH-000095", - "ACH-000160", - "ACH-000211", - "ACH-000776", - "ACH-001020", - "ACH-001028", - "ACH-001031", - "ACH-001033", - "ACH-001053", - "ACH-001054", - "ACH-001232", - "ACH-001289", - "ACH-001670", - "ACH-001711" - ], - "hoverinfo": "text", - "marker": { - "color": "#F6F926", - "size": 7 - }, - "mode": "markers", - "name": "Embryonal Tumor", - "text": [ - "Embryonal Tumor | ACH-000055", - "Embryonal Tumor | ACH-000095", - "Embryonal Tumor | ACH-000160", - "Embryonal Tumor | ACH-000211", - "Embryonal Tumor | ACH-000776", - "Embryonal Tumor | ACH-001020", - "Embryonal Tumor | ACH-001028", - "Embryonal Tumor | ACH-001031", - "Embryonal Tumor | ACH-001033", - "Embryonal Tumor | ACH-001053", - "Embryonal Tumor | ACH-001054", - "Embryonal Tumor | ACH-001232", - "Embryonal Tumor | ACH-001289", - "Embryonal Tumor | ACH-001670", - "Embryonal Tumor | ACH-001711" - ], - "type": "scattergl", - "x": { - "bdata": "J8WEP0P6Xz//2OA/5R6aPSWYIT+tPQY//We+P+DJvj/qpyU/l18bP7Ziyz8j2AA9uvk0P14NgT+i1Eo/", - "dtype": "f4" - }, - "y": { - "bdata": "CwenvkQ2Lr5OaFu/WsE7PySRKj7i35g+uEIXvyqTFb8zmE8+mSwJPU8nUr/zUIs/ofHDPekKPb6OtoY+", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000070", - "ACH-000151", - "ACH-000782", - "ACH-000922", - "ACH-000938", - "ACH-000960", - "ACH-001484", - "ACH-001520", - "ACH-001669", - "ACH-001735", - "ACH-001736", - "ACH-001993", - "ACH-002059" - ], - "hoverinfo": "text", - "marker": { - "color": "#FF9616", - "size": 7 - }, - "mode": "markers", - "name": "B-Lymphoblastic Leukemia/Lymphoma", - "text": [ - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000070", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000151", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000782", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000922", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000938", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000960", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001484", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001520", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001669", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001735", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001736", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001993", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-002059" - ], - "type": "scattergl", - "x": { - "bdata": "zSnTPzVNcz8uvbk/E4gKQGpV8j+lytg/BXGlP1VYzj/+fP8/H+OjPymGCUA5A2k/MN+7Pw==", - "dtype": "f4" - }, - "y": { - "bdata": "xTR/vxyTAr+8Ekq/TKrJv/jokL/9A2y/jZ4zvzMNa78I/6W//So6vyh6tb+YgbG+cUZQvw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000074", - "ACH-000076", - "ACH-000198", - "ACH-000295", - "ACH-000326", - "ACH-000551", - "ACH-000604", - "ACH-000920", - "ACH-000983", - "ACH-002061" - ], - "hoverinfo": "text", - "marker": { - "color": "#479B55", - "size": 7 - }, - "mode": "markers", - "name": "Myeloproliferative Neoplasms", - "text": [ - "Myeloproliferative Neoplasms | ACH-000074", - "Myeloproliferative Neoplasms | ACH-000076", - "Myeloproliferative Neoplasms | ACH-000198", - "Myeloproliferative Neoplasms | ACH-000295", - "Myeloproliferative Neoplasms | ACH-000326", - "Myeloproliferative Neoplasms | ACH-000551", - "Myeloproliferative Neoplasms | ACH-000604", - "Myeloproliferative Neoplasms | ACH-000920", - "Myeloproliferative Neoplasms | ACH-000983", - "Myeloproliferative Neoplasms | ACH-002061" - ], - "type": "scattergl", - "x": { - "bdata": "sTGYPxZyqj/zjR1ATKYGPzTrwj+qiak/eXpjP73FAz8B8+c/QSymPw==", - "dtype": "f4" - }, - "y": { - "bdata": "fh4hv2Z8Kb8ddN2/YQOTPdfsfL/O4Bm/QXJYvrfEPT5FRpi/R6YDvw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000077", - "ACH-000583", - "ACH-001197", - "ACH-001642" - ], - "hoverinfo": "text", - "marker": { - "color": "#EEA6FB", - "size": 7 - }, - "mode": "markers", - "name": "Non-Hodgkin Lymphoma", - "text": [ - "Non-Hodgkin Lymphoma | ACH-000077", - "Non-Hodgkin Lymphoma | ACH-000583", - "Non-Hodgkin Lymphoma | ACH-001197", - "Non-Hodgkin Lymphoma | ACH-001642" - ], - "type": "scattergl", - "x": { - "bdata": "OgKzPwCyI8CdJ48/JesyPw==", - "dtype": "f4" - }, - "y": { - "bdata": "/9oovw5V0r+ougS/V/CsvA==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000078", - "ACH-000099", - "ACH-000120", - "ACH-000149", - "ACH-000203", - "ACH-000227", - "ACH-000259", - "ACH-000260", - "ACH-000310", - "ACH-000312", - "ACH-000341", - "ACH-000366", - "ACH-000804", - "ACH-001188", - "ACH-001300", - "ACH-001301", - "ACH-001302", - "ACH-001303", - "ACH-001338", - "ACH-001344", - "ACH-001354", - "ACH-001366", - "ACH-001367", - "ACH-001481", - "ACH-001548", - "ACH-001603", - "ACH-001674", - "ACH-002080", - "ACH-002083", - "ACH-002261", - "ACH-002278", - "ACH-002280", - "ACH-002282", - "ACH-002283", - "ACH-002284", - "ACH-002285", - "ACH-002922" - ], - "hoverinfo": "text", - "marker": { - "color": "#DC587D", - "size": 7 - }, - "mode": "markers", - "name": "Neuroblastoma", - "text": [ - "Neuroblastoma | ACH-000078", - "Neuroblastoma | ACH-000099", - "Neuroblastoma | ACH-000120", - "Neuroblastoma | ACH-000149", - "Neuroblastoma | ACH-000203", - "Neuroblastoma | ACH-000227", - "Neuroblastoma | ACH-000259", - "Neuroblastoma | ACH-000260", - "Neuroblastoma | ACH-000310", - "Neuroblastoma | ACH-000312", - "Neuroblastoma | ACH-000341", - "Neuroblastoma | ACH-000366", - "Neuroblastoma | ACH-000804", - "Neuroblastoma | ACH-001188", - "Neuroblastoma | ACH-001300", - "Neuroblastoma | ACH-001301", - "Neuroblastoma | ACH-001302", - "Neuroblastoma | ACH-001303", - "Neuroblastoma | ACH-001338", - "Neuroblastoma | ACH-001344", - "Neuroblastoma | ACH-001354", - "Neuroblastoma | ACH-001366", - "Neuroblastoma | ACH-001367", - "Neuroblastoma | ACH-001481", - "Neuroblastoma | ACH-001548", - "Neuroblastoma | ACH-001603", - "Neuroblastoma | ACH-001674", - "Neuroblastoma | ACH-002080", - "Neuroblastoma | ACH-002083", - "Neuroblastoma | ACH-002261", - "Neuroblastoma | ACH-002278", - "Neuroblastoma | ACH-002280", - "Neuroblastoma | ACH-002282", - "Neuroblastoma | ACH-002283", - "Neuroblastoma | ACH-002284", - "Neuroblastoma | ACH-002285", - "Neuroblastoma | ACH-002922" - ], - "type": "scattergl", - "x": { - "bdata": "m1kbP34SqD9tt+k+wRKDP57ogT0vgsu+5AnmP4aRZz91B8++cVg3P95kWj2qlT0/lnK3P0SWdD8FI6g/vs0SvMan8D5qo2I+LrK5P259kj6XTSA/4p9qPzEmlT85EA4+pMkWPhP/eT8srJM/3aMywO+Jzj/DrNk/G0fQP7ejzD/sp6Q/E+ZaP5NgM8DlfyFAwZCWPw==", - "dtype": "f4" - }, - "y": { - "bdata": "BQ2OPmMv/b4UQXU+99mcvDTAKD856qA/tFZ3v18FLb6ca5c/09sgPZ++Aj/NFRE9OUcwvwTpcr6hKeC+/ZRCPxQWyj4uUQk/X1kEv7UK+T6tdDY+JpBFvj7PxL4+kAk/NK4YP+I25b3K1vy+EFxSv+TQvL5BPkq/Sy8Vv3VJAL//c+S+IYgcvXtIUr9ENpK/UX7jvg==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000082", - "ACH-000359", - "ACH-000364", - "ACH-000410", - "ACH-000748", - "ACH-001001", - "ACH-001526", - "ACH-001715", - "ACH-001814", - "ACH-002067", - "ACH-002069", - "ACH-002471", - "ACH-002834" - ], - "hoverinfo": "text", - "marker": { - "color": "#D626FF", - "size": 7 - }, - "mode": "markers", - "name": "Osteosarcoma", - "text": [ - "Osteosarcoma | ACH-000082", - "Osteosarcoma | ACH-000359", - "Osteosarcoma | ACH-000364", - "Osteosarcoma | ACH-000410", - "Osteosarcoma | ACH-000748", - "Osteosarcoma | ACH-001001", - "Osteosarcoma | ACH-001526", - "Osteosarcoma | ACH-001715", - "Osteosarcoma | ACH-001814", - "Osteosarcoma | ACH-002067", - "Osteosarcoma | ACH-002069", - "Osteosarcoma | ACH-002471", - "Osteosarcoma | ACH-002834" - ], - "type": "scattergl", - "x": { - "bdata": "iIiEv+/OTb/Yl0c/yCXgPsQFND+4+OE/EprBvpuiB78lsSq/ZUTdPrrhNr2ve5C7aVM4wA==", - "dtype": "f4" - }, - "y": { - "bdata": "O5zRP+sHrT8CqIo9GdyvPp1FAj/SXAa/rROPP13Mhz8Zq8E/rV+GPhWMQT9HzGc/fiYavw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000086", - "ACH-000092", - "ACH-000153", - "ACH-000319", - "ACH-000331", - "ACH-000335", - "ACH-000367", - "ACH-000569", - "ACH-000645", - "ACH-000648", - "ACH-001547", - "ACH-001555", - "ACH-001556", - "ACH-001557", - "ACH-001558", - "ACH-001559", - "ACH-001560", - "ACH-001562", - "ACH-001977", - "ACH-001992", - "ACH-002033" - ], - "hoverinfo": "text", - "marker": { - "color": "#6E899C", - "size": 7 - }, - "mode": "markers", - "name": "Pleural Mesothelioma", - "text": [ - "Pleural Mesothelioma | ACH-000086", - "Pleural Mesothelioma | ACH-000092", - "Pleural Mesothelioma | ACH-000153", - "Pleural Mesothelioma | ACH-000319", - "Pleural Mesothelioma | ACH-000331", - "Pleural Mesothelioma | ACH-000335", - "Pleural Mesothelioma | ACH-000367", - "Pleural Mesothelioma | ACH-000569", - "Pleural Mesothelioma | ACH-000645", - "Pleural Mesothelioma | ACH-000648", - "Pleural Mesothelioma | ACH-001547", - "Pleural Mesothelioma | ACH-001555", - "Pleural Mesothelioma | ACH-001556", - "Pleural Mesothelioma | ACH-001557", - "Pleural Mesothelioma | ACH-001558", - "Pleural Mesothelioma | ACH-001559", - "Pleural Mesothelioma | ACH-001560", - "Pleural Mesothelioma | ACH-001562", - "Pleural Mesothelioma | ACH-001977", - "Pleural Mesothelioma | ACH-001992", - "Pleural Mesothelioma | ACH-002033" - ], - "type": "scattergl", - "x": { - "bdata": "h88/P0wYCr/maMS+Xl61vgigiz6T7U0/GCk5wM3GqT7FFPy+jRPNPnShcb6/dn89WugUP0dBij4OczrA0/s2wKY5NMBN6zDA1G+jPwiEcT+wSUq/", - "dtype": "f4" - }, - "y": { - "bdata": "jfPtPUJbnj8D45Y/ty2SPyCD0T6nzRE+z2gGv6coAj+7N6A/Qgq7Pj9yRj+iOhk//gSHPvaPGj/HUf++ChExvychV7+ta4C/5kERvwwDKb5wOL8/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000090", - "ACH-000115", - "ACH-000956", - "ACH-000977", - "ACH-000979", - "ACH-001422", - "ACH-001627", - "ACH-001648", - "ACH-001649" - ], - "hoverinfo": "text", - "marker": { - "color": "#00B5F7", - "size": 7 - }, - "mode": "markers", - "name": "Prostate Adenocarcinoma", - "text": [ - "Prostate Adenocarcinoma | ACH-000090", - "Prostate Adenocarcinoma | ACH-000115", - "Prostate Adenocarcinoma | ACH-000956", - "Prostate Adenocarcinoma | ACH-000977", - "Prostate Adenocarcinoma | ACH-000979", - "Prostate Adenocarcinoma | ACH-001422", - "Prostate Adenocarcinoma | ACH-001627", - "Prostate Adenocarcinoma | ACH-001648", - "Prostate Adenocarcinoma | ACH-001649" - ], - "type": "scattergl", - "x": { - "bdata": "aZDAPF8mXb8lu1M/6fbKPxuS6D7/ZoK/a0IswDp6LcAZojbA", - "dtype": "f4" - }, - "y": { - "bdata": "fb4gPwLimT+eLEu9xFtTv6K0Sj5qAso/MySav9AHlL8X8SW/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000096", - "ACH-000172", - "ACH-000533", - "ACH-000597", - "ACH-001099", - "ACH-001128", - "ACH-001211", - "ACH-001212", - "ACH-001532" - ], - "hoverinfo": "text", - "marker": { - "color": "#B68E00", - "size": 7 - }, - "mode": "markers", - "name": "Rhabdoid Cancer", - "text": [ - "Rhabdoid Cancer | ACH-000096", - "Rhabdoid Cancer | ACH-000172", - "Rhabdoid Cancer | ACH-000533", - "Rhabdoid Cancer | ACH-000597", - "Rhabdoid Cancer | ACH-001099", - "Rhabdoid Cancer | ACH-001128", - "Rhabdoid Cancer | ACH-001211", - "Rhabdoid Cancer | ACH-001212", - "Rhabdoid Cancer | ACH-001532" - ], - "type": "scattergl", - "x": { - "bdata": "BFprPyOAHz/qLtI/X6h9Pz2v2j9ULD8/HMBjP3B/GT8+FM8/", - "dtype": "f4" - }, - "y": { - "bdata": "So8FPSP5mD4e9Tm/pBJBvoR+Rr8MpZi6Nekyvtl5iT5pYWW/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000100", - "ACH-000169", - "ACH-000607", - "ACH-000833", - "ACH-001050", - "ACH-001096", - "ACH-001184", - "ACH-001196", - "ACH-001740", - "ACH-001745", - "ACH-001750", - "ACH-001765", - "ACH-002048" - ], - "hoverinfo": "text", - "marker": { - "color": "#C9FBE5", - "size": 7 - }, - "mode": "markers", - "name": "Rhabdomyosarcoma", - "text": [ - "Rhabdomyosarcoma | ACH-000100", - "Rhabdomyosarcoma | ACH-000169", - "Rhabdomyosarcoma | ACH-000607", - "Rhabdomyosarcoma | ACH-000833", - "Rhabdomyosarcoma | ACH-001050", - "Rhabdomyosarcoma | ACH-001096", - "Rhabdomyosarcoma | ACH-001184", - "Rhabdomyosarcoma | ACH-001196", - "Rhabdomyosarcoma | ACH-001740", - "Rhabdomyosarcoma | ACH-001745", - "Rhabdomyosarcoma | ACH-001750", - "Rhabdomyosarcoma | ACH-001765", - "Rhabdomyosarcoma | ACH-002048" - ], - "type": "scattergl", - "x": { - "bdata": "wPV0P5vxbD8mlCY/0gCBP0xqk72jI80/tUKsP998cz8DFB4/eelmP+7uVT/a8aY/YmnTPw==", - "dtype": "f4" - }, - "y": { - "bdata": "QLjSvH6p+70UzwI+f1slvgtZPj8iN1G/w0Iev5fhsL562HA9YLuDvr4AET4DafO+BiBTvw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000108", - "ACH-000685" - ], - "hoverinfo": "text", - "marker": { - "color": "#FF0092", - "size": 7 - }, - "mode": "markers", - "name": "Adenosquamous Carcinoma of the Pancreas", - "text": [ - "Adenosquamous Carcinoma of the Pancreas | ACH-000108", - "Adenosquamous Carcinoma of the Pancreas | ACH-000685" - ], - "type": "scattergl", - "x": { - "bdata": "Fy0zv7paYj8=", - "dtype": "f4" - }, - "y": { - "bdata": "QiSGPyPcpD0=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000133", - "ACH-001310", - "ACH-001453", - "ACH-002210", - "ACH-002247", - "ACH-002462", - "ACH-002463", - "ACH-002464", - "ACH-002465", - "ACH-002467" - ], - "hoverinfo": "text", - "marker": { - "color": "#22FFA7", - "size": 7 - }, - "mode": "markers", - "name": "Non-Cancerous", - "text": [ - "Non-Cancerous | ACH-000133", - "Non-Cancerous | ACH-001310", - "Non-Cancerous | ACH-001453", - "Non-Cancerous | ACH-002210", - "Non-Cancerous | ACH-002247", - "Non-Cancerous | ACH-002462", - "Non-Cancerous | ACH-002463", - "Non-Cancerous | ACH-002464", - "Non-Cancerous | ACH-002465", - "Non-Cancerous | ACH-002467" - ], - "type": "scattergl", - "x": { - "bdata": "JhcjPXM/MsC1s5o+rurhP1gZNsBN1zTAsqU3wHZuPMBl9jHAnOg2wA==", - "dtype": "f4" - }, - "y": { - "bdata": "/Wk5P4COZ78Rx7I++RuVvz2fPb965Ei/+FQfv73xyL5Vo2+/pNAtvw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000141", - "ACH-001607", - "ACH-001619", - "ACH-001850", - "ACH-001861", - "ACH-001961" - ], - "hoverinfo": "text", - "marker": { - "color": "#E3EE9E", - "size": 7 - }, - "mode": "markers", - "name": "Intracholecystic Papillary Neoplasm", - "text": [ - "Intracholecystic Papillary Neoplasm | ACH-000141", - "Intracholecystic Papillary Neoplasm | ACH-001607", - "Intracholecystic Papillary Neoplasm | ACH-001619", - "Intracholecystic Papillary Neoplasm | ACH-001850", - "Intracholecystic Papillary Neoplasm | ACH-001861", - "Intracholecystic Papillary Neoplasm | ACH-001961" - ], - "type": "scattergl", - "x": { - "bdata": "MJ45wJ7+cj8S3/a+1jtqP/MLMMAOAyw/", - "dtype": "f4" - }, - "y": { - "bdata": "B8ABv0adib6RoJo/keaTvpd3hr8pXLy8", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000145", - "ACH-000505", - "ACH-002785" - ], - "hoverinfo": "text", - "marker": { - "color": "#86CE00", - "size": 7 - }, - "mode": "markers", - "name": "Leiomyosarcoma", - "text": [ - "Leiomyosarcoma | ACH-000145", - "Leiomyosarcoma | ACH-000505", - "Leiomyosarcoma | ACH-002785" - ], - "type": "scattergl", - "x": { - "bdata": "atgmv5foZr+U+tK+", - "dtype": "f4" - }, - "y": { - "bdata": "oT+zP0oCyz8Zl6Y/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000159", - "ACH-000189", - "ACH-000234", - "ACH-000246", - "ACH-000250", - "ACH-000262", - "ACH-000272", - "ACH-000313", - "ACH-000317", - "ACH-000375", - "ACH-000385", - "ACH-000411", - "ACH-000433", - "ACH-000459", - "ACH-000484", - "ACH-000495", - "ACH-000649", - "ACH-000684", - "ACH-000709", - "ACH-000792", - "ACH-000907", - "ACH-001163", - "ACH-001194", - "ACH-001398", - "ACH-001687", - "ACH-001688", - "ACH-002150", - "ACH-002189", - "ACH-002533" - ], - "hoverinfo": "text", - "marker": { - "color": "#BC7196", - "size": 7 - }, - "mode": "markers", - "name": "Renal Cell Carcinoma", - "text": [ - "Renal Cell Carcinoma | ACH-000159", - "Renal Cell Carcinoma | ACH-000189", - "Renal Cell Carcinoma | ACH-000234", - "Renal Cell Carcinoma | ACH-000246", - "Renal Cell Carcinoma | ACH-000250", - "Renal Cell Carcinoma | ACH-000262", - "Renal Cell Carcinoma | ACH-000272", - "Renal Cell Carcinoma | ACH-000313", - "Renal Cell Carcinoma | ACH-000317", - "Renal Cell Carcinoma | ACH-000375", - "Renal Cell Carcinoma | ACH-000385", - "Renal Cell Carcinoma | ACH-000411", - "Renal Cell Carcinoma | ACH-000433", - "Renal Cell Carcinoma | ACH-000459", - "Renal Cell Carcinoma | ACH-000484", - "Renal Cell Carcinoma | ACH-000495", - "Renal Cell Carcinoma | ACH-000649", - "Renal Cell Carcinoma | ACH-000684", - "Renal Cell Carcinoma | ACH-000709", - "Renal Cell Carcinoma | ACH-000792", - "Renal Cell Carcinoma | ACH-000907", - "Renal Cell Carcinoma | ACH-001163", - "Renal Cell Carcinoma | ACH-001194", - "Renal Cell Carcinoma | ACH-001398", - "Renal Cell Carcinoma | ACH-001687", - "Renal Cell Carcinoma | ACH-001688", - "Renal Cell Carcinoma | ACH-002150", - "Renal Cell Carcinoma | ACH-002189", - "Renal Cell Carcinoma | ACH-002533" - ], - "type": "scattergl", - "x": { - "bdata": "ORHTvlekN8DrbDq/io4wwB8PNsB+wzTAwg04wITiYL/oQjPAzf2kP3oNwjxO+cs+XS6GvtRIB8ByOTzARZTLvkMLHT/0ok69XFhCvwqJMz7pYIa/gkcSP14HPsCzxsG8gpwzwEL1OsBrrjLAyaKSv5x2gj8=", - "dtype": "f4" - }, - "y": { - "bdata": 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"ACH-001695", - "ACH-001696", - "ACH-001698", - "ACH-001699", - "ACH-001701", - "ACH-002029", - "ACH-002030", - "ACH-002042", - "ACH-002043", - "ACH-002044", - "ACH-002045", - "ACH-002212", - "ACH-002249", - "ACH-002250", - "ACH-002251", - "ACH-002265", - "ACH-002294", - "ACH-002295", - "ACH-002296", - "ACH-002297", - "ACH-002298", - "ACH-002305" - ], - "hoverinfo": "text", - "marker": { - "color": "#7E7DCD", - "size": 7 - }, - "mode": "markers", - "name": "Head and Neck Squamous Cell Carcinoma", - "text": [ - "Head and Neck Squamous Cell Carcinoma | ACH-000163", - "Head and Neck Squamous Cell Carcinoma | ACH-000181", - "Head and Neck Squamous Cell Carcinoma | ACH-000188", - "Head and Neck Squamous Cell Carcinoma | ACH-000207", - "Head and Neck Squamous Cell Carcinoma | ACH-000228", - "Head and Neck Squamous Cell Carcinoma | ACH-000238", - "Head and Neck Squamous Cell Carcinoma | ACH-000415", - "Head and Neck Squamous Cell Carcinoma | ACH-000472", - "Head and Neck Squamous Cell Carcinoma | ACH-000500", - "Head and Neck Squamous Cell Carcinoma | ACH-000503", - "Head and Neck Squamous Cell Carcinoma | ACH-000518", - "Head and Neck Squamous Cell Carcinoma | ACH-000546", - "Head and Neck Squamous Cell Carcinoma | ACH-000548", - "Head and Neck Squamous Cell Carcinoma | ACH-000549", - "Head and Neck Squamous Cell Carcinoma | ACH-000606", - "Head and Neck Squamous Cell Carcinoma | ACH-000618", - "Head and Neck Squamous Cell Carcinoma | ACH-000619", - "Head and Neck Squamous Cell Carcinoma | ACH-000630", - "Head and Neck Squamous Cell Carcinoma | ACH-000682", - "Head and Neck Squamous Cell Carcinoma | ACH-000732", - "Head and Neck Squamous Cell Carcinoma | ACH-000735", - "Head and Neck Squamous Cell Carcinoma | ACH-000740", - "Head and Neck Squamous Cell Carcinoma | ACH-000762", - "Head and Neck Squamous Cell Carcinoma | ACH-000771", - "Head and Neck Squamous Cell Carcinoma | ACH-000778", - "Head and Neck Squamous Cell Carcinoma | ACH-000794", - "Head and Neck Squamous Cell Carcinoma | ACH-000832", - "Head and Neck Squamous Cell Carcinoma | ACH-000836", - "Head and Neck Squamous Cell Carcinoma | ACH-000846", - "Head and Neck Squamous Cell Carcinoma | ACH-001228", - "Head and Neck Squamous Cell Carcinoma | ACH-001229", - "Head and Neck Squamous Cell Carcinoma | ACH-001331", - "Head and Neck Squamous Cell Carcinoma | ACH-001332", - "Head and Neck Squamous Cell Carcinoma | ACH-001346", - "Head and Neck Squamous Cell Carcinoma | ACH-001347", - "Head and Neck Squamous Cell Carcinoma | ACH-001385", - "Head and Neck Squamous Cell Carcinoma | ACH-001509", - "Head and Neck Squamous Cell Carcinoma | ACH-001510", - "Head and Neck Squamous Cell Carcinoma | ACH-001511", - "Head and Neck Squamous Cell Carcinoma | ACH-001542", - "Head and Neck Squamous Cell Carcinoma | ACH-001543", - "Head and Neck Squamous Cell Carcinoma | ACH-001625", - "Head and Neck Squamous Cell Carcinoma | ACH-001626", - "Head and Neck Squamous Cell Carcinoma | ACH-001641", - "Head and Neck Squamous Cell Carcinoma | ACH-001675", - "Head and Neck Squamous Cell Carcinoma | ACH-001690", - "Head and Neck Squamous Cell Carcinoma | ACH-001691", - "Head and Neck Squamous Cell Carcinoma | ACH-001692", - "Head and Neck Squamous Cell Carcinoma | ACH-001694", - "Head and Neck Squamous Cell Carcinoma | ACH-001695", - "Head and Neck Squamous Cell Carcinoma | ACH-001696", - "Head and Neck Squamous Cell Carcinoma | ACH-001698", - "Head and Neck Squamous Cell Carcinoma | ACH-001699", - "Head and Neck Squamous Cell Carcinoma | ACH-001701", - "Head and Neck Squamous Cell Carcinoma | ACH-002029", - "Head and Neck Squamous Cell Carcinoma | ACH-002030", - "Head and Neck Squamous Cell Carcinoma | ACH-002042", - "Head and Neck Squamous Cell Carcinoma | ACH-002043", - "Head and Neck Squamous Cell Carcinoma | ACH-002044", - "Head and Neck Squamous Cell Carcinoma | ACH-002045", - "Head and Neck Squamous Cell Carcinoma | ACH-002212", - "Head and Neck Squamous Cell Carcinoma | ACH-002249", 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ACH-002041" - ], - "type": "scattergl", - "x": { - "bdata": "lJeCPmle0j5yIm++pZYkvzOQir9QapY93yx1vQ==", - "dtype": "f4" - }, - "y": { - "bdata": "6zIaP/PbSz6CgZQ/qry2PzWAwD/Qnzk/PPqKPw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000182", - "ACH-000377", - "ACH-001862", - "ACH-002023" - ], - "hoverinfo": "text", - "marker": { - "color": "#E48F72", - "size": 7 - }, - "mode": "markers", - "name": "Ampullary Carcinoma", - "text": [ - "Ampullary Carcinoma | ACH-000182", - "Ampullary Carcinoma | ACH-000377", - "Ampullary Carcinoma | ACH-001862", - "Ampullary Carcinoma | ACH-002023" - ], - "type": "scattergl", - "x": { - "bdata": "Tog0wNMTNcAYF4G+U+kxPw==", - "dtype": "f4" - }, - "y": { - "bdata": "RolKv+WfSL/Cvio/tRZVvg==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000187", - "ACH-000257", - "ACH-000290", - "ACH-000292", - "ACH-000355", - "ACH-000431", - "ACH-000514", - "ACH-000515", - "ACH-000525", - "ACH-000559", - "ACH-000639", - "ACH-000695", - "ACH-000698", - 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Neuroendocrine Tumor | ACH-000767", - "Lung Neuroendocrine Tumor | ACH-000775", - "Lung Neuroendocrine Tumor | ACH-000790", - "Lung Neuroendocrine Tumor | ACH-000800", - "Lung Neuroendocrine Tumor | ACH-000866", - "Lung Neuroendocrine Tumor | ACH-000871", - "Lung Neuroendocrine Tumor | ACH-000890", - "Lung Neuroendocrine Tumor | ACH-000912", - "Lung Neuroendocrine Tumor | ACH-001386", - "Lung Neuroendocrine Tumor | ACH-001549", - "Lung Neuroendocrine Tumor | ACH-002051", - "Lung Neuroendocrine Tumor | ACH-002052", - "Lung Neuroendocrine Tumor | ACH-002077" - ], - "type": "scattergl", - "x": { - "bdata": "3m1kP4zVBj6sLEI/fS/AP2PatT/JI6g+q9CtvTreUD9fDzQ/in4mvhq+wj9VFl++CkmMPyB9Zj8Q/KO8w25RP4C3hj+sexY/RULEP2nWtT+g6la+a95YPw0usT4dwec+5TEDv7SulD1U/qa+", - "dtype": "f4" - }, - "y": { - "bdata": "DZuUvVxOKz/C8pe9cvQdv4j1NL+oEgE/Q7pHP/2UXL7UV668RrEpP+6yfL9pV2w//lQEv1iEHr6kjVQ/0w5WvmdsOr7vonA+eb5Pv8YnGL87pWs/CZ26vc0AnD5/DLw+RFSlP0p1ND+a8n4/", - "dtype": "f4" - } - }, - { - "customdata": [ - 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"Endometrial Carcinoma | ACH-000941", - "Endometrial Carcinoma | ACH-000946", - "Endometrial Carcinoma | ACH-000961", - "Endometrial Carcinoma | ACH-000965", - "Endometrial Carcinoma | ACH-000972", - "Endometrial Carcinoma | ACH-000974", - "Endometrial Carcinoma | ACH-000978", - "Endometrial Carcinoma | ACH-000984", - "Endometrial Carcinoma | ACH-000988", - "Endometrial Carcinoma | ACH-000993", - "Endometrial Carcinoma | ACH-000994", - "Endometrial Carcinoma | ACH-000996", - "Endometrial Carcinoma | ACH-001495", - "Endometrial Carcinoma | ACH-001517", - "Endometrial Carcinoma | ACH-001518", - "Endometrial Carcinoma | ACH-002026", - "Endometrial Carcinoma | ACH-002027", - "Endometrial Carcinoma | ACH-002046" - ], - "type": "scattergl", - "x": { - "bdata": "cZ9Yvyr4Ub/BCrI8bRaavUkyCz4LzWq+KC4xwBdZVz9w9Zc/Nx2TPzhpEL9AdmY/UAhgP5bI2T8D7jjARYqNP36mLz4JTd6+p3EIPY367z1uRTPADhwCPfRctr6uIIy/dJA9wDk8kT+qNws/YpqqvQ==", - "dtype": "f4" - }, - "y": { - "bdata": 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ACH-001538", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001673", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001834", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001835", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001836", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001838", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001839", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001841", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001842", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001843", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001844", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001848", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001849", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001852", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001856", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001857", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001858", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001863", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001864", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001959", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001960", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001997", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-002647" - ], - "type": "scattergl", - "x": { - "bdata": "U1Q3wLMgOMCBbzPAnjI3PAuiPj5MGIQ+xQ2XPhBjqD+QXznAHoszwNrONsA9eTzA04g2wLWMMsAwmYW9HYc2wOTsM8DqzTPAcy00wG36rD/h/NM+/sUlP416HT9aiDrAPE6aPoBB4z9EmDQ/Xao3wMigIT8=", - "dtype": "f4" - }, - "y": { - "bdata": "1OMjvwzWEb/Dsk+/VqEQP75c6D6azvw+7UD6PonjNL/Dyg6/6lxTv/oANL/tkLy+eeQsv9+HbL+f8lg/Ipsvv84HVr8/ele/y+RIv37HGL+odoc+MQwHPmNVMb4mSwO/toywPZmofr+JoEs+fTckv6tlUj4=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000217", - "ACH-000221", - "ACH-000316", - "ACH-000361", - 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Carcinoma | ACH-000493", - "Hepatocellular Carcinoma | ACH-000537", - "Hepatocellular Carcinoma | ACH-000577", - "Hepatocellular Carcinoma | ACH-000620", - "Hepatocellular Carcinoma | ACH-000734", - "Hepatocellular Carcinoma | ACH-000848", - "Hepatocellular Carcinoma | ACH-001318", - "Hepatocellular Carcinoma | ACH-002523" - ], - "type": "scattergl", - "x": { - "bdata": "1flGP2aUzT8A3D0+QYqePnKVfr+S/N2+2iASP708kLxdxlw/JmSSvoa0v74M6og/hF/1vhMvmj24PgI/0JmOv/GlIT/TUa0/aiOoP0Q2PD8Wcfc+", - "dtype": "f4" - }, - "y": { - "bdata": "5fBDvdbs/75YxEk/5K8BP0+P6T8joJQ/phWDPhXoHj/lpgq9bwBuP6Cnfz8yhFe+esWQP+rvOT+Vz8o9vDzgP1KS2r3powW/Vf4Jv8nBhT1xP+E+", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000305", - "ACH-000318", - "ACH-000408", - "ACH-000452", - "ACH-000488", - "ACH-000544", - "ACH-000561", - "ACH-000605", - "ACH-000637", - "ACH-000647", - "ACH-000693", - "ACH-000694", - "ACH-000717", - "ACH-000777", - "ACH-000784", - "ACH-000809", - "ACH-000823", - "ACH-000824", - "ACH-000855", - "ACH-000865", - "ACH-000873", - "ACH-000917", - "ACH-002243", - "ACH-002263" - ], - "hoverinfo": "text", - "marker": { - "color": "#222A2A", - "size": 7 - }, - "mode": "markers", - "name": "Esophageal Squamous Cell Carcinoma", - "text": [ - "Esophageal Squamous Cell Carcinoma | ACH-000305", - "Esophageal Squamous Cell Carcinoma | ACH-000318", - "Esophageal Squamous Cell Carcinoma | ACH-000408", - "Esophageal Squamous Cell Carcinoma | ACH-000452", - "Esophageal Squamous Cell Carcinoma | ACH-000488", - "Esophageal Squamous Cell Carcinoma | ACH-000544", - "Esophageal Squamous Cell Carcinoma | ACH-000561", - "Esophageal Squamous Cell Carcinoma | ACH-000605", - "Esophageal Squamous Cell Carcinoma | ACH-000637", - "Esophageal Squamous Cell Carcinoma | ACH-000647", - "Esophageal Squamous Cell Carcinoma | ACH-000693", - "Esophageal Squamous Cell Carcinoma | ACH-000694", - "Esophageal Squamous Cell Carcinoma | ACH-000717", - "Esophageal Squamous Cell Carcinoma | ACH-000777", - "Esophageal Squamous Cell Carcinoma | ACH-000784", - "Esophageal Squamous Cell Carcinoma | ACH-000809", - "Esophageal Squamous Cell Carcinoma | ACH-000823", - "Esophageal Squamous Cell Carcinoma | ACH-000824", - "Esophageal Squamous Cell Carcinoma | ACH-000855", - "Esophageal Squamous Cell Carcinoma | ACH-000865", - "Esophageal Squamous Cell Carcinoma | ACH-000873", - "Esophageal Squamous Cell Carcinoma | ACH-000917", - "Esophageal Squamous Cell Carcinoma | ACH-002243", - "Esophageal Squamous Cell Carcinoma | ACH-002263" - ], - "type": "scattergl", - "x": { - "bdata": "x7SYPmRgSD/+Lkg/oEaDPWYX5j+BEVo/IdY0PzCP9T7loQs+Kl/yvX7O5D9Bm2Q/ZBhePbaxTj/awoo/nHWkPxsHkD8UhhM/GumGP/T6dz/1wII/sGKAP2Z+ND+1dVo/", - "dtype": "f4" - }, - "y": { - "bdata": "Y7+4PmXuBjy9vJY7DGEQP9EbXb97m7a9n6fOvKPdoT67sis/y981P3SdLL/K3Ri+B4kZPxjeYr55squ+NNQJv+I1jr7edp0+lMbAvQZBKr1oC1m+FjKcvs1uVz7YYXW+", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000456" - ], - "hoverinfo": "text", - "marker": { - "color": "#B68100", - "size": 7 - }, - "mode": "markers", - "name": "Poorly Differentiated Thyroid Cancer", - "text": [ - "Poorly Differentiated Thyroid Cancer | ACH-000456" - ], - "type": "scattergl", - "x": { - "bdata": "MEOfPw==", - "dtype": "f4" - }, - "y": { - "bdata": "/0ajvg==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000487" - ], - "hoverinfo": "text", - "marker": { - "color": "#750D86", - "size": 7 - }, - "mode": "markers", - "name": "Myelodysplastic Syndromes", - "text": [ - "Myelodysplastic Syndromes | ACH-000487" - ], - "type": "scattergl", - "x": { - "bdata": "cKv3Pw==", - "dtype": "f4" - }, - "y": { - "bdata": "DYOcvw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000490", - "ACH-000556", - "ACH-001333", - "ACH-001334", - "ACH-001335", - "ACH-001336", - "ACH-001360", - "ACH-001402", - "ACH-001451", - "ACH-001515", - "ACH-001651", - "ACH-001652", - "ACH-002020" - ], - "hoverinfo": "text", - "marker": { - "color": "#EB663B", - "size": 7 - }, - "mode": "markers", - "name": "Cervical Squamous Cell Carcinoma", - "text": [ - "Cervical Squamous Cell Carcinoma | ACH-000490", - "Cervical Squamous Cell Carcinoma | ACH-000556", - "Cervical Squamous Cell Carcinoma | ACH-001333", - "Cervical Squamous Cell Carcinoma | ACH-001334", - "Cervical Squamous Cell Carcinoma | ACH-001335", - "Cervical Squamous Cell Carcinoma | ACH-001336", - "Cervical Squamous Cell Carcinoma | ACH-001360", - "Cervical Squamous Cell Carcinoma | ACH-001402", - "Cervical Squamous Cell Carcinoma | ACH-001451", - "Cervical Squamous Cell Carcinoma | ACH-001515", - "Cervical Squamous Cell Carcinoma | ACH-001651", - "Cervical Squamous Cell Carcinoma | ACH-001652", - "Cervical Squamous Cell Carcinoma | ACH-002020" - ], - "type": "scattergl", - "x": { - "bdata": "Ty0rPxIomj6HkXQ/+/HPPzAVUT9fqwM/eGjOv1oqsz/tTTjAXfVePuvXrb/gReo+8WgGPA==", - "dtype": "f4" - }, - "y": { - "bdata": "KFORPjjf1j6WjKq9/UNSv1GltTymq44+kygWQK7Y3b46hiK/kz8XP1j7AkBUyqc+qdcWPw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000516" - ], - "hoverinfo": "text", - "marker": { - "color": "#511CFB", - "size": 7 - }, - "mode": "markers", - "name": "Chondrosarcoma", - "text": [ - "Chondrosarcoma | ACH-000516" - ], - "type": "scattergl", - "x": { - "bdata": "TGNovw==", - "dtype": "f4" - }, - "y": { - "bdata": "KXTYPw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000624", - "ACH-000725", - "ACH-000859" - ], - "hoverinfo": "text", - "marker": { - "color": "#00A08B", - "size": 7 - }, - "mode": "markers", - "name": "Breast Ductal Carcinoma In Situ", - "text": [ - "Breast Ductal Carcinoma In Situ | ACH-000624", - "Breast Ductal Carcinoma In Situ | ACH-000725", - "Breast Ductal Carcinoma In Situ | ACH-000859" - ], - "type": "scattergl", - "x": { - "bdata": "EXLqPuNdPr8BHNK6", - "dtype": "f4" - }, - "y": { - "bdata": "x617vRUBrD+J/Ak/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000671", - "ACH-000739" - ], - "hoverinfo": "text", - "marker": { - "color": "#FB00D1", - "size": 7 - }, - "mode": "markers", - "name": "Hepatoblastoma", - "text": [ - "Hepatoblastoma | ACH-000671", - "Hepatoblastoma | ACH-000739" - ], - "type": "scattergl", - "x": { - "bdata": "R96vP/gruz4=", - "dtype": "f4" - }, - "y": { - "bdata": "UHgBvwhVpj4=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000702", - "ACH-000754", - "ACH-001685" - ], - "hoverinfo": "text", - "marker": { - "color": "#FC0080", - "size": 7 - }, - "mode": "markers", - "name": "Hodgkin Lymphoma", - "text": [ - "Hodgkin Lymphoma | ACH-000702", - "Hodgkin Lymphoma | ACH-000754", - "Hodgkin Lymphoma | ACH-001685" - ], - "type": "scattergl", - "x": { - "bdata": "ArigPoiJHD+My4a7", - "dtype": "f4" - }, - "y": { - "bdata": "7FBdPiHBDj4pHxE/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000716", - "ACH-000903", - "ACH-001528" - ], - "hoverinfo": "text", - "marker": { - "color": "#B2828D", - "size": 7 - }, - "mode": "markers", - "name": "Well-Differentiated Thyroid Cancer", - "text": [ - "Well-Differentiated Thyroid Cancer | ACH-000716", - "Well-Differentiated Thyroid Cancer | ACH-000903", - "Well-Differentiated Thyroid Cancer | ACH-001528" - ], - "type": "scattergl", - "x": { - "bdata": "NtS4Px7eSz/lOMQ/", - "dtype": "f4" - }, - "y": { - "bdata": "ZkMVv0JEtDx8GVG/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000835", - "ACH-001164" - ], - "hoverinfo": "text", - "marker": { - "color": "#6C7C32", - "size": 7 - }, - "mode": "markers", - "name": "Undifferentiated Pleomorphic Sarcoma/Malignant Fibrous Histiocytoma/High-Grade Spindle Cell Sarcoma", - "text": [ - "Undifferentiated Pleomorphic Sarcoma/Malignant Fibrous Histiocytoma/High-Grade Spindle Cell Sarcoma | ACH-000835", - "Undifferentiated Pleomorphic Sarcoma/Malignant Fibrous Histiocytoma/High-Grade Spindle Cell Sarcoma | ACH-001164" - ], - "type": "scattergl", - "x": { - "bdata": "vVFnP9XHgD8=", - "dtype": "f4" - }, - "y": { - "bdata": "49RJvTVghr4=", - "dtype": "f4" - } - }, - { - "customdata": [ - 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"markers", - "name": "Squamous Cell Carcinoma of the Vulva/Vagina", - "text": [ - "Squamous Cell Carcinoma of the Vulva/Vagina | ACH-001400" - ], - "type": "scattergl", - "x": { - "bdata": "mP0/vg==", - "dtype": "f4" - }, - "y": { - "bdata": "CxVCPw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-001401" - ], - "hoverinfo": "text", - "marker": { - "color": "#636EFA", - "size": 7 - }, - "mode": "markers", - "name": "Adrenocortical Carcinoma", - "text": [ - "Adrenocortical Carcinoma | ACH-001401" - ], - "type": "scattergl", - "x": { - "bdata": "nE+zPg==", - "dtype": "f4" - }, - "y": { - "bdata": "DyzHPg==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-001433", - "ACH-001702" - ], - "hoverinfo": "text", - "marker": { - "color": "#EF553B", - "size": 7 - }, - "mode": "markers", - "name": "Epithelioid Sarcoma", - "text": [ - "Epithelioid Sarcoma | ACH-001433", - "Epithelioid Sarcoma | ACH-001702" - ], - "type": "scattergl", - "x": { - "bdata": "NTdaPqGMlz4=", - "dtype": 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ACH-000005", - "Acute Myeloid Leukemia | ACH-000045", - "Acute Myeloid Leukemia | ACH-000113", - "Acute Myeloid Leukemia | ACH-000146", - "Acute Myeloid Leukemia | ACH-000168", - "Acute Myeloid Leukemia | ACH-000190", - "Acute Myeloid Leukemia | ACH-000195", - "Acute Myeloid Leukemia | ACH-000263", - "Acute Myeloid Leukemia | ACH-000294", - "Acute Myeloid Leukemia | ACH-000336", - "Acute Myeloid Leukemia | ACH-000362", - "Acute Myeloid Leukemia | ACH-000387", - "Acute Myeloid Leukemia | ACH-000406", - "Acute Myeloid Leukemia | ACH-000498", - "Acute Myeloid Leukemia | ACH-000557", - "Acute Myeloid Leukemia | ACH-000602", - "Acute Myeloid Leukemia | ACH-000770", - "Acute Myeloid Leukemia | ACH-001036", - "Acute Myeloid Leukemia | ACH-001129", - "Acute Myeloid Leukemia | ACH-001574", - "Acute Myeloid Leukemia | ACH-001577", - "Acute Myeloid Leukemia | ACH-001613", - "Acute Myeloid Leukemia | ACH-001618", - "Acute Myeloid Leukemia | ACH-001647", - "Acute Myeloid Leukemia | ACH-001656" - ], 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"ACH-000985", - "ACH-000986", - "ACH-000991", - "ACH-000997", - "ACH-001039", - "ACH-001061", - "ACH-001081", - "ACH-001345", - "ACH-001399", - "ACH-001454", - "ACH-001458", - "ACH-001459", - "ACH-001460", - "ACH-001461", - "ACH-001786", - "ACH-002024", - "ACH-002025", - "ACH-002233", - "ACH-002535", - "ACH-002654", - "ACH-002659", - "ACH-002660", - "ACH-002662", - "ACH-002664", - "ACH-002669" - ], - "hoverinfo": "text", - "marker": { - "color": "#00CC96", - "size": 7 - }, - "mode": "markers", - "name": "Colorectal Adenocarcinoma", - "text": [ - "Colorectal Adenocarcinoma | ACH-000007", - "Colorectal Adenocarcinoma | ACH-000009", - "Colorectal Adenocarcinoma | ACH-000202", - "Colorectal Adenocarcinoma | ACH-000249", - "Colorectal Adenocarcinoma | ACH-000252", - "Colorectal Adenocarcinoma | ACH-000253", - "Colorectal Adenocarcinoma | ACH-000286", - "Colorectal Adenocarcinoma | ACH-000296", - "Colorectal Adenocarcinoma | ACH-000350", - "Colorectal Adenocarcinoma | ACH-000381", - "Colorectal Adenocarcinoma | ACH-000403", - "Colorectal Adenocarcinoma | ACH-000421", - "Colorectal Adenocarcinoma | ACH-000467", - "Colorectal Adenocarcinoma | ACH-000470", - "Colorectal Adenocarcinoma | ACH-000489", - "Colorectal Adenocarcinoma | ACH-000491", - "Colorectal Adenocarcinoma | ACH-000501", - "Colorectal Adenocarcinoma | ACH-000532", - "Colorectal Adenocarcinoma | ACH-000552", - "Colorectal Adenocarcinoma | ACH-000565", - "Colorectal Adenocarcinoma | ACH-000651", - "Colorectal Adenocarcinoma | ACH-000683", - "Colorectal Adenocarcinoma | ACH-000722", - "Colorectal Adenocarcinoma | ACH-000798", - "Colorectal Adenocarcinoma | ACH-000820", - "Colorectal Adenocarcinoma | ACH-000926", - "Colorectal Adenocarcinoma | ACH-000935", - "Colorectal Adenocarcinoma | ACH-000943", - "Colorectal Adenocarcinoma | ACH-000950", - "Colorectal Adenocarcinoma | ACH-000957", - "Colorectal Adenocarcinoma | ACH-000958", - "Colorectal Adenocarcinoma | ACH-000959", - "Colorectal Adenocarcinoma | ACH-000963", - "Colorectal Adenocarcinoma | ACH-000969", - "Colorectal Adenocarcinoma | ACH-000970", - "Colorectal Adenocarcinoma | ACH-000971", - "Colorectal Adenocarcinoma | ACH-000985", - "Colorectal Adenocarcinoma | ACH-000986", - "Colorectal Adenocarcinoma | ACH-000991", - "Colorectal Adenocarcinoma | ACH-000997", - "Colorectal Adenocarcinoma | ACH-001039", - "Colorectal Adenocarcinoma | ACH-001061", - "Colorectal Adenocarcinoma | ACH-001081", - "Colorectal Adenocarcinoma | ACH-001345", - "Colorectal Adenocarcinoma | ACH-001399", - "Colorectal Adenocarcinoma | ACH-001454", - "Colorectal Adenocarcinoma | ACH-001458", - "Colorectal Adenocarcinoma | ACH-001459", - "Colorectal Adenocarcinoma | ACH-001460", - "Colorectal Adenocarcinoma | ACH-001461", - "Colorectal Adenocarcinoma | ACH-001786", - "Colorectal Adenocarcinoma | ACH-002024", - "Colorectal Adenocarcinoma | ACH-002025", - "Colorectal Adenocarcinoma | ACH-002233", - "Colorectal Adenocarcinoma | ACH-002535", - "Colorectal Adenocarcinoma | ACH-002654", - "Colorectal Adenocarcinoma | ACH-002659", - "Colorectal Adenocarcinoma | ACH-002660", - "Colorectal Adenocarcinoma | ACH-002662", - "Colorectal Adenocarcinoma | ACH-002664", - "Colorectal Adenocarcinoma | ACH-002669" - ], - "type": "scattergl", - "x": { - "bdata": "Pj5MQJQn5z9ZM9M/tU/1wMHqRz71BYw/X7mpP51M4D8Z+xHA2fcoQMaEnb9Y0iS/XVH1wFC11L1RFoY/SDaFv+sez7whYoA/WRrNP5Fclz9S0C9AjWtrvuiJ2T80Y/XANglePyph9cBGXvXAThf1wIQ1WkB2GVtAzP4CQOYtI0CZ6J2/9V/1wI0s0T89tcs/SkVZP2pK9cAc7Jc/F0w0QA0yMkAr32BAnFL1wJxoCEAPLYM/tnarvzsJXD+il94/UiJFQLGhwr9BTPY+6/6gP7ZF9cB/R6M+pusxPxJGKb00gzpA/KuXP+1cKEDljipAPo9FQA==", - "dtype": "f4" - }, - "y": { - "bdata": 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Carcinoma", - "text": [ - "Bladder Urothelial Carcinoma | ACH-000011", - "Bladder Urothelial Carcinoma | ACH-000018", - "Bladder Urothelial Carcinoma | ACH-000026", - "Bladder Urothelial Carcinoma | ACH-000127", - "Bladder Urothelial Carcinoma | ACH-000142", - "Bladder Urothelial Carcinoma | ACH-000242", - "Bladder Urothelial Carcinoma | ACH-000396", - "Bladder Urothelial Carcinoma | ACH-000473", - "Bladder Urothelial Carcinoma | ACH-000486", - "Bladder Urothelial Carcinoma | ACH-000522", - "Bladder Urothelial Carcinoma | ACH-000545", - "Bladder Urothelial Carcinoma | ACH-000547", - "Bladder Urothelial Carcinoma | ACH-000593", - "Bladder Urothelial Carcinoma | ACH-000720", - "Bladder Urothelial Carcinoma | ACH-000724", - "Bladder Urothelial Carcinoma | ACH-000741", - "Bladder Urothelial Carcinoma | ACH-000753", - "Bladder Urothelial Carcinoma | ACH-000802", - "Bladder Urothelial Carcinoma | ACH-000834", - "Bladder Urothelial Carcinoma | ACH-000862", - "Bladder Urothelial Carcinoma | ACH-000896", - "Bladder Urothelial Carcinoma | ACH-000905", - "Bladder Urothelial Carcinoma | ACH-001183", - "Bladder Urothelial Carcinoma | ACH-001407", - "Bladder Urothelial Carcinoma | ACH-001409", - "Bladder Urothelial Carcinoma | ACH-001412", - "Bladder Urothelial Carcinoma | ACH-001413", - "Bladder Urothelial Carcinoma | ACH-001414", - "Bladder Urothelial Carcinoma | ACH-001415", - "Bladder Urothelial Carcinoma | ACH-001416" - ], - "type": "scattergl", - "x": { - "bdata": "0rv5PzG3yj+vyNg/FhtpQDqeCUAYkt4/6UXbvcBk9cADpklACDL1wFdV9cDAIwVApjTgP3fmAkBPV3O/cGzOP4y1VEBUPlBA7EJTQAGJ9cC0txFATzMbQLZZ9cAoOPXA90b1wNRY9cBkMvXAuFn1wD6N9cAQW/XA", - "dtype": "f4" - }, - "y": { - "bdata": "hcSLP9+nzD+pwsA9NZ2gu0SA2T4BWpo+kxOOP+H0br6XAgU/ZhR0vo+Jbb7meFQ/aJesP52y6T+q1KQ/bMNAPjR9IT99XYw/u/U1Pwu8Wb5bMjM/M4kPP5r9Xb4GpW++gyhovq9/bL5X74C+jlddvs4RZb6kAHO+", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000012", - "ACH-000015", - "ACH-000021", - "ACH-000029", - "ACH-000030", - "ACH-000035", - "ACH-000143", - "ACH-000161", - "ACH-000176", - "ACH-000251", - "ACH-000261", - "ACH-000264", - "ACH-000311", - "ACH-000337", - "ACH-000339", - "ACH-000343", - "ACH-000378", - "ACH-000390", - "ACH-000395", - "ACH-000414", - "ACH-000416", - "ACH-000434", - "ACH-000438", - "ACH-000442", - "ACH-000444", - "ACH-000448", - "ACH-000454", - "ACH-000463", - "ACH-000481", - "ACH-000496", - "ACH-000510", - "ACH-000511", - "ACH-000521", - "ACH-000528", - "ACH-000562", - "ACH-000563", - "ACH-000585", - "ACH-000587", - "ACH-000589", - "ACH-000596", - "ACH-000627", - "ACH-000638", - "ACH-000662", - "ACH-000665", - "ACH-000666", - "ACH-000667", - "ACH-000672", - "ACH-000677", - "ACH-000681", - "ACH-000700", - "ACH-000706", - "ACH-000718", - "ACH-000747", - "ACH-000757", - "ACH-000766", - "ACH-000769", - "ACH-000774", - "ACH-000781", - "ACH-000785", - "ACH-000787", - "ACH-000791", - "ACH-000826", - "ACH-000837", - "ACH-000840", - "ACH-000841", - "ACH-000843", - "ACH-000845", - "ACH-000851", - "ACH-000853", - "ACH-000858", - "ACH-000860", - "ACH-000861", - "ACH-000867", - "ACH-000869", - "ACH-000872", - "ACH-000878", - "ACH-000886", - "ACH-000888", - "ACH-000894", - "ACH-000900", - "ACH-000901", - "ACH-000916", - "ACH-000921", - "ACH-000924", - "ACH-000929", - "ACH-000945", - "ACH-000975", - "ACH-000980", - "ACH-001075", - "ACH-001137", - "ACH-001233", - "ACH-002035", - "ACH-002156", - "ACH-002522", - "ACH-002526", - "ACH-002531", - "ACH-002650", - "ACH-003012" - ], - "hoverinfo": "text", - "marker": { - "color": "#FFA15A", - "size": 7 - }, - "mode": "markers", - "name": "Non-Small Cell Lung Cancer", - "text": [ - "Non-Small Cell Lung Cancer | ACH-000012", - "Non-Small Cell Lung Cancer | ACH-000015", - "Non-Small Cell Lung Cancer | ACH-000021", - "Non-Small Cell Lung Cancer | ACH-000029", - "Non-Small Cell Lung Cancer | ACH-000030", - "Non-Small Cell Lung Cancer | ACH-000035", - "Non-Small Cell Lung Cancer | ACH-000143", - "Non-Small Cell Lung Cancer | ACH-000161", - "Non-Small Cell Lung Cancer | ACH-000176", - "Non-Small Cell Lung Cancer | ACH-000251", - "Non-Small Cell Lung Cancer | ACH-000261", - "Non-Small Cell Lung Cancer | ACH-000264", - "Non-Small Cell Lung Cancer | ACH-000311", - "Non-Small Cell Lung Cancer | ACH-000337", - "Non-Small Cell Lung Cancer | ACH-000339", - "Non-Small Cell Lung Cancer | ACH-000343", - "Non-Small Cell Lung Cancer | ACH-000378", - "Non-Small Cell Lung Cancer | ACH-000390", - "Non-Small Cell Lung Cancer | ACH-000395", - "Non-Small Cell Lung Cancer | ACH-000414", - "Non-Small Cell Lung Cancer | ACH-000416", - "Non-Small Cell Lung Cancer | ACH-000434", - "Non-Small Cell Lung Cancer | ACH-000438", - "Non-Small Cell Lung Cancer | ACH-000442", - "Non-Small Cell Lung Cancer | ACH-000444", - "Non-Small Cell Lung Cancer | ACH-000448", - "Non-Small Cell Lung Cancer | ACH-000454", - "Non-Small Cell Lung Cancer | ACH-000463", - "Non-Small Cell Lung Cancer | ACH-000481", - "Non-Small Cell Lung Cancer | ACH-000496", - "Non-Small Cell Lung Cancer | ACH-000510", - "Non-Small Cell Lung Cancer | ACH-000511", - "Non-Small Cell Lung Cancer | ACH-000521", - "Non-Small Cell Lung Cancer | ACH-000528", - "Non-Small Cell Lung Cancer | ACH-000562", - "Non-Small Cell Lung Cancer | ACH-000563", - "Non-Small Cell Lung Cancer | ACH-000585", - "Non-Small Cell Lung Cancer | ACH-000587", - "Non-Small Cell Lung Cancer | ACH-000589", - "Non-Small Cell Lung Cancer | ACH-000596", - "Non-Small Cell Lung Cancer | ACH-000627", - "Non-Small Cell Lung Cancer | ACH-000638", - "Non-Small Cell Lung Cancer | ACH-000662", - "Non-Small Cell Lung Cancer | ACH-000665", - "Non-Small Cell Lung Cancer | ACH-000666", - "Non-Small Cell Lung Cancer | ACH-000667", - "Non-Small Cell Lung Cancer | ACH-000672", - "Non-Small Cell Lung Cancer | ACH-000677", - "Non-Small Cell Lung Cancer | ACH-000681", - "Non-Small Cell Lung Cancer | ACH-000700", - "Non-Small Cell Lung Cancer | ACH-000706", - "Non-Small Cell Lung Cancer | ACH-000718", - "Non-Small Cell Lung Cancer | ACH-000747", - "Non-Small Cell Lung Cancer | ACH-000757", - "Non-Small Cell Lung Cancer | ACH-000766", - "Non-Small Cell Lung Cancer | ACH-000769", - "Non-Small Cell Lung Cancer | ACH-000774", - "Non-Small Cell Lung Cancer | ACH-000781", - "Non-Small Cell Lung Cancer | ACH-000785", - "Non-Small Cell Lung Cancer | ACH-000787", - "Non-Small Cell Lung Cancer | ACH-000791", - "Non-Small Cell Lung Cancer | ACH-000826", - "Non-Small Cell Lung Cancer | ACH-000837", - "Non-Small Cell Lung Cancer | ACH-000840", - "Non-Small Cell Lung Cancer | ACH-000841", - "Non-Small Cell Lung Cancer | ACH-000843", - "Non-Small Cell Lung Cancer | ACH-000845", - "Non-Small Cell Lung Cancer | ACH-000851", - "Non-Small Cell Lung Cancer | ACH-000853", - "Non-Small Cell Lung Cancer | ACH-000858", - "Non-Small Cell Lung Cancer | ACH-000860", - "Non-Small Cell Lung Cancer | ACH-000861", - "Non-Small Cell Lung Cancer | ACH-000867", - "Non-Small Cell Lung Cancer | ACH-000869", - "Non-Small Cell Lung Cancer | ACH-000872", - "Non-Small Cell Lung Cancer | ACH-000878", - "Non-Small Cell Lung Cancer | ACH-000886", - "Non-Small Cell Lung Cancer | ACH-000888", - "Non-Small Cell Lung Cancer | ACH-000894", - "Non-Small Cell Lung Cancer | ACH-000900", - "Non-Small Cell Lung Cancer | ACH-000901", - "Non-Small Cell Lung Cancer | ACH-000916", - "Non-Small Cell Lung Cancer | ACH-000921", - "Non-Small Cell Lung Cancer | ACH-000924", - "Non-Small Cell Lung Cancer | ACH-000929", - "Non-Small Cell Lung Cancer | ACH-000945", - "Non-Small Cell Lung Cancer | ACH-000975", - "Non-Small Cell Lung Cancer | ACH-000980", - "Non-Small Cell Lung Cancer | ACH-001075", - "Non-Small Cell Lung Cancer | ACH-001137", - "Non-Small Cell Lung Cancer | ACH-001233", - "Non-Small Cell Lung Cancer | ACH-002035", - "Non-Small Cell Lung Cancer | ACH-002156", - "Non-Small Cell Lung Cancer | ACH-002522", - "Non-Small Cell Lung Cancer | ACH-002526", - "Non-Small Cell Lung Cancer | ACH-002531", - "Non-Small Cell Lung Cancer | ACH-002650", - "Non-Small Cell Lung Cancer | ACH-003012" - ], - "type": "scattergl", - "x": { - "bdata": "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", - "dtype": "f4" - }, - "y": { - "bdata": 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"ACH-000827", - "ACH-000881", - "ACH-000882", - "ACH-000884", - "ACH-000899", - "ACH-000915", - "ACH-000968", - "ACH-001041", - "ACH-001190", - "ACH-001239", - "ACH-001522", - "ACH-001563", - "ACH-001566", - "ACH-001567", - "ACH-001568", - "ACH-001570", - "ACH-001645", - "ACH-001970", - "ACH-001972", - "ACH-001973", - "ACH-001975", - "ACH-001982", - "ACH-001986", - "ACH-001990", - "ACH-002001", - "ACH-002002", - "ACH-002003", - "ACH-002004", - "ACH-002005", - "ACH-002084", - "ACH-002143", - "ACH-002458", - "ACH-002460", - "ACH-002461", - "ACH-002508", - "ACH-002510", - "ACH-002511", - "ACH-002512", - "ACH-002847", - "ACH-002928" - ], - "hoverinfo": "text", - "marker": { - "color": "#19D3F3", - "size": 7 - }, - "mode": "markers", - "name": "Melanoma", - "text": [ - "Melanoma | ACH-000014", - "Melanoma | ACH-000219", - "Melanoma | ACH-000274", - "Melanoma | ACH-000304", - "Melanoma | ACH-000322", - "Melanoma | ACH-000348", - "Melanoma | ACH-000401", - "Melanoma | ACH-000404", - "Melanoma | ACH-000425", - "Melanoma | ACH-000441", - "Melanoma | ACH-000450", - "Melanoma | ACH-000458", - "Melanoma | ACH-000477", - "Melanoma | ACH-000550", - "Melanoma | ACH-000579", - "Melanoma | ACH-000580", - "Melanoma | ACH-000614", - "Melanoma | ACH-000632", - "Melanoma | ACH-000661", - "Melanoma | ACH-000765", - "Melanoma | ACH-000788", - "Melanoma | ACH-000799", - "Melanoma | ACH-000801", - "Melanoma | ACH-000805", - "Melanoma | ACH-000810", - "Melanoma | ACH-000822", - "Melanoma | ACH-000827", - "Melanoma | ACH-000881", - "Melanoma | ACH-000882", - "Melanoma | ACH-000884", - "Melanoma | ACH-000899", - "Melanoma | ACH-000915", - "Melanoma | ACH-000968", - "Melanoma | ACH-001041", - "Melanoma | ACH-001190", - "Melanoma | ACH-001239", - "Melanoma | ACH-001522", - "Melanoma | ACH-001563", - "Melanoma | ACH-001566", - "Melanoma | ACH-001567", - "Melanoma | ACH-001568", - "Melanoma | ACH-001570", - "Melanoma | ACH-001645", - "Melanoma | ACH-001970", - "Melanoma | ACH-001972", - "Melanoma | ACH-001973", - "Melanoma | ACH-001975", - "Melanoma | ACH-001982", - "Melanoma | ACH-001986", - "Melanoma | ACH-001990", - "Melanoma | ACH-002001", - "Melanoma | ACH-002002", - "Melanoma | ACH-002003", - "Melanoma | ACH-002004", - "Melanoma | ACH-002005", - "Melanoma | ACH-002084", - "Melanoma | ACH-002143", - "Melanoma | ACH-002458", - "Melanoma | ACH-002460", - "Melanoma | ACH-002461", - "Melanoma | ACH-002508", - "Melanoma | ACH-002510", - "Melanoma | ACH-002511", - "Melanoma | ACH-002512", - "Melanoma | ACH-002847", - "Melanoma | ACH-002928" - ], - "type": "scattergl", - "x": { - "bdata": "RBoeQKmUpEBPvdC/Ne4KP3NkUkDyuRK/3akpQL1E9cCkbvXAlydcQDpV9cCcRfXAgTMlP8WRL7+OXfXAMmmqPmSkPEC0nyNAvmD1wJ4I4T8lkMU/5uURP7Z29cAIQc8/ouplP0KT1r8UMOo/WnVEQMDDakCWWjhAgkj1wIHxPkD0mi1AWfzrP5jKqrzmHDdAv7XuP9FI9cDfavXAgHL1wHZe9cDEVfXAjir1PPkzF0BTJvXA4Fn1wHxo9cD5ogVANGdCQCr6W0B9b2JA2LGPQHwAFEBYPfXA1utYQLMNPzuR2AvAKUcqQJo1GkCGwDE/KKZtPhI9OEBV5gTAySquP/zkrD7i4P2/", - "dtype": "f4" - }, - "y": { - "bdata": 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"ACH-001393", - "ACH-001394", - "ACH-001396", - "ACH-001419", - "ACH-001662", - "ACH-001683", - "ACH-001819", - "ACH-002179", - "ACH-002399", - "ACH-002401" - ], - "hoverinfo": "text", - "marker": { - "color": "#FF6692", - "size": 7 - }, - "mode": "markers", - "name": "Invasive Breast Carcinoma", - "text": [ - "Invasive Breast Carcinoma | ACH-000017", - "Invasive Breast Carcinoma | ACH-000019", - "Invasive Breast Carcinoma | ACH-000028", - "Invasive Breast Carcinoma | ACH-000097", - "Invasive Breast Carcinoma | ACH-000111", - "Invasive Breast Carcinoma | ACH-000147", - "Invasive Breast Carcinoma | ACH-000148", - "Invasive Breast Carcinoma | ACH-000212", - "Invasive Breast Carcinoma | ACH-000223", - "Invasive Breast Carcinoma | ACH-000248", - "Invasive Breast Carcinoma | ACH-000258", - "Invasive Breast Carcinoma | ACH-000276", - "Invasive Breast Carcinoma | ACH-000277", - "Invasive Breast Carcinoma | ACH-000288", - "Invasive Breast Carcinoma | ACH-000330", - "Invasive Breast Carcinoma | ACH-000352", - "Invasive Breast Carcinoma | ACH-000374", - "Invasive Breast Carcinoma | ACH-000554", - "Invasive Breast Carcinoma | ACH-000573", - "Invasive Breast Carcinoma | ACH-000621", - "Invasive Breast Carcinoma | ACH-000668", - "Invasive Breast Carcinoma | ACH-000699", - "Invasive Breast Carcinoma | ACH-000711", - "Invasive Breast Carcinoma | ACH-000721", - "Invasive Breast Carcinoma | ACH-000768", - "Invasive Breast Carcinoma | ACH-000783", - "Invasive Breast Carcinoma | ACH-000849", - "Invasive Breast Carcinoma | ACH-000856", - "Invasive Breast Carcinoma | ACH-000876", - "Invasive Breast Carcinoma | ACH-000910", - "Invasive Breast Carcinoma | ACH-000934", - "Invasive Breast Carcinoma | ACH-001065", - "Invasive Breast Carcinoma | ACH-001388", - "Invasive Breast Carcinoma | ACH-001389", - "Invasive Breast Carcinoma | ACH-001390", - "Invasive Breast Carcinoma | ACH-001391", - "Invasive Breast Carcinoma | ACH-001392", - "Invasive Breast Carcinoma | ACH-001393", - "Invasive Breast Carcinoma | ACH-001394", - "Invasive Breast Carcinoma | ACH-001396", - "Invasive Breast Carcinoma | ACH-001419", - "Invasive Breast Carcinoma | ACH-001662", - "Invasive Breast Carcinoma | ACH-001683", - "Invasive Breast Carcinoma | ACH-001819", - "Invasive Breast Carcinoma | ACH-002179", - "Invasive Breast Carcinoma | ACH-002399", - "Invasive Breast Carcinoma | ACH-002401" - ], - "type": "scattergl", - "x": { - "bdata": "hOtRPmIYlT8ZFEJA/CokP62K0T9n0/c/fZToPpTtwD/IHnS/hZaxP3A4P75uMuK9sjkuvjxB1D8x9Rk/8wMDPwPIxT9ykDbAUauiP/vWGsDh95K+/ajHv/y+AUDQuj1AjB3NP3DHEMB6zShAtN+SQAUJ9r9tMfU/sjqAwJQDdUC2glm/2Vf1wHw1B0AiRLa/4V71wHBa9cDuY/XAb4b1wCUeYD8cOXu+v1QZu2/stL84zZE/jMOoP8j+J0A=", - "dtype": "f4" - }, - "y": { - "bdata": "bx9mv6Y817962tO/YaGSv3qEBsDlEMO/Jy6SP1WVCD9/Yyy/JaW8v27Bdr42n0k+U5B1v0OtEEAICoW/Fke1vww4P79nMA3APro9PmqgCD5PYqi/rEjaPvOTKr9xixO/XppvPEoxrr9cYwm/45ckPkjs7r/E4RrAZoL6vxMd1r8O5K48JuBivhgkMT+RPiM+aYJovo9YbL5xWG6+CeVpvl395b6JHiC/H750v3OXdr+PSibA33rjvs3rVL0=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000022", - "ACH-000023", - "ACH-000042", - "ACH-000060", - "ACH-000085", - "ACH-000093", - "ACH-000094", - "ACH-000114", - "ACH-000118", - "ACH-000138", - "ACH-000139", - "ACH-000155", - "ACH-000164", - "ACH-000178", - "ACH-000213", - "ACH-000222", - "ACH-000235", - "ACH-000243", - "ACH-000265", - "ACH-000266", - "ACH-000281", - "ACH-000307", - "ACH-000320", - "ACH-000332", - "ACH-000354", - "ACH-000417", - "ACH-000468", - "ACH-000502", - "ACH-000517", - "ACH-000535", - "ACH-000599", - "ACH-000601", - "ACH-000652", - "ACH-001098", - "ACH-001107", - "ACH-001353", - "ACH-001375", - "ACH-001377", - "ACH-001379", - "ACH-001380", - "ACH-001382", - "ACH-001999", - "ACH-002039", - "ACH-002186", - "ACH-002672" - ], - "hoverinfo": "text", - "marker": { - "color": "#B6E880", - "size": 7 - }, - "mode": "markers", - "name": "Pancreatic Adenocarcinoma", - "text": [ - "Pancreatic Adenocarcinoma | ACH-000022", - "Pancreatic Adenocarcinoma | ACH-000023", - "Pancreatic Adenocarcinoma | ACH-000042", - "Pancreatic Adenocarcinoma | ACH-000060", - "Pancreatic Adenocarcinoma | ACH-000085", - "Pancreatic Adenocarcinoma | ACH-000093", - "Pancreatic Adenocarcinoma | ACH-000094", - "Pancreatic Adenocarcinoma | ACH-000114", - "Pancreatic Adenocarcinoma | ACH-000118", - "Pancreatic Adenocarcinoma | ACH-000138", - "Pancreatic Adenocarcinoma | ACH-000139", - "Pancreatic Adenocarcinoma | ACH-000155", - "Pancreatic Adenocarcinoma | ACH-000164", - "Pancreatic Adenocarcinoma | ACH-000178", - "Pancreatic Adenocarcinoma | ACH-000213", - "Pancreatic Adenocarcinoma | ACH-000222", - "Pancreatic Adenocarcinoma | ACH-000235", - "Pancreatic Adenocarcinoma | ACH-000243", - "Pancreatic Adenocarcinoma | ACH-000265", - "Pancreatic Adenocarcinoma | ACH-000266", - "Pancreatic Adenocarcinoma | ACH-000281", - "Pancreatic Adenocarcinoma | ACH-000307", - "Pancreatic Adenocarcinoma | ACH-000320", - "Pancreatic Adenocarcinoma | ACH-000332", - "Pancreatic Adenocarcinoma | ACH-000354", - "Pancreatic Adenocarcinoma | ACH-000417", - "Pancreatic Adenocarcinoma | ACH-000468", - "Pancreatic Adenocarcinoma | ACH-000502", - "Pancreatic Adenocarcinoma | ACH-000517", - "Pancreatic Adenocarcinoma | ACH-000535", - "Pancreatic Adenocarcinoma | ACH-000599", - "Pancreatic Adenocarcinoma | ACH-000601", - "Pancreatic Adenocarcinoma | ACH-000652", - "Pancreatic Adenocarcinoma | ACH-001098", - "Pancreatic Adenocarcinoma | ACH-001107", - "Pancreatic Adenocarcinoma | ACH-001353", - "Pancreatic Adenocarcinoma | ACH-001375", - "Pancreatic Adenocarcinoma | ACH-001377", - "Pancreatic Adenocarcinoma | ACH-001379", - "Pancreatic Adenocarcinoma | ACH-001380", - "Pancreatic Adenocarcinoma | ACH-001382", - "Pancreatic Adenocarcinoma | ACH-001999", - "Pancreatic Adenocarcinoma | ACH-002039", - "Pancreatic Adenocarcinoma | ACH-002186", - "Pancreatic Adenocarcinoma | ACH-002672" - ], - "type": "scattergl", - "x": { - "bdata": "rgS9PzeViEDK2QW/btWKvnGMTj+PEks/C91evyPCfD1oPeM/5nQHQCkfoz+O2l4+kHnIP6rUF0Drk+E/ltQFwHxQlT8vmglAhcuOQOpJt79dYQ8/Omf1wNZyPkCacLk/g4b7Pm4vNL8HjvXA29zRP1Bhab9iAo0/VTp9P4ckX0C1BeM/2iwrQLRMSz7H8lc/jKWYPmqCEkA0je8/HGAqQEo7AD9CYPXAbV/1wHVX9cByhdE/", - "dtype": "f4" - }, - "y": { - "bdata": "pdfKvqClkj/z5uG9W9/vPi8SAD/zN0k/2jmnv40UQz9/cRq/Yzp+PiUrj706yi8+l5ypvRcupT7kAay/16ytvwsz675yqTY/6N2fPtKamT5e9As/7RBuvoVaAj8fLLg+JMqfv90fMr9BqVO+ixhnPcGDPz+NOA0/HKetvzUF8b4/X/c+HDuwvmijSj+7MTg/vO4MP/2WnT4M3Rg7RPMrPhC7uz9jNXC+xO1ivgb4c76ggXg9", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000024", - "ACH-000106", - "ACH-000124", - "ACH-000167", - "ACH-000183", - "ACH-000204", - "ACH-000271", - "ACH-000315", - "ACH-000334", - "ACH-000346", - "ACH-000363", - "ACH-000365", - "ACH-000371", - "ACH-000398", - "ACH-000402", - "ACH-000405", - "ACH-000426", - "ACH-000436", - "ACH-000512", - "ACH-000541", - "ACH-000567", - "ACH-000576", - "ACH-000588", - "ACH-000653", - "ACH-000654", - "ACH-000656", - "ACH-000660", - "ACH-000697", - "ACH-000714", - "ACH-000763", - "ACH-000817", - "ACH-000821", - "ACH-000829", - "ACH-000838", - "ACH-000889", - "ACH-000914", - "ACH-000944", - "ACH-001450", - "ACH-001498", - "ACH-001533", - "ACH-001539", - "ACH-001616", - "ACH-001634", - "ACH-001639", - "ACH-001677", - "ACH-001707", - "ACH-001709", - "ACH-002055", - "ACH-002062", - "ACH-002214", - "ACH-002215", - "ACH-002478", - "ACH-002485", - "ACH-002500", - "ACH-002677", - "ACH-002678" - ], - "hoverinfo": "text", - "marker": { - "color": "#FF97FF", - "size": 7 - }, - "mode": "markers", - "name": "Mature B-Cell Neoplasms", - "text": [ - "Mature B-Cell Neoplasms | ACH-000024", - "Mature B-Cell Neoplasms | ACH-000106", - "Mature B-Cell Neoplasms | ACH-000124", - "Mature B-Cell Neoplasms | ACH-000167", - "Mature B-Cell Neoplasms | ACH-000183", - "Mature B-Cell Neoplasms | ACH-000204", - "Mature B-Cell Neoplasms | ACH-000271", - "Mature B-Cell Neoplasms | ACH-000315", - "Mature B-Cell Neoplasms | ACH-000334", - "Mature B-Cell Neoplasms | ACH-000346", - "Mature B-Cell Neoplasms | ACH-000363", - "Mature B-Cell Neoplasms | ACH-000365", - "Mature B-Cell Neoplasms | ACH-000371", - "Mature B-Cell Neoplasms | ACH-000398", - "Mature B-Cell Neoplasms | ACH-000402", - "Mature B-Cell Neoplasms | ACH-000405", - "Mature B-Cell Neoplasms | ACH-000426", - "Mature B-Cell Neoplasms | ACH-000436", - "Mature B-Cell Neoplasms | ACH-000512", - "Mature B-Cell Neoplasms | ACH-000541", - "Mature B-Cell Neoplasms | ACH-000567", - "Mature B-Cell Neoplasms | ACH-000576", - "Mature B-Cell Neoplasms | ACH-000588", - "Mature B-Cell Neoplasms | ACH-000653", - "Mature B-Cell Neoplasms | ACH-000654", - "Mature B-Cell Neoplasms | ACH-000656", - "Mature B-Cell Neoplasms | ACH-000660", - "Mature B-Cell Neoplasms | ACH-000697", - "Mature B-Cell Neoplasms | ACH-000714", - "Mature B-Cell Neoplasms | ACH-000763", - "Mature B-Cell Neoplasms | ACH-000817", - "Mature B-Cell Neoplasms | ACH-000821", - "Mature B-Cell Neoplasms | ACH-000829", - "Mature B-Cell Neoplasms | ACH-000838", - "Mature B-Cell Neoplasms | ACH-000889", - "Mature B-Cell Neoplasms | ACH-000914", - "Mature B-Cell Neoplasms | ACH-000944", - "Mature B-Cell Neoplasms | ACH-001450", - "Mature B-Cell Neoplasms | ACH-001498", - "Mature B-Cell Neoplasms | ACH-001533", - "Mature B-Cell Neoplasms | ACH-001539", - "Mature B-Cell Neoplasms | ACH-001616", - "Mature B-Cell Neoplasms | ACH-001634", - "Mature B-Cell Neoplasms | ACH-001639", - "Mature B-Cell Neoplasms | ACH-001677", - "Mature B-Cell Neoplasms | ACH-001707", - "Mature B-Cell Neoplasms | ACH-001709", - "Mature B-Cell Neoplasms | ACH-002055", - "Mature B-Cell Neoplasms | ACH-002062", - "Mature B-Cell Neoplasms | ACH-002214", - "Mature B-Cell Neoplasms | ACH-002215", - "Mature B-Cell Neoplasms | ACH-002478", - "Mature B-Cell Neoplasms | ACH-002485", - "Mature B-Cell Neoplasms | ACH-002500", - "Mature B-Cell Neoplasms | ACH-002677", - "Mature B-Cell Neoplasms | ACH-002678" - ], - "type": "scattergl", - "x": { - "bdata": "J+omQHwl4z/a75ZA1dcUQPpscUDoeTVAQ/6jQEygAUCxBoK/lL5FQB9fCr/CXmxAxpQnQI6mGkBIQgxAusJpQLnAjD5BR/XA8uskQDLarD/NDPXACkNGP2rOWUBxyQtAMAoEQPhEoUCJcqZA32hQQMBs/j9/llY/bHFGQI302j90PfXA+U7XP2Kte0DUrn5ALTRXQKn/L0CRplpA4i71wPG+pj8bYmxAn1H1wJCcjj+fMNc/LFj1wDNch0ASkSpA5MQLQAk4eECyfE5AByQpQCyYIUCKQXhAlFRvQAh4AUA=", - "dtype": "f4" - }, - "y": { - "bdata": "MOcTwGrcTr9+/wTATzXkv45bJcBrpFnALixAwKVG6r+H4hHAIMIHwDdXMcCjNDPAtAMowBmnG8BistS/SrD5v1sC4b9agXO+jPn8v3OFEcDFfYO+zHMDwNcGHsANEifAAFoqwIzEFsC+pd+/QAjbv4sEKsBks/G/kdIawGSH8b+Jvm6+sbQHwMTaEsAXQTLAr5kPwAgyNsAQ6RPA69d/vtnt07+M+kvATZF0vhXMTcCBNW6/6MB5vgHKNcDwbwPAlrHTv8AeMcARA+W/dwkNwINqmb+TIgDA3Fs+wNwqDsA=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000025", - "ACH-001067", - "ACH-002070" - ], - "hoverinfo": "text", - "marker": { - "color": "#FECB52", - "size": 7 - }, - "mode": "markers", - "name": "Meningothelial Tumor", - "text": [ - "Meningothelial Tumor | ACH-000025", - "Meningothelial Tumor | ACH-001067", - "Meningothelial Tumor | ACH-002070" - ], - "type": "scattergl", - "x": { - "bdata": "yABNQNop9cD6YO4/", - "dtype": "f4" - }, - "y": { - "bdata": "7jABQMvIc749eaQ/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000036", - "ACH-000040", - "ACH-000067", - "ACH-000075", - "ACH-000098", - "ACH-000128", - "ACH-000137", - "ACH-000152", - "ACH-000200", - "ACH-000208", - "ACH-000215", - "ACH-000231", - "ACH-000232", - "ACH-000244", - "ACH-000269", - "ACH-000273", - "ACH-000323", - "ACH-000329", - "ACH-000368", - "ACH-000370", - "ACH-000376", - "ACH-000389", - "ACH-000437", - "ACH-000445", - "ACH-000455", - "ACH-000464", - "ACH-000469", - "ACH-000479", - "ACH-000504", - "ACH-000558", - "ACH-000570", - "ACH-000571", - "ACH-000591", - "ACH-000592", - "ACH-000595", - "ACH-000609", - "ACH-000622", - "ACH-000623", - "ACH-000631", - "ACH-000634", - "ACH-000655", - "ACH-000673", - "ACH-000676", - "ACH-000738", - "ACH-000756", - "ACH-000760", - "ACH-000807", - "ACH-000819", - "ACH-000863", - "ACH-000887", - "ACH-001016", - "ACH-001126", - "ACH-001172", - "ACH-001329", - "ACH-001605", - "ACH-001606", - "ACH-001608", - "ACH-001609", - "ACH-001610", - "ACH-001611", - "ACH-001622", - "ACH-001623", - "ACH-001624", - "ACH-002228", - "ACH-002229", - "ACH-002230", - "ACH-002257", - "ACH-002269", - "ACH-002304", - "ACH-002680" - ], - "hoverinfo": "text", - "marker": { - "color": "#FD3216", - "size": 7 - }, - "mode": "markers", - "name": "Diffuse Glioma", - "text": [ - "Diffuse Glioma | ACH-000036", - "Diffuse Glioma | ACH-000040", - "Diffuse Glioma | ACH-000067", - "Diffuse Glioma | ACH-000075", - "Diffuse Glioma | ACH-000098", - "Diffuse Glioma | ACH-000128", - "Diffuse Glioma | ACH-000137", - "Diffuse Glioma | ACH-000152", - "Diffuse Glioma | ACH-000200", - "Diffuse Glioma | ACH-000208", - "Diffuse Glioma | ACH-000215", - "Diffuse Glioma | ACH-000231", - "Diffuse Glioma | ACH-000232", - "Diffuse Glioma | ACH-000244", - "Diffuse Glioma | ACH-000269", - "Diffuse Glioma | ACH-000273", - "Diffuse Glioma | ACH-000323", - "Diffuse Glioma | ACH-000329", - "Diffuse Glioma | ACH-000368", - "Diffuse Glioma | ACH-000370", - "Diffuse Glioma | ACH-000376", - "Diffuse Glioma | ACH-000389", - "Diffuse Glioma | ACH-000437", - "Diffuse Glioma | ACH-000445", - "Diffuse Glioma | ACH-000455", - "Diffuse Glioma | ACH-000464", - "Diffuse Glioma | ACH-000469", - "Diffuse Glioma | ACH-000479", - "Diffuse Glioma | ACH-000504", - "Diffuse Glioma | ACH-000558", - "Diffuse Glioma | ACH-000570", - "Diffuse Glioma | ACH-000571", - "Diffuse Glioma | ACH-000591", - "Diffuse Glioma | ACH-000592", - "Diffuse Glioma | ACH-000595", - "Diffuse Glioma | ACH-000609", - "Diffuse Glioma | ACH-000622", - "Diffuse Glioma | ACH-000623", - "Diffuse Glioma | ACH-000631", - "Diffuse Glioma | ACH-000634", - "Diffuse Glioma | ACH-000655", - "Diffuse Glioma | ACH-000673", - "Diffuse Glioma | ACH-000676", - "Diffuse Glioma | ACH-000738", - "Diffuse Glioma | ACH-000756", - "Diffuse Glioma | ACH-000760", - "Diffuse Glioma | ACH-000807", - "Diffuse Glioma | ACH-000819", - "Diffuse Glioma | ACH-000863", - "Diffuse Glioma | ACH-000887", - "Diffuse Glioma | ACH-001016", - "Diffuse Glioma | ACH-001126", - "Diffuse Glioma | ACH-001172", - "Diffuse Glioma | ACH-001329", - "Diffuse Glioma | ACH-001605", - "Diffuse Glioma | ACH-001606", - "Diffuse Glioma | ACH-001608", - "Diffuse Glioma | ACH-001609", - "Diffuse Glioma | ACH-001610", - "Diffuse Glioma | ACH-001611", - "Diffuse Glioma | ACH-001622", - "Diffuse Glioma | ACH-001623", - "Diffuse Glioma | ACH-001624", - "Diffuse Glioma | ACH-002228", - "Diffuse Glioma | ACH-002229", - "Diffuse Glioma | ACH-002230", - "Diffuse Glioma | ACH-002257", - "Diffuse Glioma | ACH-002269", - "Diffuse Glioma | ACH-002304", - "Diffuse Glioma | ACH-002680" - ], - "type": "scattergl", - "x": { - "bdata": "ygmvP89N+b29fTS/QAfnvvIPmT8iee8/f8nZP9oa/b6ZbPXAH6ZoP27ADECr7q4/hrlUQCLlEMCq4I29orkyQLJnbT9wk26+GJy1PhFm4L46kmpAetGaP4PHqz9s0Pk+hPVcQCr2zL8SfqE/4L5fP8RmAMCLasU/ct0DQMdXob84M44/i/wWv90sxz+ELTc/CIIGwFTdCr9Pf60+T9bRP/yXBz9qffXATF9MQAJDNkBIrCdAEDJvP1lx5z/p960/6lErQJYHAUCuo/Y/Eln1wBFGV0A3+1m/trwlPWARrr+/ag9AxVGrP/RbkT+pPLU/5r5YPoEJ/b6P9zO+6lz1wAY+9cCdUvXAOjxCP71yU0CAOfXA9mVkPw==", - "dtype": "f4" - }, - "y": { - "bdata": "+5M6QEexPkCn1BFAcmgTQC5XXUC5OBc/vjkYQAzSA0CnHl++dtGrP6wHBUBKvw9AbOJzP0oSP0CUIsU+6mENQOsR0T9ranI/fYFlQCBuEj+N5qA/pvIQQNfeB0D0px1A/kNLP+L9IUCLmBlALkPvP7tVAkAp8vk/oGYqQLzjtz9rwUpAQaMBQBYKBkAVCw5AZe0NP+d0IkDRjrw/YsnZP5T0ZD8w6VS+aMTUvt+2Yj/LtyBAhbUlPy2DXz6cUt8/cpkOQG8WPD/3yIo/b4FvvjN2xT7S/xtA0CbvPykpoz8jrdg/ah/AP8mQuT/Gn9M/zK06QJxMK0AzdDs/Si1wviRqYb6ImWS+OJpgQFheqz/Xvnm+xko8QA==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000037" - ], - "hoverinfo": "text", - "marker": { - "color": "#00FE35", - "size": 7 - }, - "mode": "markers", - "name": "Sarcoma, NOS", - "text": [ - "Sarcoma, NOS | ACH-000037" - ], - "type": "scattergl", - "x": { - "bdata": "LiYbvw==", - "dtype": "f4" - }, - "y": { - "bdata": "atrvPw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000039", - "ACH-000041", - "ACH-000052", - "ACH-000087", - "ACH-000210", - "ACH-000279", - "ACH-000391", - "ACH-000424", - "ACH-000499", - "ACH-001029", - "ACH-001038", - "ACH-001192", - "ACH-001193", - "ACH-001205", - "ACH-001283", - "ACH-001430", - "ACH-001431", - "ACH-002105", - "ACH-002106", - "ACH-002109", - "ACH-002110", - "ACH-002114", - "ACH-002116", - "ACH-002119", - "ACH-002160" - ], - "hoverinfo": "text", - "marker": { - "color": "#6A76FC", - "size": 7 - }, - "mode": "markers", - "name": "Ewing Sarcoma", - "text": [ - "Ewing Sarcoma | ACH-000039", - "Ewing Sarcoma | ACH-000041", - "Ewing Sarcoma | ACH-000052", - "Ewing Sarcoma | ACH-000087", - "Ewing Sarcoma | ACH-000210", - "Ewing Sarcoma | ACH-000279", - "Ewing Sarcoma | ACH-000391", - "Ewing Sarcoma | ACH-000424", - "Ewing Sarcoma | ACH-000499", - "Ewing Sarcoma | ACH-001029", - "Ewing Sarcoma | ACH-001038", - "Ewing Sarcoma | ACH-001192", - "Ewing Sarcoma | ACH-001193", - "Ewing Sarcoma | ACH-001205", - "Ewing Sarcoma | ACH-001283", - "Ewing Sarcoma | ACH-001430", - "Ewing Sarcoma | ACH-001431", - "Ewing Sarcoma | ACH-002105", - "Ewing Sarcoma | ACH-002106", - "Ewing Sarcoma | ACH-002109", - "Ewing Sarcoma | ACH-002110", - "Ewing Sarcoma | ACH-002114", - "Ewing Sarcoma | ACH-002116", - "Ewing Sarcoma | ACH-002119", - "Ewing Sarcoma | ACH-002160" - ], - "type": "scattergl", - "x": { - "bdata": "DIWCPlcphD4KdZ8/thsdQLIjlz9V7UpAk0tyQCU3j0DyikRAMshnQJhb6z9/vPg/VwPoPxxY7j+fkARAc8PTPwXXBkDiogBAl7lOQGySBUBVWphA7U/1wHBz9cDmIoNAD2t4QA==", - "dtype": "f4" - }, - "y": { - "bdata": "F6ncPh4t474dvcY/3PfOvmmndb5xT/a+RMSRP8TFaj8rhCI/O74qP5zz0L+ynJA+tmSQP2iMAj5lVgw+P1gIPxWHhr4laBJA7r+tvyxFxT6QGBk+5lJqvktxY76d8gc/iJ/7vQ==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000047", - "ACH-000144", - "ACH-000216", - "ACH-000239", - "ACH-000247", - "ACH-000255", - "ACH-000303", - "ACH-000325", - "ACH-000344", - "ACH-000356", - "ACH-000383", - "ACH-000427", - "ACH-000466", - "ACH-000485", - "ACH-000507", - "ACH-000581", - "ACH-000616", - "ACH-000633", - "ACH-000736", - "ACH-000746", - "ACH-000758", - "ACH-000764", - "ACH-000793", - "ACH-000847", - "ACH-000880", - "ACH-000898", - "ACH-000911", - "ACH-000919", - "ACH-000932", - "ACH-000948", - "ACH-001368", - "ACH-001496", - "ACH-001497", - "ACH-001500", - "ACH-001544", - "ACH-001653", - "ACH-001654", - "ACH-001664", - "ACH-002141", - "ACH-002161", - "ACH-002202", - "ACH-002446", - "ACH-002705", - "ACH-002706" - ], - "hoverinfo": "text", - "marker": { - "color": "#FED4C4", - "size": 7 - }, - "mode": "markers", - "name": "Esophagogastric Adenocarcinoma", - "text": [ - "Esophagogastric Adenocarcinoma | ACH-000047", - "Esophagogastric Adenocarcinoma | ACH-000144", - "Esophagogastric Adenocarcinoma | ACH-000216", - "Esophagogastric Adenocarcinoma | ACH-000239", - "Esophagogastric Adenocarcinoma | ACH-000247", - "Esophagogastric Adenocarcinoma | ACH-000255", - "Esophagogastric Adenocarcinoma | ACH-000303", - "Esophagogastric Adenocarcinoma | ACH-000325", - "Esophagogastric Adenocarcinoma | ACH-000344", - "Esophagogastric Adenocarcinoma | ACH-000356", - "Esophagogastric Adenocarcinoma | ACH-000383", - "Esophagogastric Adenocarcinoma | ACH-000427", - "Esophagogastric Adenocarcinoma | ACH-000466", - "Esophagogastric Adenocarcinoma | ACH-000485", - "Esophagogastric Adenocarcinoma | ACH-000507", - "Esophagogastric Adenocarcinoma | ACH-000581", - "Esophagogastric Adenocarcinoma | ACH-000616", - "Esophagogastric Adenocarcinoma | ACH-000633", - "Esophagogastric Adenocarcinoma | ACH-000736", - "Esophagogastric Adenocarcinoma | ACH-000746", - "Esophagogastric Adenocarcinoma | ACH-000758", - "Esophagogastric Adenocarcinoma | ACH-000764", - "Esophagogastric Adenocarcinoma | ACH-000793", - "Esophagogastric Adenocarcinoma | ACH-000847", - "Esophagogastric Adenocarcinoma | ACH-000880", - "Esophagogastric Adenocarcinoma | ACH-000898", - "Esophagogastric Adenocarcinoma | ACH-000911", - "Esophagogastric Adenocarcinoma | ACH-000919", - "Esophagogastric Adenocarcinoma | ACH-000932", - "Esophagogastric Adenocarcinoma | ACH-000948", - "Esophagogastric Adenocarcinoma | ACH-001368", - "Esophagogastric Adenocarcinoma | ACH-001496", - "Esophagogastric Adenocarcinoma | ACH-001497", - "Esophagogastric Adenocarcinoma | ACH-001500", - "Esophagogastric Adenocarcinoma | ACH-001544", - "Esophagogastric Adenocarcinoma | ACH-001653", - "Esophagogastric Adenocarcinoma | ACH-001654", - "Esophagogastric Adenocarcinoma | ACH-001664", - "Esophagogastric Adenocarcinoma | ACH-002141", - "Esophagogastric Adenocarcinoma | ACH-002161", - "Esophagogastric Adenocarcinoma | ACH-002202", - "Esophagogastric Adenocarcinoma | ACH-002446", - "Esophagogastric Adenocarcinoma | ACH-002705", - "Esophagogastric Adenocarcinoma | ACH-002706" - ], - "type": "scattergl", - "x": { - "bdata": "WLhTQBshJ8BPCxlA/opNPxZrKUDoZe8/mdIJQBIuGEDqf6A/D0DcP/GbFz9yYvXANyF2P71lHEBmrlJA1IbnP/HTND8AgbA/gPlJQEMCvD6f5yJAcmj1wAK8GUDtHvXADD94QC1qAT/jeltA3evlP8X1OkD3PztAGjzPP0oDPT+4rqQ/L7ckQHpu5z2xfQZAF3spQL34WkCcO4BA5+X/P74GPUCVxhZAVLciQPEjWUA=", - "dtype": "f4" - }, - "y": { - "bdata": "FveQv2c2Vb80eC0/JatOPQWBvb8B1NU/YR4vv4vSHMAQkEI/LCf6vn7Rw7/Z7nS+9qzlP3D2q79F+5K/aITvvyP+yj/qi66/zAK/v8HLGMCoro+/2tVgvna4AcDOBoG+UqaQvsv8+L8SlUm/08L7vhRX3r+THXm/2dDjv2Sn9r8Uj6W/HFdhPwkX0L8FWIe/JzPHPwM1DcDJQ8u/DgE+v82cOr5IofW+Em3Uvv7Cyb4=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000053", - "ACH-000101", - "ACH-000226", - "ACH-000233", - "ACH-000338", - "ACH-000664", - "ACH-000773", - "ACH-001111", - "ACH-001119", - "ACH-001737" - ], - "hoverinfo": "text", - "marker": { - "color": "#FE00CE", - "size": 7 - }, - "mode": "markers", - "name": "Mature T and NK Neoplasms", - "text": [ - "Mature T and NK Neoplasms | ACH-000053", - "Mature T and NK Neoplasms | ACH-000101", - "Mature T and NK Neoplasms | ACH-000226", - "Mature T and NK Neoplasms | ACH-000233", - "Mature T and NK Neoplasms | ACH-000338", - "Mature T and NK Neoplasms | ACH-000664", - "Mature T and NK Neoplasms | ACH-000773", - "Mature T and NK Neoplasms | ACH-001111", - "Mature T and NK Neoplasms | ACH-001119", - "Mature T and NK Neoplasms | ACH-001737" - ], - "type": "scattergl", - "x": { - "bdata": "EWe6P5C9Z0BdeE5AwjM9QJPJvD+sbItATXoLQPlr7j/09zG/8jMfQA==", - "dtype": "f4" - }, - "y": { - "bdata": "7uwIwIumIcDK5v+/HiW7v8fczL6mmhXAb47Xv85/hb9OAzW/aUcuPg==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000054" - ], - "hoverinfo": "text", - "marker": { - "color": "#0DF9FF", - "size": 7 - }, - "mode": "markers", - "name": "Fibrosarcoma", - "text": [ - "Fibrosarcoma | ACH-000054" - ], - "type": "scattergl", - "x": { - "bdata": "DTuBPw==", - "dtype": "f4" - }, - "y": { - "bdata": "fpSPPw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000055", - "ACH-000095", - "ACH-000160", - "ACH-000211", - "ACH-000776", - "ACH-001020", - "ACH-001028", - "ACH-001031", - "ACH-001033", - "ACH-001053", - "ACH-001054", - "ACH-001232", - "ACH-001289", - "ACH-001670", - "ACH-001711" - ], - "hoverinfo": "text", - "marker": { - "color": "#F6F926", - "size": 7 - }, - "mode": "markers", - "name": "Embryonal Tumor", - "text": [ - "Embryonal Tumor | ACH-000055", - "Embryonal Tumor | ACH-000095", - "Embryonal Tumor | ACH-000160", - "Embryonal Tumor | ACH-000211", - "Embryonal Tumor | ACH-000776", - "Embryonal Tumor | ACH-001020", - "Embryonal Tumor | ACH-001028", - "Embryonal Tumor | ACH-001031", - "Embryonal Tumor | ACH-001033", - "Embryonal Tumor | ACH-001053", - "Embryonal Tumor | ACH-001054", - "Embryonal Tumor | ACH-001232", - "Embryonal Tumor | ACH-001289", - "Embryonal Tumor | ACH-001670", - "Embryonal Tumor | ACH-001711" - ], - "type": "scattergl", - "x": { - "bdata": "/esoQHAd9z9/anFAHl5zP3E6BECd5QJA1vFTQCNMY0C6Mdg/3HTSPygGWkDQKFA/TeugPwsmOkBiSA9A", - "dtype": "f4" - }, - "y": { - "bdata": "Q8R1v+p5Lb8gP/Y+C+LtP/W6Qz/CeHU/IU+kvpUT8D6yS+M+6LWbviaXi78FYC5AOGz2vu+Q5T7U2sc+", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000070", - "ACH-000151", - "ACH-000782", - "ACH-000922", - "ACH-000938", - "ACH-000960", - "ACH-001484", - "ACH-001520", - "ACH-001669", - "ACH-001735", - "ACH-001736", - "ACH-001993", - "ACH-002059" - ], - "hoverinfo": "text", - "marker": { - "color": "#FF9616", - "size": 7 - }, - "mode": "markers", - "name": "B-Lymphoblastic Leukemia/Lymphoma", - "text": [ - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000070", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000151", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000782", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000922", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000938", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000960", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001484", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001520", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001669", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001735", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001736", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001993", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-002059" - ], - "type": "scattergl", - "x": { - "bdata": "DitMQDjJqz/1ZDtAUVFtQEOATUBzyEpA6Xo1QDW7VUBJHm5AC3EhQGJAeUDe6dA/KUE+QA==", - "dtype": "f4" - }, - "y": { - "bdata": "+i4gwBykJcBwwirAq+ZBwC5PWsC1HDPAq8YAwAIsCsDFainAeBA5wOYvRcDGSwrAlaf5vw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000074", - "ACH-000076", - "ACH-000198", - "ACH-000295", - "ACH-000326", - "ACH-000551", - "ACH-000604", - "ACH-000920", - "ACH-000983", - "ACH-002061" - ], - "hoverinfo": "text", - "marker": { - "color": "#479B55", - "size": 7 - }, - "mode": "markers", - "name": "Myeloproliferative Neoplasms", - "text": [ - "Myeloproliferative Neoplasms | ACH-000074", - "Myeloproliferative Neoplasms | ACH-000076", - "Myeloproliferative Neoplasms | ACH-000198", - "Myeloproliferative Neoplasms | ACH-000295", - "Myeloproliferative Neoplasms | ACH-000326", - "Myeloproliferative Neoplasms | ACH-000551", - "Myeloproliferative Neoplasms | ACH-000604", - "Myeloproliferative Neoplasms | ACH-000920", - "Myeloproliferative Neoplasms | ACH-000983", - "Myeloproliferative Neoplasms | ACH-002061" - ], - "type": "scattergl", - "x": { - "bdata": "u1n9P1XPSkA1Y4xAHpSaP8A6X0CWkB1A6Gb9P1Obzj8DFGlADDJEQA==", - "dtype": "f4" - }, - "y": { - "bdata": "WHsbwGzt4L8QWjTAZlPLv25QBcDHQx7AuYDgv8ilFL++ByLAo6L8vw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000077", - "ACH-000583", - "ACH-001197", - "ACH-001642" - ], - "hoverinfo": "text", - "marker": { - "color": "#EEA6FB", - "size": 7 - }, - "mode": "markers", - "name": "Non-Hodgkin Lymphoma", - "text": [ - "Non-Hodgkin Lymphoma | ACH-000077", - "Non-Hodgkin Lymphoma | ACH-000583", - "Non-Hodgkin Lymphoma | ACH-001197", - "Non-Hodgkin Lymphoma | ACH-001642" - ], - "type": "scattergl", - "x": { - "bdata": "k+NUQEUn9cAoSSJABGnVPw==", - "dtype": "f4" - }, - "y": { - "bdata": "vr1nvz1chL4rKPq/i8u3vw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000078", - "ACH-000099", - "ACH-000120", - "ACH-000149", - "ACH-000203", - "ACH-000227", - "ACH-000259", - "ACH-000260", - "ACH-000310", - "ACH-000312", - "ACH-000341", - "ACH-000366", - "ACH-000804", - "ACH-001188", - "ACH-001300", - "ACH-001301", - "ACH-001302", - "ACH-001303", - "ACH-001338", - "ACH-001344", - "ACH-001354", - "ACH-001366", - "ACH-001367", - "ACH-001481", - "ACH-001548", - "ACH-001603", - "ACH-001674", - "ACH-002080", - "ACH-002083", - "ACH-002261", - "ACH-002278", - "ACH-002280", - "ACH-002282", - "ACH-002283", - "ACH-002284", - "ACH-002285", - "ACH-002922" - ], - "hoverinfo": "text", - "marker": { - "color": "#DC587D", - "size": 7 - }, - "mode": "markers", - "name": "Neuroblastoma", - "text": [ - "Neuroblastoma | ACH-000078", - "Neuroblastoma | ACH-000099", - "Neuroblastoma | ACH-000120", - "Neuroblastoma | ACH-000149", - "Neuroblastoma | ACH-000203", - "Neuroblastoma | ACH-000227", - "Neuroblastoma | ACH-000259", - "Neuroblastoma | ACH-000260", - "Neuroblastoma | ACH-000310", - "Neuroblastoma | ACH-000312", - "Neuroblastoma | ACH-000341", - "Neuroblastoma | ACH-000366", - "Neuroblastoma | ACH-000804", - "Neuroblastoma | ACH-001188", - "Neuroblastoma | ACH-001300", - "Neuroblastoma | ACH-001301", - "Neuroblastoma | ACH-001302", - "Neuroblastoma | ACH-001303", - "Neuroblastoma | ACH-001338", - "Neuroblastoma | ACH-001344", - "Neuroblastoma | ACH-001354", - "Neuroblastoma | ACH-001366", - "Neuroblastoma | ACH-001367", - "Neuroblastoma | ACH-001481", - "Neuroblastoma | ACH-001548", - "Neuroblastoma | ACH-001603", - "Neuroblastoma | ACH-001674", - "Neuroblastoma | ACH-002080", - "Neuroblastoma | ACH-002083", - "Neuroblastoma | ACH-002261", - "Neuroblastoma | ACH-002278", - "Neuroblastoma | ACH-002280", - "Neuroblastoma | ACH-002282", - "Neuroblastoma | ACH-002283", - "Neuroblastoma | ACH-002284", - "Neuroblastoma | ACH-002285", - "Neuroblastoma | ACH-002922" - ], - "type": "scattergl", - "x": { - "bdata": "Xm9AP+mTHkDgf30/cRkuQBOtET9j7e+/VONSQHdECUAyo8W/zXc0P92s5b4Xe7E/J3ZVQN/AC0AIbixAewHfvG/VWj/d9lA+YhUnQF9Gij/zJLo/P03zPxpGHkAPO0o/qGo3PwaYoj967c8/ein1wFK5ckBl20JANbMzQCeQIUD1RA9AHxwQQFlI9cDNS6dATmspQA==", - "dtype": "f4" - }, - "y": { - "bdata": "Tdwyv8WvWL9jkEw/xtSfPux4yT46Dmu/iU95vxjGez/qCR2/DuuQv3KPlD5dFsm+9i20vs9z0z7FtJa+UDXmPiHBr743CFy+62XRv5SOnj8rH2i9zNAov8DHGr91irE/LjTvPrNHKb8QadS/BTF8vhITvT9jMm6/qDoOv2V8Rb/C9wK/MsopPzncab5VWSY/+c1Cvw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000082", - "ACH-000359", - "ACH-000364", - "ACH-000410", - "ACH-000748", - "ACH-001001", - "ACH-001526", - "ACH-001715", - "ACH-001814", - "ACH-002067", - "ACH-002069", - "ACH-002471", - "ACH-002834" - ], - "hoverinfo": "text", - "marker": { - "color": "#D626FF", - "size": 7 - }, - "mode": "markers", - "name": "Osteosarcoma", - "text": [ - "Osteosarcoma | ACH-000082", - "Osteosarcoma | ACH-000359", - "Osteosarcoma | ACH-000364", - "Osteosarcoma | ACH-000410", - "Osteosarcoma | ACH-000748", - "Osteosarcoma | ACH-001001", - "Osteosarcoma | ACH-001526", - "Osteosarcoma | ACH-001715", - "Osteosarcoma | ACH-001814", - "Osteosarcoma | ACH-002067", - "Osteosarcoma | ACH-002069", - "Osteosarcoma | ACH-002471", - "Osteosarcoma | ACH-002834" - ], - "type": "scattergl", - "x": { - "bdata": "tqkRwK0axL/2lQdA5suAPzL9DUBoBWFAiAibvjQj+b5AbcS+TBajP6qLgj9bGTQ/qo71wA==", - "dtype": "f4" - }, - "y": { - "bdata": "DXmcP+yRpz++IwNANiqXPz8gN0CgQ6y+UTChP3jguT+JYBZAHyIOP7UaIkBKmbw/SeJavg==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000086", - "ACH-000092", - "ACH-000153", - "ACH-000319", - "ACH-000331", - "ACH-000335", - "ACH-000367", - "ACH-000569", - "ACH-000645", - "ACH-000648", - "ACH-001547", - "ACH-001555", - "ACH-001556", - "ACH-001557", - "ACH-001558", - "ACH-001559", - "ACH-001560", - "ACH-001562", - "ACH-001977", - "ACH-001992", - "ACH-002033" - ], - "hoverinfo": "text", - "marker": { - "color": "#6E899C", - "size": 7 - }, - "mode": "markers", - "name": "Pleural Mesothelioma", - "text": [ - "Pleural Mesothelioma | ACH-000086", - "Pleural Mesothelioma | ACH-000092", - "Pleural Mesothelioma | ACH-000153", - "Pleural Mesothelioma | ACH-000319", - "Pleural Mesothelioma | ACH-000331", - "Pleural Mesothelioma | ACH-000335", - "Pleural Mesothelioma | ACH-000367", - "Pleural Mesothelioma | ACH-000569", - "Pleural Mesothelioma | ACH-000645", - "Pleural Mesothelioma | ACH-000648", - "Pleural Mesothelioma | ACH-001547", - "Pleural Mesothelioma | ACH-001555", - "Pleural Mesothelioma | ACH-001556", - "Pleural Mesothelioma | ACH-001557", - "Pleural Mesothelioma | ACH-001558", - "Pleural Mesothelioma | ACH-001559", - "Pleural Mesothelioma | ACH-001560", - "Pleural Mesothelioma | ACH-001562", - "Pleural Mesothelioma | ACH-001977", - "Pleural Mesothelioma | ACH-001992", - "Pleural Mesothelioma | ACH-002033" - ], - "type": "scattergl", - "x": { - "bdata": "2ScXQOObKr9EWAI97RhwPWrLlj+bpiJAO0r1wCyKjD/Vv1a/VSLXP2qhZj/GUKU/KGH4PwQKrT8UZPXACjr1wF1Z9cCEMPXAL2lJQKNGN0AXSP+/", - "dtype": "f4" - }, - "y": { - "bdata": "iK3GP9RAzz+GvQFA5HQVQF7T3j+CjLE+xWFsvs6ECT9X1Ng/Mkm/P8kNJEDVm/A/c7dRP0VMBUCxDmK+m15xvsy9bL6Ll2u+Eqv/vWZojT8f2Gs+", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000090", - "ACH-000115", - "ACH-000956", - "ACH-000977", - "ACH-000979", - "ACH-001422", - "ACH-001627", - "ACH-001648", - "ACH-001649" - ], - "hoverinfo": "text", - "marker": { - "color": "#00B5F7", - "size": 7 - }, - "mode": "markers", - "name": "Prostate Adenocarcinoma", - "text": [ - "Prostate Adenocarcinoma | ACH-000090", - "Prostate Adenocarcinoma | ACH-000115", - "Prostate Adenocarcinoma | ACH-000956", - "Prostate Adenocarcinoma | ACH-000977", - "Prostate Adenocarcinoma | ACH-000979", - "Prostate Adenocarcinoma | ACH-001422", - "Prostate Adenocarcinoma | ACH-001627", - "Prostate Adenocarcinoma | ACH-001648", - "Prostate Adenocarcinoma | ACH-001649" - ], - "type": "scattergl", - "x": { - "bdata": "5niCP7HAFsAfKUI/XY9KQID1pD93MEDAujD1wFUp9cCyY/XA", - "dtype": "f4" - }, - "y": { - "bdata": "q6SdP5k+L78R376/jie9v00E/D7XvsK/vs98vkiAfL4HQGa+", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000096", - "ACH-000172", - "ACH-000533", - "ACH-000597", - "ACH-001099", - "ACH-001128", - "ACH-001211", - "ACH-001212", - "ACH-001532" - ], - "hoverinfo": "text", - "marker": { - "color": "#B68E00", - "size": 7 - }, - "mode": "markers", - "name": "Rhabdoid Cancer", - "text": [ - "Rhabdoid Cancer | ACH-000096", - "Rhabdoid Cancer | ACH-000172", - "Rhabdoid Cancer | ACH-000533", - "Rhabdoid Cancer | ACH-000597", - "Rhabdoid Cancer | ACH-001099", - "Rhabdoid Cancer | ACH-001128", - "Rhabdoid Cancer | ACH-001211", - "Rhabdoid Cancer | ACH-001212", - "Rhabdoid Cancer | ACH-001532" - ], - "type": "scattergl", - "x": { - "bdata": "gQ/7Pxz6AEDGinVAxe0vQHBzeECgdxNAZk0kQM7A7T+J4W9A", - "dtype": "f4" - }, - "y": { - "bdata": "eH2zPnlXgD/lvKY+JwteP1q2Nj+9qwc/p3fuPmuwpz/pf/m+", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000100", - "ACH-000169", - "ACH-000607", - "ACH-000833", - "ACH-001050", - "ACH-001096", - "ACH-001184", - "ACH-001196", - "ACH-001740", - "ACH-001745", - "ACH-001750", - "ACH-001765", - "ACH-002048" - ], - "hoverinfo": "text", - "marker": { - "color": "#C9FBE5", - "size": 7 - }, - "mode": "markers", - "name": "Rhabdomyosarcoma", - "text": [ - "Rhabdomyosarcoma | ACH-000100", - "Rhabdomyosarcoma | ACH-000169", - "Rhabdomyosarcoma | ACH-000607", - "Rhabdomyosarcoma | ACH-000833", - "Rhabdomyosarcoma | ACH-001050", - "Rhabdomyosarcoma | ACH-001096", - "Rhabdomyosarcoma | ACH-001184", - "Rhabdomyosarcoma | ACH-001196", - "Rhabdomyosarcoma | ACH-001740", - "Rhabdomyosarcoma | ACH-001745", - "Rhabdomyosarcoma | ACH-001750", - "Rhabdomyosarcoma | ACH-001765", - "Rhabdomyosarcoma | ACH-002048" - ], - "type": "scattergl", - "x": { - "bdata": "OQcIQCJnGUAkqeA/+v8aQIslaD8NtFdAiPE9QNgvN0DlANI/FFUPQL5i/z9qezxAZBxsQA==", - "dtype": "f4" - }, - "y": { - "bdata": "SakQv5iQeD7fAQ4/uQibva5RL0DuAna+UnQkv0xqGz+2F949OFOOvivajD8QylK/mycWvg==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000108", - "ACH-000685" - ], - "hoverinfo": "text", - "marker": { - "color": "#FF0092", - "size": 7 - }, - "mode": "markers", - "name": "Adenosquamous Carcinoma of the Pancreas", - "text": [ - "Adenosquamous Carcinoma of the Pancreas | ACH-000108", - "Adenosquamous Carcinoma of the Pancreas | ACH-000685" - ], - "type": "scattergl", - "x": { - "bdata": "Q21bv+xvOkA=", - "dtype": "f4" - }, - "y": { - "bdata": "YnGZPkp3wz8=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000133", - "ACH-001310", - "ACH-001453", - "ACH-002210", - "ACH-002247", - "ACH-002462", - "ACH-002463", - "ACH-002464", - "ACH-002465", - "ACH-002467" - ], - "hoverinfo": "text", - "marker": { - "color": "#22FFA7", - "size": 7 - }, - "mode": "markers", - "name": "Non-Cancerous", - "text": [ - "Non-Cancerous | ACH-000133", - "Non-Cancerous | ACH-001310", - "Non-Cancerous | ACH-001453", - "Non-Cancerous | ACH-002210", - "Non-Cancerous | ACH-002247", - "Non-Cancerous | ACH-002462", - "Non-Cancerous | ACH-002463", - "Non-Cancerous | ACH-002464", - "Non-Cancerous | ACH-002465", - "Non-Cancerous | ACH-002467" - ], - "type": "scattergl", - "x": { - "bdata": "inBOP8U49cBENfg/ORyPQFk79cBSfPXAZVn1wIes9cA3ZfXAyFT1wA==", - "dtype": "f4" - }, - "y": { - "bdata": "WREnQHe2db7Lvq8/INL9v0cbdr7rFmG+UjtjvsLDWb63JGy+lztsvg==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000141", - "ACH-001607", - "ACH-001619", - "ACH-001850", - "ACH-001861", - "ACH-001961" - ], - "hoverinfo": "text", - "marker": { - "color": "#E3EE9E", - "size": 7 - }, - "mode": "markers", - "name": "Intracholecystic Papillary Neoplasm", - "text": [ - "Intracholecystic Papillary Neoplasm | ACH-000141", - "Intracholecystic Papillary Neoplasm | ACH-001607", - "Intracholecystic Papillary Neoplasm | ACH-001619", - "Intracholecystic Papillary Neoplasm | ACH-001850", - "Intracholecystic Papillary Neoplasm | ACH-001861", - "Intracholecystic Papillary Neoplasm | ACH-001961" - ], - "type": "scattergl", - "x": { - "bdata": "ho31wPBPLkBRPsK+qDdCQGd09cDhdyVA", - "dtype": "f4" - }, - "y": { - "bdata": "CmZTvgIhHb9T5aU/vgpHPrcRZr5dMpi+", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000145", - "ACH-000505", - "ACH-002785" - ], - "hoverinfo": "text", - "marker": { - "color": "#86CE00", - "size": 7 - }, - "mode": "markers", - "name": "Leiomyosarcoma", - "text": [ - "Leiomyosarcoma | ACH-000145", - "Leiomyosarcoma | ACH-000505", - "Leiomyosarcoma | ACH-002785" - ], - "type": "scattergl", - "x": { - "bdata": "mskwv9vcwb+ghI+/", - "dtype": "f4" - }, - "y": { - "bdata": "a0XnP4YXxz+YzK4+", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000159", - "ACH-000189", - "ACH-000234", - "ACH-000246", - "ACH-000250", - "ACH-000262", - "ACH-000272", - "ACH-000313", - "ACH-000317", - "ACH-000375", - "ACH-000385", - "ACH-000411", - "ACH-000433", - "ACH-000459", - "ACH-000484", - "ACH-000495", - "ACH-000649", - "ACH-000684", - "ACH-000709", - "ACH-000792", - "ACH-000907", - "ACH-001163", - "ACH-001194", - "ACH-001398", - "ACH-001687", - "ACH-001688", - "ACH-002150", - "ACH-002189", - "ACH-002533" - ], - "hoverinfo": "text", - "marker": { - "color": "#BC7196", - "size": 7 - }, - "mode": "markers", - "name": "Renal Cell Carcinoma", - "text": [ - "Renal Cell Carcinoma | ACH-000159", - "Renal Cell Carcinoma | ACH-000189", - "Renal Cell Carcinoma | ACH-000234", - "Renal Cell Carcinoma | ACH-000246", - "Renal Cell Carcinoma | ACH-000250", - "Renal Cell Carcinoma | ACH-000262", - "Renal Cell Carcinoma | ACH-000272", - "Renal Cell Carcinoma | ACH-000313", - "Renal Cell Carcinoma | ACH-000317", - "Renal Cell Carcinoma | ACH-000375", - "Renal Cell Carcinoma | ACH-000385", - "Renal Cell Carcinoma | ACH-000411", - "Renal Cell Carcinoma | ACH-000433", - "Renal Cell Carcinoma | ACH-000459", - "Renal Cell Carcinoma | ACH-000484", - "Renal Cell Carcinoma | ACH-000495", - "Renal Cell Carcinoma | ACH-000649", - "Renal Cell Carcinoma | ACH-000684", - "Renal Cell Carcinoma | ACH-000709", - "Renal Cell Carcinoma | ACH-000792", - "Renal Cell Carcinoma | ACH-000907", - "Renal Cell Carcinoma | ACH-001163", - "Renal Cell Carcinoma | ACH-001194", - "Renal Cell Carcinoma | ACH-001398", - "Renal Cell Carcinoma | ACH-001687", - "Renal Cell Carcinoma | ACH-001688", - "Renal Cell Carcinoma | ACH-002150", - "Renal Cell Carcinoma | ACH-002189", - "Renal Cell Carcinoma | ACH-002533" - ], - "type": "scattergl", - "x": { - "bdata": "SJ0vv4Bo9cDFbNi+iVf1wGxD9cCKVfXA04b1wGoBmr9Oe/XAl+ZOQPRrnT+1NQRAL9r9PSSwlsBzjPXA4JUSPgVOG0BVBV4/x9B8vwLmyD9RTfS/W3OBPxKX9cD6TCy+Azv1wGeS9cBgSfXAhvkXwCjzVUA=", - "dtype": "f4" - }, - "y": { - "bdata": "EfAeP/DXVr7SkvU/Z5tivtGtZL4hmFe+1p5cviFWsj/q1GO+UMW9PNC9vT8zRtc/chD2P+D62b6EeGO+5J/sPz6o8z9FDBRAjsmxP5beRUADrABA1CWcv7bySL5WTu8+VcVovui+Z74FjWy+VZFzPzt0nrs=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000163", - "ACH-000181", - "ACH-000188", - "ACH-000207", - "ACH-000228", - "ACH-000238", - "ACH-000415", - "ACH-000472", - "ACH-000500", - "ACH-000503", - "ACH-000518", - "ACH-000546", - "ACH-000548", - "ACH-000549", - "ACH-000606", - "ACH-000618", - "ACH-000619", - "ACH-000630", - "ACH-000682", - "ACH-000732", - "ACH-000735", - "ACH-000740", - "ACH-000762", - "ACH-000771", - "ACH-000778", - "ACH-000794", - "ACH-000832", - "ACH-000836", - "ACH-000846", - "ACH-001228", - "ACH-001229", - "ACH-001331", - "ACH-001332", - "ACH-001346", - "ACH-001347", - "ACH-001385", - "ACH-001509", - "ACH-001510", - "ACH-001511", - "ACH-001542", - "ACH-001543", - "ACH-001625", - "ACH-001626", - "ACH-001641", - "ACH-001675", - "ACH-001690", - "ACH-001691", - "ACH-001692", - "ACH-001694", - "ACH-001695", - "ACH-001696", - "ACH-001698", - "ACH-001699", - "ACH-001701", - "ACH-002029", - "ACH-002030", - "ACH-002042", - "ACH-002043", - "ACH-002044", - "ACH-002045", - "ACH-002212", - "ACH-002249", - "ACH-002250", - "ACH-002251", - "ACH-002265", - "ACH-002294", - "ACH-002295", - "ACH-002296", - "ACH-002297", - "ACH-002298", - "ACH-002305" - ], - "hoverinfo": "text", - "marker": { - "color": "#7E7DCD", - "size": 7 - }, - "mode": "markers", - "name": "Head and Neck Squamous Cell Carcinoma", - "text": [ - "Head and Neck Squamous Cell Carcinoma | ACH-000163", - "Head and Neck Squamous Cell Carcinoma | ACH-000181", - "Head and Neck Squamous Cell Carcinoma | ACH-000188", - "Head and Neck Squamous Cell Carcinoma | ACH-000207", - "Head and Neck Squamous Cell Carcinoma | ACH-000228", - "Head and Neck Squamous Cell Carcinoma | ACH-000238", - "Head and Neck Squamous Cell Carcinoma | ACH-000415", - "Head and Neck Squamous Cell Carcinoma | ACH-000472", - "Head and Neck Squamous Cell Carcinoma | ACH-000500", - "Head and Neck Squamous Cell Carcinoma | ACH-000503", - "Head and Neck Squamous Cell Carcinoma | ACH-000518", - "Head and Neck Squamous Cell Carcinoma | ACH-000546", - "Head and Neck Squamous Cell Carcinoma | ACH-000548", - "Head and Neck Squamous Cell Carcinoma | ACH-000549", - "Head and Neck Squamous Cell Carcinoma | ACH-000606", - "Head and Neck Squamous Cell Carcinoma | ACH-000618", - "Head and Neck Squamous Cell Carcinoma | ACH-000619", - "Head and Neck Squamous Cell Carcinoma | ACH-000630", - "Head and Neck Squamous Cell Carcinoma | ACH-000682", - "Head and Neck Squamous Cell Carcinoma | ACH-000732", - "Head and Neck Squamous Cell Carcinoma | ACH-000735", - "Head and Neck Squamous Cell Carcinoma | ACH-000740", - "Head and Neck Squamous Cell Carcinoma | ACH-000762", - "Head and Neck Squamous Cell Carcinoma | ACH-000771", - "Head and Neck Squamous Cell Carcinoma | ACH-000778", - "Head and Neck Squamous Cell Carcinoma | ACH-000794", - "Head and Neck Squamous Cell Carcinoma | ACH-000832", - "Head and Neck Squamous Cell Carcinoma | ACH-000836", - "Head and Neck Squamous Cell Carcinoma | ACH-000846", - "Head and Neck Squamous Cell Carcinoma | ACH-001228", - "Head and Neck Squamous Cell Carcinoma | ACH-001229", - "Head and Neck Squamous Cell Carcinoma | ACH-001331", - "Head and Neck Squamous Cell Carcinoma | ACH-001332", - "Head and Neck Squamous Cell Carcinoma | ACH-001346", - "Head and Neck Squamous Cell Carcinoma | ACH-001347", - "Head and Neck Squamous Cell Carcinoma | ACH-001385", - "Head and Neck Squamous Cell Carcinoma | ACH-001509", - "Head and Neck Squamous Cell Carcinoma | ACH-001510", - "Head and Neck Squamous Cell Carcinoma | ACH-001511", - "Head and Neck Squamous Cell Carcinoma | ACH-001542", - "Head and Neck Squamous Cell Carcinoma | ACH-001543", - "Head and Neck Squamous Cell Carcinoma | ACH-001625", - "Head and Neck Squamous Cell Carcinoma | ACH-001626", - "Head and Neck Squamous Cell Carcinoma | ACH-001641", - "Head and Neck Squamous Cell Carcinoma | ACH-001675", - "Head and Neck Squamous Cell Carcinoma | ACH-001690", - "Head and Neck Squamous Cell Carcinoma | ACH-001691", - "Head and Neck Squamous Cell Carcinoma | ACH-001692", - "Head and Neck Squamous Cell Carcinoma | ACH-001694", - "Head and Neck Squamous Cell Carcinoma | ACH-001695", - "Head and Neck Squamous Cell Carcinoma | ACH-001696", - "Head and Neck Squamous Cell Carcinoma | ACH-001698", - "Head and Neck Squamous Cell Carcinoma | ACH-001699", - "Head and Neck Squamous Cell Carcinoma | ACH-001701", - "Head and Neck Squamous Cell Carcinoma | ACH-002029", - "Head and Neck Squamous Cell Carcinoma | ACH-002030", - "Head and Neck Squamous Cell Carcinoma | ACH-002042", - "Head and Neck Squamous Cell Carcinoma | ACH-002043", - "Head and Neck Squamous Cell Carcinoma | ACH-002044", - "Head and Neck Squamous Cell Carcinoma | ACH-002045", - "Head and Neck Squamous Cell Carcinoma | ACH-002212", - "Head and Neck Squamous Cell Carcinoma | ACH-002249", - "Head and Neck Squamous Cell Carcinoma | ACH-002250", - "Head and Neck Squamous Cell Carcinoma | ACH-002251", - "Head and Neck Squamous Cell Carcinoma | ACH-002265", - "Head and Neck Squamous Cell Carcinoma | ACH-002294", - "Head and Neck Squamous Cell Carcinoma | ACH-002295", - "Head and Neck Squamous Cell Carcinoma | ACH-002296", - "Head and Neck Squamous Cell Carcinoma | ACH-002297", - "Head and Neck Squamous Cell Carcinoma | ACH-002298", - "Head and Neck Squamous Cell Carcinoma | ACH-002305" - ], - "type": "scattergl", - "x": { - "bdata": "3LxePzs2AkDYNBZA+lL1wDlf9cD9IN0/uG/1wIUzjT5zSDg/zm/1wL7VY0Bg30tARd3qPgmFCkBcXyJA88tuQKq4XEAk+RFAveJBQNyb6T9wpwBA/t6/P7cR9j+HYvXAZ4AkvXngOUC5l5NA6XwbQASrbEAaAlG+RkHePzp19cCMePXAoyITQPDxGkDiWlxAw2eWP7UjFEDbZjU+QUqDQNjSD0Ao7yq/znubv61T9cA99f4/NslPQCzQXD+MwU9Ac0suQCLqD0AM+B1AHW8AQAuZcEA0uCVACkCAQN/ELkDscoa+Y5AjQGycc0AV2DJAuGb1wJABd0BCc4Q/ScVMQAlF9cA/rSpAiuNbP9ygjEDtAGFAF3x6QD1l9cA=", - "dtype": "f4" - }, - "y": { - "bdata": 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ACH-002041" - ], - "type": "scattergl", - "x": { - "bdata": "QZrQPzuE8j/0Zco+ti6Sv8VlCcC1eo4/Ds4YPw==", - "dtype": "f4" - }, - "y": { - "bdata": "vw3SP5GYyT/AZSZAp5hOP/nwk72qnaA/hGEbQA==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000182", - "ACH-000377", - "ACH-001862", - "ACH-002023" - ], - "hoverinfo": "text", - "marker": { - "color": "#E48F72", - "size": 7 - }, - "mode": "markers", - "name": "Ampullary Carcinoma", - "text": [ - "Ampullary Carcinoma | ACH-000182", - "Ampullary Carcinoma | ACH-000377", - "Ampullary Carcinoma | ACH-001862", - "Ampullary Carcinoma | ACH-002023" - ], - "type": "scattergl", - "x": { - "bdata": "okP1wF9K9cCtYQK/I6ggQA==", - "dtype": "f4" - }, - "y": { - "bdata": "+rB/vp1Rbb5jYXg+ulJgvw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000187", - "ACH-000257", - "ACH-000290", - "ACH-000292", - "ACH-000355", - "ACH-000431", - "ACH-000514", - "ACH-000515", - "ACH-000525", - "ACH-000559", - "ACH-000639", - "ACH-000695", - "ACH-000698", - "ACH-000749", - "ACH-000767", - "ACH-000775", - "ACH-000790", - "ACH-000800", - "ACH-000866", - "ACH-000871", - "ACH-000890", - "ACH-000912", - "ACH-001386", - "ACH-001549", - "ACH-002051", - "ACH-002052", - "ACH-002077" - ], - "hoverinfo": "text", - "marker": { - "color": "#2E91E5", - "size": 7 - }, - "mode": "markers", - "name": "Lung Neuroendocrine Tumor", - "text": [ - "Lung Neuroendocrine Tumor | ACH-000187", - "Lung Neuroendocrine Tumor | ACH-000257", - "Lung Neuroendocrine Tumor | ACH-000290", - "Lung Neuroendocrine Tumor | ACH-000292", - "Lung Neuroendocrine Tumor | ACH-000355", - "Lung Neuroendocrine Tumor | ACH-000431", - "Lung Neuroendocrine Tumor | ACH-000514", - "Lung Neuroendocrine Tumor | ACH-000515", - "Lung Neuroendocrine Tumor | ACH-000525", - "Lung Neuroendocrine Tumor | ACH-000559", - "Lung Neuroendocrine Tumor | ACH-000639", - "Lung Neuroendocrine Tumor | ACH-000695", - "Lung Neuroendocrine Tumor | ACH-000698", - "Lung Neuroendocrine Tumor | ACH-000749", - "Lung Neuroendocrine Tumor | ACH-000767", - "Lung Neuroendocrine Tumor | ACH-000775", - "Lung Neuroendocrine Tumor | ACH-000790", - "Lung Neuroendocrine Tumor | ACH-000800", - "Lung Neuroendocrine Tumor | ACH-000866", - "Lung Neuroendocrine Tumor | ACH-000871", - "Lung Neuroendocrine Tumor | ACH-000890", - "Lung Neuroendocrine Tumor | ACH-000912", - "Lung Neuroendocrine Tumor | ACH-001386", - "Lung Neuroendocrine Tumor | ACH-001549", - "Lung Neuroendocrine Tumor | ACH-002051", - "Lung Neuroendocrine Tumor | ACH-002052", - "Lung Neuroendocrine Tumor | ACH-002077" - ], - "type": "scattergl", - "x": { - "bdata": "v60WP1hRub4G5NQ+k1ZWQNpHVECeBZE7p+yev4/PDEBR15w/uLiAvw4kOUDpLlG/k4riPxzn6j+RSKG/inv7P39cE0BmUQBAeypAQADJOkA8Olk/LC0pQMQi3704ydE+Cgvzv96bf7/PwYa/", - "dtype": "f4" - }, - "y": { - "bdata": "iZ8pwNhWvr840gXA1OmiPhRzBr8wiW+/pfLav5u6X7/r2bG/AGiuv1SXDsDVg36/g6UewLpKa77t1/m/Ljf4vrkQoL9JjFA/cnazv12ynr8uywdAcY8HP391w79Adau/u/jKv+rm6L+rpWS/", - "dtype": "f4" - } - }, - { - "customdata": [ - 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"Endometrial Carcinoma | ACH-000941", - "Endometrial Carcinoma | ACH-000946", - "Endometrial Carcinoma | ACH-000961", - "Endometrial Carcinoma | ACH-000965", - "Endometrial Carcinoma | ACH-000972", - "Endometrial Carcinoma | ACH-000974", - "Endometrial Carcinoma | ACH-000978", - "Endometrial Carcinoma | ACH-000984", - "Endometrial Carcinoma | ACH-000988", - "Endometrial Carcinoma | ACH-000993", - "Endometrial Carcinoma | ACH-000994", - "Endometrial Carcinoma | ACH-000996", - "Endometrial Carcinoma | ACH-001495", - "Endometrial Carcinoma | ACH-001517", - "Endometrial Carcinoma | ACH-001518", - "Endometrial Carcinoma | ACH-002026", - "Endometrial Carcinoma | ACH-002027", - "Endometrial Carcinoma | ACH-002046" - ], - "type": "scattergl", - "x": { - "bdata": "Y1IewEPDAsDLISE+GpczP8fQiD82IAs+x1b1wP/pdD/V/CJAhF9KQDL5jb/V0QtAfgs4QD2jcEDKcPXAPfMxQJVcbj+yhW2/S9tOP6vEhz+CZ/XAZF3RPp0kHL8FHSjAQqf1wLxyKkD09co/oaoSPw==", - "dtype": "f4" - }, - "y": { - "bdata": 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Carcinoma | ACH-000493", - "Hepatocellular Carcinoma | ACH-000537", - "Hepatocellular Carcinoma | ACH-000577", - "Hepatocellular Carcinoma | ACH-000620", - "Hepatocellular Carcinoma | ACH-000734", - "Hepatocellular Carcinoma | ACH-000848", - "Hepatocellular Carcinoma | ACH-001318", - "Hepatocellular Carcinoma | ACH-002523" - ], - "type": "scattergl", - "x": { - "bdata": "JCnUP9pFVUBKWcw/YsavP26grL+hdeG+UjkPQJvqnj851AxAj1wSv9meQT71JyxARB9tvyHdUT+m37c//D3zv0Tloj9Z/jxA7DtEQKam9T+iDPQ/", - "dtype": "f4" - }, - "y": { - "bdata": "4f8QPtPO377vozxAypmIP/Hf6z8NK+o/y7Y+QGxPDEC7JC09weWlPgX8/D9Ey4A/KxLrP4hbDECtX8Y/uH+mP25HgL6yqTS/Bpc6vxlLVD5iA0BA", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000305", - "ACH-000318", - "ACH-000408", - "ACH-000452", - "ACH-000488", - "ACH-000544", - "ACH-000561", - "ACH-000605", - "ACH-000637", - "ACH-000647", - "ACH-000693", - "ACH-000694", - "ACH-000717", - "ACH-000777", - "ACH-000784", - "ACH-000809", - "ACH-000823", - "ACH-000824", - "ACH-000855", - 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Squamous Cell Carcinoma | ACH-000784", - "Esophageal Squamous Cell Carcinoma | ACH-000809", - "Esophageal Squamous Cell Carcinoma | ACH-000823", - "Esophageal Squamous Cell Carcinoma | ACH-000824", - "Esophageal Squamous Cell Carcinoma | ACH-000855", - "Esophageal Squamous Cell Carcinoma | ACH-000865", - "Esophageal Squamous Cell Carcinoma | ACH-000873", - "Esophageal Squamous Cell Carcinoma | ACH-000917", - "Esophageal Squamous Cell Carcinoma | ACH-002243", - "Esophageal Squamous Cell Carcinoma | ACH-002263" - ], - "type": "scattergl", - "x": { - "bdata": "B89eP+s5JUCKxjlAUiRRP+F/eEC+5jdAqmXiP2Tb2j99/Lo/69QfPRltgUAGHBpA1aqqP/fCMEC9HChANmlmQHGvP0DdxBVA1VddQAYcQ0CI4VFAyRIsQLJmEEAtSD1A", - "dtype": "f4" - }, - "y": { - "bdata": "7Ba9Pnq/kz5m/qk+/P2XP1BuCr94QFs/67Hgvvr5Kz9wFqc/ELxHvdgVLT4vTHE+mKBDP/JiDz8mY5s+urSmvgSfC77hh0c/E+voPkTflz9Jb9K+bzYmvwxPoj98w/e+", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000456" - ], - "hoverinfo": "text", - "marker": { - "color": "#B68100", - 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"lightgrey" - }, - { - "color": "lightgrey" - } - ], - "visible": [ - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true - ] - }, - { - "title": "PCA Highlighted: Chordoma" - } - ], - "label": "Chordoma", - "method": "update" - }, - { - "args": [ - { - "marker": [ - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - 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"lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "#0DF9FF" - }, - { - "color": "lightgrey" - } - ], - "visible": [ - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true - ] - }, - { - "title": "PCA Highlighted: Head and Neck Carcinoma, Other" - } - ], - "label": "Head and Neck Carcinoma, Other", - "method": "update" - }, - { - "args": [ - { - "marker": [ - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - 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"color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "#F6F926" - } - ], - "visible": [ - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true - ] - }, - { - "title": "PCA Highlighted: Salivary Carcinoma" - } - ], - "label": "Salivary Carcinoma", - "method": "update" - } - ], - "direction": "down", - "showactive": true, - "x": 1.15, - "xanchor": "left", - "y": 1.15, - "yanchor": "top" - } - ], - "width": 1500, - "xaxis": { - "title": { - "text": "PCA1" - } - }, - "yaxis": { - "title": { - "text": "PCA2" - } - } - } - } - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "92e3889c12d5473f886a52d78b22ca39", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Output()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Assuming combined_df is your full dataset\n", - "reactome_fig, reactome_out = make_dropdown_pca_with_selection(\n", - " reactome_matrix, \"PCA: Reactome Subset\"\n", - ")\n", - "corum_fig, corum_out = make_dropdown_pca_with_selection(\n", - " corum_matrix, \"PCA: CORUM Subset\"\n", - ")\n", - "drug_fig, drug_out = make_dropdown_pca_with_selection(drug_matrix, \"PCA: Drug Subset\")\n", - "\n", - "# Show plots\n", - "reactome_fig.show()\n", - "display(reactome_out)\n", - "\n", - "corum_fig.show()\n", - "display(corum_out)\n", - "\n", - "drug_fig.show()\n", - "display(drug_out)\n", - "\n", - "# Save HTMLs\n", - "reactome_fig.write_html(\"pca_reactome.html\")\n", - "corum_fig.write_html(\"pca_corum.html\")\n", - "drug_fig.write_html(\"pca_drug.html\")" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "abstract_embedding", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.14" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/9.webapp/8.spider_plots.ipynb b/9.webapp/8.spider_plots.ipynb deleted file mode 100644 index 829b73e..0000000 --- a/9.webapp/8.spider_plots.ipynb +++ /dev/null @@ -1,266 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "d32e077c", - "metadata": {}, - "outputs": [], - "source": [ - "import textwrap\n", - "\n", - "import matplotlib.pyplot as plt\n", - "import numpy as np\n", - "import pandas as pd" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "4e20869b", - "metadata": {}, - "outputs": [], - "source": [ - "model_ids = [\"ACH-000323\", \"ACH-002083\", \"ACH-002228\"]\n", - "files = {\n", - " \"Reactome Pathways\": \"../5.drug-dependency/results/all_reactome_results.parquet\",\n", - " \"CORUM Complexes\": \"../5.drug-dependency/results/all_corum_results.parquet\",\n", - " \"Drug Responses\": \"../5.drug-dependency/results/all_drug_results.parquet\",\n", - "}\n", - "# Adjust these if your column names differ\n", - "feature_colnames = {\n", - " \"Reactome Pathways\": \"reactome_pathway\",\n", - " \"CORUM Complexes\": \"reactome_pathway\",\n", - " \"Drug Responses\": \"name\",\n", - "}\n", - "score_col = \"pathway_score\"\n", - "\n", - "model_colors = {\n", - " \"ACH-000323\": \"#00FFFF\", # cyan\n", - " \"ACH-002083\": \"#FF69B4\", # pink\n", - " \"ACH-002228\": \"#800080\", # purple\n", - "}" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "08894e82", - "metadata": {}, - "outputs": [], - "source": [ - "def clean_label(x: str) -> str:\n", - " \"\"\"\n", - " Clean or override specific long labels before truncation.\n", - " \"\"\"\n", - " # Polymerase switching\n", - " if \"Polymerase Switching\" in x:\n", - " return \"Polymerase Switching\"\n", - "\n", - " # Negative MET regulation\n", - " if \"Negative Regulation Of MET\" in x or \"Negative Regulation of MET\" in x:\n", - " return \"Negative MET Regulation\"\n", - "\n", - " return truncate_label(x)\n", - "\n", - "\n", - "def truncate_label(\n", - " label: str,\n", - " max_chars_per_line: int = 22,\n", - " max_total_words: int = 4,\n", - " max_lines: int = 2,\n", - ") -> str:\n", - " \"\"\"\n", - " Truncate a label according to character and line limits.\n", - " \"\"\"\n", - " words = label.split()\n", - " short = \" \".join(words[:max_total_words])\n", - "\n", - " # Wrap\n", - " lines = textwrap.wrap(short, width=max_chars_per_line)\n", - "\n", - " # clamp to max lines\n", - " if len(lines) > max_lines:\n", - " lines = lines[:max_lines]\n", - "\n", - " wrapped = \"\\n\".join(lines)\n", - "\n", - " # Determine if truncated\n", - " if len(words) > max_total_words or (\n", - " len(lines) >= max_lines\n", - " and len(lines) < len(textwrap.wrap(short, width=max_chars_per_line))\n", - " ):\n", - " wrapped += \"...\"\n", - "\n", - " return wrapped\n", - "\n", - "\n", - "def place_labels_polar(ax, angles, labels, radius: float) -> None:\n", - " \"\"\"\n", - " Place labels around a polar plot at a given radius.\n", - " \"\"\"\n", - " for angle, label in zip(angles[:-1], labels):\n", - " r = radius\n", - "\n", - " # left / right alignment\n", - " if 0 <= angle <= np.pi / 2 or 3 * np.pi / 2 <= angle <= 2 * np.pi:\n", - " ha = \"left\"\n", - " else:\n", - " ha = \"right\"\n", - "\n", - " ax.text(\n", - " angle, r, label, fontsize=9, color=\"black\", ha=ha, va=\"center\", wrap=True\n", - " )\n", - "\n", - " return None\n", - "\n", - "\n", - "def make_radar(\n", - " ax,\n", - " df: pd.DataFrame,\n", - " feature_col: str,\n", - " title: str,\n", - " global_max: float,\n", - " num_circles: int = 5,\n", - ") -> None:\n", - " \"\"\"\n", - " Draw a radar plot on an existing polar matplotlib axis.\n", - " \"\"\"\n", - " df = df[df[\"ModelID\"].isin(model_ids)].copy()\n", - "\n", - " # Top 5 per model, union of all\n", - " top_by_model = (\n", - " df.groupby(\"ModelID\", group_keys=False)\n", - " .apply(lambda x: x.nlargest(5, score_col))\n", - " .reset_index(drop=True)\n", - " )\n", - " top_features = top_by_model[feature_col].drop_duplicates().tolist()\n", - " n_vars = len(top_features)\n", - " labels = [clean_label(x) for x in top_features]\n", - "\n", - " # Angles\n", - " angles = np.linspace(0, 2 * np.pi, n_vars, endpoint=False).tolist()\n", - " angles += [angles[0]]\n", - "\n", - " # Reference circles\n", - " circle_levels = np.linspace(0, global_max, num_circles + 1)[1:]\n", - " for r in circle_levels:\n", - " circle_vals = [r] * (n_vars + 1)\n", - " ax.plot(\n", - " angles, circle_vals, color=\"grey\", linestyle=\"--\", linewidth=1, zorder=0\n", - " )\n", - "\n", - " # Plot each model\n", - " for mid in model_ids:\n", - " subset = df[df[\"ModelID\"] == mid]\n", - "\n", - " merged = pd.DataFrame({feature_col: top_features}).merge(\n", - " subset[[feature_col, score_col]], on=feature_col, how=\"left\"\n", - " )\n", - "\n", - " values = merged[score_col].fillna(0).tolist()\n", - " values += [values[0]]\n", - "\n", - " ax.plot(angles, values, color=model_colors[mid], linewidth=3, label=mid)\n", - " ax.scatter(\n", - " angles, values, color=model_colors[mid], s=30, edgecolor=\"black\", zorder=5\n", - " )\n", - "\n", - " # Axis styling\n", - " ax.set_ylim(0, global_max * 1.25)\n", - " ax.set_xticks([])\n", - " ax.set_yticks([])\n", - " ax.set_aspect(\"equal\")\n", - "\n", - " # Labels\n", - " label_radius = global_max * 1.4\n", - " place_labels_polar(ax, angles, labels, label_radius)\n", - "\n", - " # Title\n", - " ax.set_title(title, fontsize=18, pad=30, fontweight=\"bold\", y=1)\n", - "\n", - " return None" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "fb8024f8", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
    " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "global_max = 0\n", - "dfs = {}\n", - "for name, file in files.items():\n", - " df = pd.read_parquet(file)\n", - " dfs[name] = df\n", - " if df[score_col].max() > global_max:\n", - " global_max = df[score_col].max()\n", - "\n", - "# --- Create one combined figure ---\n", - "fig, axes = plt.subplots(3, 1, figsize=(18, 12), subplot_kw=dict(polar=True))\n", - "\n", - "for ax, (title, df) in zip(axes, dfs.items()):\n", - " make_radar(ax, df, feature_colnames[title], title, global_max)\n", - "\n", - "# Shared legend (one for all)\n", - "handles, labels = axes[0].get_legend_handles_labels()\n", - "\n", - "fig.legend(\n", - " handles,\n", - " labels,\n", - " loc=\"lower center\",\n", - " ncol=3,\n", - " fontsize=12,\n", - " frameon=False,\n", - " bbox_to_anchor=(0.5, -0.05),\n", - ")\n", - "\n", - "plt.tight_layout(rect=[0, 0, 1, 0.95])\n", - "# plt.savefig(\"visualize/combined_radar_plots.png\", dpi=600,\n", - "# bbox_inches=\"tight\", transparent=True)\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "301ec03f", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": ".venv (3.13.1)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.13.1" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/9.webapp/app.py b/9.webapp/app.py index 0ff286f..574024a 100644 --- a/9.webapp/app.py +++ b/9.webapp/app.py @@ -1,31 +1,14 @@ """ Gene Process Dependency Explorer -Streamlit app for exploring DepMap gene dependency latent representations. -Reproduces the analysis pattern from: - - WayScience/gene-process-dependencies 8.shiny-app/1.latent-pcas.ipynb (PCA plots) - - WayScience/gene-process-dependencies 5.drug-dependency/8.spider_plots.ipynb (spider plots) - -Data schema mirrors the real DepMap / BioBombe outputs: - - Models: PCA, ICA, NMF, DAE, VAE, β-VAE, β-TCVAE - - Metadata: primary_disease, lineage, cell_line (CCLE name) - - PCA columns: pca_1, pca_2 (per model + latent_dim) - - Spider columns: mean dependency score per biological process category """ -import colorsys -import pathlib -import random -import sys import textwrap -import ipywidgets as widgets -import joblib import matplotlib.pyplot as plt import numpy as np import pandas as pd import plotly.express as px import plotly.graph_objects as go -import plotly.graph_objs as go import streamlit as st from app_utils import ( clean_label, @@ -49,10 +32,9 @@ page_title="Gene Process Dependency Explorer", page_icon="🧬", layout="wide", - initial_sidebar_state="expanded", + initial_sidebar_state="collapsed", ) - # ── Styling ─────────────────────────────────────────────────────────────────── st.markdown( """ @@ -60,7 +42,6 @@ @import url('https://fonts.googleapis.com/css2?family=IBM+Plex+Mono:wght@400;600&family=IBM+Plex+Sans:wght@300;400;600&display=swap'); html, body, [class*="css"] { font-family: 'IBM Plex Sans', sans-serif; } - .stApp { background: #0d1117; color: #e6edf3; } .metric-card { @@ -73,6 +54,22 @@ .metric-label { font-size: 11px; color: #8b949e; text-transform: uppercase; letter-spacing: 1px; } .metric-value { font-size: 28px; font-weight: 600; color: #58a6ff; font-family: 'IBM Plex Mono', monospace; } + .control-panel { + background: #161b22; + border: 1px solid #21262d; + border-radius: 8px; + padding: 16px 20px; + margin-bottom: 20px; + } + .control-label { + font-size: 11px; + color: #8b949e; + font-family: 'IBM Plex Mono', monospace; + text-transform: uppercase; + letter-spacing: 0.5px; + margin-bottom: 4px; + } + h1, h2, h3 { font-family: 'IBM Plex Mono', monospace !important; } h1 { color: #58a6ff !important; font-size: 1.6rem !important; } h2 { color: #79c0ff !important; font-size: 1.1rem !important; } @@ -90,21 +87,6 @@ margin-bottom: 12px; } - div[data-testid="stSidebar"] { - background: #010409 !important; - border-right: 1px solid #21262d !important; - } - - div[data-testid="stSidebar"] .stSelectbox label, - div[data-testid="stSidebar"] .stMultiSelect label, - div[data-testid="stSidebar"] .stSlider label { - color: #8b949e !important; - font-size: 12px !important; - font-family: 'IBM Plex Mono', monospace !important; - text-transform: uppercase; - letter-spacing: 0.5px; - } - .stTabs [data-baseweb="tab-list"] { gap: 8px; } .stTabs [data-baseweb="tab"] { background: #161b22; @@ -125,172 +107,125 @@ unsafe_allow_html=True, ) +# ── Header ──────────────────────────────────────────────────────────────────── +st.markdown("# Gene Process Dependency Explorer") +st.markdown( + 'DepMap · BioBombe · WayScience', + unsafe_allow_html=True, +) -# ── Sidebar controls ────────────────────────────────────────────────────────── -with st.sidebar: - st.markdown("## 🧬 Selections") - st.markdown("---") - reactome_matrix, corum_matrix, drug_matrix = latent_load_data() +# ── Load base data once (cheap — just for disease list) ─────────────────────── +_base_reactome, _base_corum, _base_drug = latent_load_data() +ALL_DISEASES = sorted(_base_reactome["OncotreePrimaryDisease"].unique().tolist()) +ALL_MODEL_IDS = sorted(_base_reactome["ModelID"].unique().tolist()) +DEFAULT_MODEL_IDS = ["ACH-000323", "ACH-002083", "ACH-002228"] + +# ── Tabs ────────────────────────────────────────────────────────────────────── +( + tab_welcome, + tab_single, + tab_latent, + tab_spider, + tab_scores, + tab_table, +) = st.tabs( + [ + "📖 Welcome", + "📍 Single dependency plots", + "📍 Latent plots", + "🕷 Spider plots", + "📊 Top scores", + "📋 Data table", + ] +) - # ── Disease selector ────────────────────────────────────────────── - all_diseases = list(reactome_matrix["OncotreePrimaryDisease"].unique()) +# ── Helpers ─────────────────────────────────────────────────────────────────── +def disease_controls(key_prefix: str, default_all: bool = True) -> list[str]: + """Render an All / None button pair + multiselect for disease filtering.""" st.markdown( - "Primary diseases", - unsafe_allow_html=True, + '
    Primary diseases
    ', unsafe_allow_html=True ) - col_d1, col_d2 = st.columns(2) - if col_d1.button("All", key="disease_all", use_container_width=True): - st.session_state["diseases"] = all_diseases - if col_d2.button("None", key="disease_none", use_container_width=True): - st.session_state["diseases"] = [] - - selected_diseases = st.multiselect( + ca, cn = st.columns(2) + if ca.button("All", key=f"{key_prefix}_dis_all", use_container_width=True): + st.session_state[f"{key_prefix}_diseases"] = ALL_DISEASES + if cn.button("None", key=f"{key_prefix}_dis_none", use_container_width=True): + st.session_state[f"{key_prefix}_diseases"] = [] + return st.multiselect( "Primary diseases", - all_diseases, - default=st.session_state.get("diseases", all_diseases), + ALL_DISEASES, + default=st.session_state.get( + f"{key_prefix}_diseases", ALL_DISEASES if default_all else [] + ), label_visibility="collapsed", - key="diseases", + key=f"{key_prefix}_diseases", ) - st.markdown("---") - # ── Model ID selector ───────────────────────────────────────────── - DEFAULT_MODEL_IDS = ["ACH-000323", "ACH-002083", "ACH-002228"] - all_model_ids = list(reactome_matrix["ModelID"].unique()) - - st.markdown( - "ModelIDs (spider plots)", - unsafe_allow_html=True, - ) - col_m1, col_m2, col_m3 = st.columns(3) - if col_m1.button("All", key="model_all", use_container_width=True): - st.session_state["model_ids"] = all_model_ids - if col_m2.button("None", key="model_none", use_container_width=True): - st.session_state["model_ids"] = [] - if col_m3.button("Default", key="model_default", use_container_width=True): - st.session_state["model_ids"] = DEFAULT_MODEL_IDS - - model_ids = st.multiselect( - "ModelIds (for spider plots)", - all_model_ids, - default=st.session_state.get("model_ids", DEFAULT_MODEL_IDS), +def model_id_controls(key_prefix: str) -> list[str]: + """Render All / None / Default buttons + multiselect for ModelID filtering.""" + st.markdown('
    Model IDs
    ', unsafe_allow_html=True) + ca, cn, cd = st.columns(3) + if ca.button("All", key=f"{key_prefix}_mod_all", use_container_width=True): + st.session_state[f"{key_prefix}_model_ids"] = ALL_MODEL_IDS + if cn.button("None", key=f"{key_prefix}_mod_none", use_container_width=True): + st.session_state[f"{key_prefix}_model_ids"] = [] + if cd.button("Default", key=f"{key_prefix}_mod_default", use_container_width=True): + st.session_state[f"{key_prefix}_model_ids"] = DEFAULT_MODEL_IDS + return st.multiselect( + "Model IDs", + ALL_MODEL_IDS, + default=st.session_state.get(f"{key_prefix}_model_ids", DEFAULT_MODEL_IDS), label_visibility="collapsed", - key="model_ids", + key=f"{key_prefix}_model_ids", ) - st.markdown("---") - # ── Spider plot process limit ───────────────────────────────────── +# ──────────────────────────────────────────────────────────────────────────── +# TAB 0 — Intro text +# ──────────────────────────────────────────────────────────────────────────── +with tab_welcome: + st.markdown("## Welcome to the Gene Process Dependency Explorer") st.markdown( - "Spider plot — max processes", - unsafe_allow_html=True, + "This app allows you to explore gene process dependencies across different cancer types and model IDs." ) - - limit_processes = st.toggle("Limit axes", value=False, key="limit_processes") - - if limit_processes: - max_processes = st.slider( - "Max processes per plot", - min_value=3, - max_value=20, - value=20, - step=1, - label_visibility="collapsed", - ) - else: - max_processes = None # signals downstream: show all - - st.markdown("---") st.markdown( - 'Data: DepMap synthetic (mirrors WayScience/gene-process-dependencies schema)', - unsafe_allow_html=True, + "We are visualizing latent representations of gene dependencies learned by a compression model trained on DepMap data, with biological processes as features." ) - -# ── Header ──────────────────────────────────────────────────────────────────── -st.markdown("# Gene Process Dependency Explorer") -st.markdown( - 'DepMap · BioBombe · WayScience', - unsafe_allow_html=True, -) - - -# ── Tabs ────────────────────────────────────────────────────────────────────── -tab_single, tab_latent, tab_spider, tab_scores, tab_table = st.tabs( - [ - "📍 single dependency plots", - "📍 latent plots", - "🕷 Spider Plots", - "📊 Top Scores", - "📋 Data Table", - ] -) - -# ───────────────────────────────────────────────────────────────────────────── -# TAB 1: PCA -# ───────────────────────────────────────────────────────────────────────────── -with tab_latent: - st.markdown("### Latent Space PCA Projections") st.markdown( - "PCA projection of latent representations learned by the selected compression model. " - "Each point is a cancer cell line; clusters indicate similar gene dependency profiles." - ) - - reactome_matrix, corum_matrix, drug_matrix = latent_load_data() - # add a way to show all diseases or select specific ones - - reactome_matrix = reactome_matrix[ - reactome_matrix["OncotreePrimaryDisease"].isin(selected_diseases) - ] - corum_matrix = corum_matrix[ - corum_matrix["OncotreePrimaryDisease"].isin(selected_diseases) - ] - drug_matrix = drug_matrix[ - drug_matrix["OncotreePrimaryDisease"].isin(selected_diseases) - ] - # Assuming combined_df is your full dataset - reactome_fig, reactome_out = make_dropdown_pca_with_selection( - reactome_matrix, "PCA: Reactome Subset" - ) - corum_fig, corum_out = make_dropdown_pca_with_selection( - corum_matrix, "PCA: CORUM Subset" + "For more details on the data and methods, please see our github repository: https://github.com/WayScience/gene-process-dependencies" ) - drug_fig, drug_out = make_dropdown_pca_with_selection( - drug_matrix, "PCA: Drug Subset" + st.markdown( + "For more information about the group, please visit the WayScience website: https://wayscience.com" ) - st.plotly_chart(reactome_fig, use_container_width=True) - st.plotly_chart(corum_fig, use_container_width=True) - st.plotly_chart(drug_fig, use_container_width=True) - - + st.markdown("---") # ───────────────────────────────────────────────────────────────────────────── -# TAB 2: PCA single +# TAB 1 — Single dependency plots # ───────────────────────────────────────────────────────────────────────────── with tab_single: - st.markdown("### Latent Space PCA Projections") + st.markdown("### Latent Space PCA — single dependency") st.markdown( - "PCA projection of latent representations learned by the selected compression model. " - "Each point is a cancer cell line; clusters indicate similar gene dependency profiles." + "PCA projection of raw gene dependency scores. " + "Each point is a cancer cell line; colour encodes primary disease." ) - # st.markdown("**(Placeholder for latent space PCA plots)**") + + with st.container(): + st.markdown('
    ', unsafe_allow_html=True) + selected_diseases_single = disease_controls("single") + st.markdown("
    ", unsafe_allow_html=True) combined_df = single_load_data() combined_df = combined_df[ - combined_df["OncotreePrimaryDisease"].isin(selected_diseases) + combined_df["OncotreePrimaryDisease"].isin(selected_diseases_single) ] - gene_cols = combined_df.columns.drop("ModelID") - gene_cols = gene_cols.drop("OncotreePrimaryDisease") - # Prepare PCA input (excluding non-numeric columns) + gene_cols = combined_df.columns.drop(["ModelID", "OncotreePrimaryDisease"]) pca_input = combined_df[gene_cols].apply(pd.to_numeric, errors="coerce") pca = PCA(n_components=2, random_state=0) pca_embedding = pca.fit_transform(pca_input) - - # Add PCA components to the dataframe combined_df["PCA1"] = pca_embedding[:, 0] combined_df["PCA2"] = pca_embedding[:, 1] - # Prepare color map for each cancer type cancer_types = combined_df["OncotreePrimaryDisease"].unique() color_map = ( px.colors.qualitative.Plotly @@ -298,70 +233,130 @@ + px.colors.qualitative.Dark24 ) highlight_color_map = { - cancer: color_map[i % len(color_map)] for i, cancer in enumerate(cancer_types) + c: color_map[i % len(color_map)] for i, c in enumerate(cancer_types) } - default_colors = [highlight_color_map[cancer] for cancer in cancer_types] - # Create one trace per cancer type traces = [] for cancer in cancer_types: - df_subset = combined_df[combined_df["OncotreePrimaryDisease"] == cancer] - trace = go.Scatter( - x=df_subset["PCA1"], - y=df_subset["PCA2"], - mode="markers", - name=cancer, - marker=dict(size=7), - text=[f"{cancer} | {model_id}" for model_id in df_subset["ModelID"]], - hoverinfo="text", + df_sub = combined_df[combined_df["OncotreePrimaryDisease"] == cancer] + traces.append( + go.Scatter( + x=df_sub["PCA1"], + y=df_sub["PCA2"], + mode="markers", + name=cancer, + marker=dict(size=7, color=highlight_color_map[cancer]), + text=[f"{cancer} | {m}" for m in df_sub["ModelID"]], + hoverinfo="text", + ) ) - traces.append(trace) - import plotly.graph_objects as go - import streamlit as st - # Create the figure - fig = go.Figure(data=traces) + fig_single = go.Figure(data=traces) + fig_single.update_layout( + paper_bgcolor="#0d1117", + plot_bgcolor="#0d1117", + font=dict(color="#e6edf3"), + xaxis=dict(gridcolor="#21262d"), + yaxis=dict(gridcolor="#21262d"), + legend=dict(bgcolor="#161b22", bordercolor="#30363d", borderwidth=1), + height=1200, + margin=dict(l=40, r=40, t=40, b=40), + width=800, + ) + st.plotly_chart(fig_single, use_container_width=True) - # Set default colors - for i, trace in enumerate(fig.data): - trace.marker.color = default_colors[i] - st.plotly_chart(fig, use_container_width=True) - # fig.write_html("achilles_pca.html") +# ───────────────────────────────────────────────────────────────────────────── +# TAB 2 — Latent plots +# ───────────────────────────────────────────────────────────────────────────── +with tab_latent: + st.markdown("### Latent Space PCA Projections") + st.markdown( + "PCA projection of latent representations learned by the selected compression model. " + "Each point is a cancer cell line; clusters indicate similar gene dependency profiles." + ) + + with st.container(): + st.markdown('
    ', unsafe_allow_html=True) + selected_diseases_latent = disease_controls("latent") + st.markdown("
    ", unsafe_allow_html=True) + + reactome_matrix, corum_matrix, drug_matrix = latent_load_data() + reactome_matrix = reactome_matrix[ + reactome_matrix["OncotreePrimaryDisease"].isin(selected_diseases_latent) + ] + corum_matrix = corum_matrix[ + corum_matrix["OncotreePrimaryDisease"].isin(selected_diseases_latent) + ] + drug_matrix = drug_matrix[ + drug_matrix["OncotreePrimaryDisease"].isin(selected_diseases_latent) + ] + + reactome_fig, _ = make_dropdown_pca_with_selection( + reactome_matrix, "PCA: Reactome Subset" + ) + corum_fig, _ = make_dropdown_pca_with_selection(corum_matrix, "PCA: CORUM Subset") + drug_fig, _ = make_dropdown_pca_with_selection(drug_matrix, "PCA: Drug Subset") + + st.plotly_chart(reactome_fig, use_container_width=True) + st.plotly_chart(corum_fig, use_container_width=True) + st.plotly_chart(drug_fig, use_container_width=True) + # ───────────────────────────────────────────────────────────────────────────── -# TAB 3: Spider / Radar plots +# TAB 3 — Spider plots # ───────────────────────────────────────────────────────────────────────────── with tab_spider: st.markdown("### Biological Process Dependency Profiles — Spider Plots") st.markdown( - "Mean dependency score per biological process category for selected diseases. " - "Negative scores indicate stronger dependencies (essential genes). " - "Each axis = one process; the profile shape captures cancer-type-specific vulnerabilities." + "Mean dependency score per biological process category for selected cell lines. " + "Negative scores indicate stronger dependencies (essential genes)." ) - dfs, global_max, feature_colnames = spider_load_data() + with st.container(): + st.markdown('
    ', unsafe_allow_html=True) + sp_c1, sp_c2 = st.columns(2) + with sp_c1: + model_ids_spider = model_id_controls("spider") + with sp_c2: + st.markdown( + '
    Process limit
    ', unsafe_allow_html=True + ) + limit_processes = st.toggle( + "Limit axes", value=False, key="spider_limit_toggle" + ) + if limit_processes: + max_processes = st.slider( + "Max processes per plot", + min_value=3, + max_value=50, + value=20, + step=1, + key="spider_max_proc", + label_visibility="collapsed", + ) + else: + max_processes = None + st.markdown("
    ", unsafe_allow_html=True) - fig, axes = plt.subplots(3, 1, figsize=(18, 12), subplot_kw=dict(polar=True)) + dfs, global_max, feature_colnames = spider_load_data() + fig_spider, axes = plt.subplots(3, 1, figsize=(18, 12), subplot_kw=dict(polar=True)) for ax, (title, df) in zip(axes, dfs.items()): - df = df[df["ModelID"].isin(model_ids)].copy() - - # Apply process limit if set + df = df[df["ModelID"].isin(model_ids_spider)].copy() cols = feature_colnames[title] - make_radar( ax, df, cols, title, global_max, - model_ids=model_ids, + model_ids=model_ids_spider, max_processes=max_processes, ) handles, labels = axes[0].get_legend_handles_labels() - fig.legend( + fig_spider.legend( handles, labels, loc="lower center", @@ -370,18 +365,17 @@ frameon=False, bbox_to_anchor=(0.5, -0.05), ) - plt.tight_layout(rect=[0, 0, 1, 0.95]) - st.pyplot(fig) + st.pyplot(fig_spider) + # ───────────────────────────────────────────────────────────────────────────── -# TAB 4: Top Scores +# TAB 4 — Top scores # ───────────────────────────────────────────────────────────────────────────── with tab_scores: st.markdown("### Top Dependency Scores") st.markdown( - "Visualize the highest-scoring biological processes across cancer types and individual cell lines. " - "Use the controls below to tune how many processes, cancer types, and model IDs are shown." + "Highest-scoring biological processes across cancer types and individual cell lines." ) reactome_matrix, corum_matrix, drug_matrix = latent_load_data() @@ -391,75 +385,74 @@ "Drug": drug_matrix, } - # ── Controls ────────────────────────────────────────────────────── - sc1, sc2, sc3, sc4 = st.columns(4) - with sc1: - scores_dataset = st.selectbox( - "Dataset", - options=["Reactome", "CORUM", "Drug"], - key="scores_dataset", - ) - with sc2: - top_n_scores = st.slider( - "Top N processes", - min_value=3, - max_value=50, - value=15, - step=1, - key="scores_top_n", - ) - with sc3: - top_m_types = st.slider( - "Top M cancer types", - min_value=1, - max_value=30, - value=8, - step=1, - key="scores_top_m", - ) - with sc4: - top_i_models = st.slider( - "Top I model IDs", - min_value=1, - max_value=30, - value=8, - step=1, - key="scores_top_i", - ) + with st.container(): + st.markdown('
    ', unsafe_allow_html=True) + ctl1, ctl2, ctl3, ctl4, ctl5 = st.columns(5) + with ctl1: + selected_diseases_scores = disease_controls("scores") + with ctl2: + scores_dataset = st.selectbox( + "Dataset", + options=["Reactome", "CORUM", "Drug"], + key="scores_dataset", + ) + with ctl3: + top_n_scores = st.slider( + "Top N processes", + min_value=3, + max_value=50, + value=15, + step=1, + key="scores_top_n", + ) + with ctl4: + top_m_types = st.slider( + "Top M cancer types", + min_value=1, + max_value=len(selected_diseases_scores), + value=8, + step=1, + key="scores_top_m", + ) + with ctl5: + top_i_models = st.slider( + "Top I model IDs", + min_value=1, + max_value=30, + value=8, + step=1, + key="scores_top_i", + ) + st.markdown("
    ", unsafe_allow_html=True) score_df = all_matrices[scores_dataset].copy() - score_df = score_df[score_df["OncotreePrimaryDisease"].isin(selected_diseases)] - + score_df = score_df[ + score_df["OncotreePrimaryDisease"].isin(selected_diseases_scores) + ] meta_cols = ["ModelID", "OncotreePrimaryDisease"] score_cols = [c for c in score_df.columns if c not in meta_cols] - # ── Plot 1: top N processes × top M cancer types ────────────────── + # ── Heatmap: cancer types ───────────────────────────────────────── st.markdown("---") st.markdown("#### By cancer type") st.markdown( - "Mean dependency score per process, averaged across all cell lines in each cancer type. " - "Only the top N processes (by max mean score across shown cancer types) are displayed." + "Mean dependency score per process averaged across all cell lines in each cancer type. " + "Top N processes by max mean score across shown cancer types." ) - # Mean score per (disease, process) disease_means = ( score_df.groupby("OncotreePrimaryDisease")[score_cols].mean().reset_index() ) - - # Pick top M cancer types by their single highest mean score across all processes disease_means["_max"] = disease_means[score_cols].max(axis=1) top_diseases = disease_means.nlargest(top_m_types, "_max")[ "OncotreePrimaryDisease" ].tolist() disease_means = disease_means[ disease_means["OncotreePrimaryDisease"].isin(top_diseases) - ] - disease_means = disease_means.drop(columns=["_max"]) - - # Pick top N processes by max mean score across selected diseases - process_maxes = disease_means[score_cols].max(axis=0) - top_processes = process_maxes.nlargest(top_n_scores).index.tolist() - + ].drop(columns=["_max"]) + top_processes = ( + disease_means[score_cols].max(axis=0).nlargest(top_n_scores).index.tolist() + ) heatmap_disease = disease_means.set_index("OncotreePrimaryDisease")[top_processes] fig_disease = go.Figure( @@ -486,19 +479,16 @@ ) st.plotly_chart(fig_disease, use_container_width=True) - # ── Plot 2: top N processes × top I model IDs ───────────────────── + # ── Heatmap: model IDs ──────────────────────────────────────────── st.markdown("---") st.markdown("#### By model ID") st.markdown( - "Raw dependency score per process for individual cell lines. " - "Only the top I model IDs (by their single highest score across all processes) are shown." + "Raw dependency score per process for individual cell lines ranked by peak score." ) - # Pick top I models by max score across all processes score_df["_max"] = score_df[score_cols].max(axis=1) top_models = score_df.nlargest(top_i_models, "_max")["ModelID"].tolist() score_df = score_df.drop(columns=["_max"]) - model_df = score_df[score_df["ModelID"].isin(top_models)].set_index("ModelID")[ top_processes ] @@ -526,12 +516,10 @@ ) st.plotly_chart(fig_model, use_container_width=True) - # ── Bar charts: top N processes collapsed ───────────────────────── + # ── Bar charts ──────────────────────────────────────────────────── st.markdown("---") st.markdown("#### Overall top processes") - st.markdown( - "Global mean score per process across all cell lines in the filtered dataset, ranked." - ) + st.markdown("Global mean score per process across all filtered cell lines, ranked.") overall_means = score_df[score_cols].mean().nlargest(top_n_scores).reset_index() overall_means.columns = ["Process", "Mean Score"] @@ -541,8 +529,19 @@ bar1, bar2 = st.columns(2) + _bar_layout = dict( + margin=dict(l=10, r=10, t=40, b=20), + paper_bgcolor="#0d1117", + plot_bgcolor="#0d1117", + font=dict(color="#e6edf3", size=11), + yaxis=dict(autorange="reversed", gridcolor="#21262d"), + xaxis=dict(gridcolor="#21262d"), + coloraxis_showscale=False, + showlegend=False, + ) + with bar1: - fig_bar_d = px.bar( + fig_bar_all = px.bar( overall_means, x="Mean Score", y="Process", @@ -551,21 +550,12 @@ color="Mean Score", color_continuous_scale="Blues", ) - fig_bar_d.update_layout( - height=max(300, top_n_scores * 24 + 80), - margin=dict(l=10, r=10, t=40, b=20), - paper_bgcolor="#0d1117", - plot_bgcolor="#0d1117", - font=dict(color="#e6edf3", size=11), - yaxis=dict(autorange="reversed", gridcolor="#21262d"), - xaxis=dict(gridcolor="#21262d"), - coloraxis_showscale=False, - showlegend=False, + fig_bar_all.update_layout( + height=max(300, top_n_scores * 24 + 80), **_bar_layout ) - st.plotly_chart(fig_bar_d, use_container_width=True) + st.plotly_chart(fig_bar_all, use_container_width=True) with bar2: - # Same but restricted to the top-M diseases top_disease_means = ( score_df[score_df["OncotreePrimaryDisease"].isin(top_diseases)][score_cols] .mean() @@ -576,7 +566,7 @@ top_disease_means["Process"] = top_disease_means["Process"].apply( lambda p: textwrap.shorten(p, width=40, placeholder="…") ) - fig_bar_m = px.bar( + fig_bar_top = px.bar( top_disease_means, x="Mean Score", y="Process", @@ -585,52 +575,39 @@ color="Mean Score", color_continuous_scale="Purples", ) - fig_bar_m.update_layout( - height=max(300, top_n_scores * 24 + 80), - margin=dict(l=10, r=10, t=40, b=20), - paper_bgcolor="#0d1117", - plot_bgcolor="#0d1117", - font=dict(color="#e6edf3", size=11), - yaxis=dict(autorange="reversed", gridcolor="#21262d"), - xaxis=dict(gridcolor="#21262d"), - coloraxis_showscale=False, - showlegend=False, + fig_bar_top.update_layout( + height=max(300, top_n_scores * 24 + 80), **_bar_layout ) - st.plotly_chart(fig_bar_m, use_container_width=True) + st.plotly_chart(fig_bar_top, use_container_width=True) + # ───────────────────────────────────────────────────────────────────────────── -# TAB 5: Data Table +# TAB 5 — Data table # ───────────────────────────────────────────────────────────────────────────── with tab_table: st.markdown("### Cancer Types & Primary Diseases") - st.markdown( - "Summary of all cancer types and their associated primary diseases present in the dataset." - ) + st.markdown("Summary of all cancer types and their associated primary diseases.") - reactome_matrix, corum_matrix, drug_matrix = latent_load_data() + with st.container(): + st.markdown('
    ', unsafe_allow_html=True) + selected_diseases_table = disease_controls("table") + st.markdown("
    ", unsafe_allow_html=True) + + reactome_matrix, _, _ = latent_load_data() full_df = reactome_matrix[ - reactome_matrix["OncotreePrimaryDisease"].isin(selected_diseases) + reactome_matrix["OncotreePrimaryDisease"].isin(selected_diseases_table) ] - # Build summary: one row per unique (OncotreeLineage, OncotreePrimaryDisease) pair - # adjust column names below to match whatever lineage/cancer-type column your data actually has - group_cols = ["OncotreePrimaryDisease", "ModelID"] # ← rename if needed summary = ( - reactome_matrix.groupby(group_cols, dropna=False) - .agg(n_models=("ModelID", "nunique")) - .reset_index() - .sort_values(group_cols) - .rename( - columns={ - "OncotreePrimaryDisease": "Primary Disease", - "n_models": "Cell Lines", - } - ) - .drop(columns=["Cell Lines"]) + full_df.groupby(["OncotreePrimaryDisease", "ModelID"], dropna=False) + .size() + .reset_index(name="_n") + .drop(columns=["_n"]) .drop_duplicates() + .rename(columns={"OncotreePrimaryDisease": "Primary Disease"}) + .sort_values(["Primary Disease", "ModelID"]) ) - # ── Summary metrics ─────────────────────────────────────────────── m1, m2 = st.columns(2) m1.markdown( f'
    Primary diseases
    {summary["Primary Disease"].nunique()}
    ', @@ -642,14 +619,10 @@ ) st.markdown("") - # ── Sort controls ───────────────────────────────────────────────── sc1, sc2 = st.columns([3, 1]) with sc1: sort_by = st.selectbox( - "Sort by", - options=summary.columns.tolist(), - index=0, - key="table_sort_col", + "Sort by", options=summary.columns.tolist(), index=0, key="table_sort_col" ) with sc2: sort_asc = st.radio( @@ -662,20 +635,17 @@ summary = summary.sort_values(sort_by, ascending=(sort_asc == "Ascending")) - # ── Table ───────────────────────────────────────────────────────── st.dataframe( summary.reset_index(drop=True), use_container_width=True, height=560, column_config={ - "Lineage / Cancer Type": st.column_config.TextColumn(width="large"), "Primary Disease": st.column_config.TextColumn(width="large"), - "Cell Lines": st.column_config.NumberColumn(width="small", format="%d"), + "ModelID": st.column_config.TextColumn("Model ID", width="large"), }, hide_index=True, ) - # ── Download ────────────────────────────────────────────────────── st.download_button( label="⬇ Download as CSV", data=summary.to_csv(index=False).encode("utf-8"), diff --git a/9.webapp/requirements.txt b/9.webapp/requirements.txt new file mode 100644 index 0000000..0c47f25 --- /dev/null +++ b/9.webapp/requirements.txt @@ -0,0 +1,88 @@ +altair==6.1.0 +anyio==4.13.0 +asttokens==3.0.1 +attrs==26.1.0 +blinker==1.9.0 +cachetools==7.1.4 +certifi==2026.5.20 +charset-normalizer==3.4.7 +click==8.4.1 +comm==0.2.3 +contourpy==1.3.3 +cycler==0.12.1 +debugpy==1.8.21 +decorator==5.3.1 +executing==2.2.1 +fonttools==4.63.0 +-e file:///home/lippincm/gene-process-dependencies/9.webapp +gitdb==4.0.12 +gitpython==3.1.50 +h11==0.16.0 +httptools==0.8.0 +idna==3.18 +ipykernel==7.2.0 +ipython==9.14.1 +ipython-pygments-lexers==1.1.1 +ipywidgets==8.1.8 +itsdangerous==2.2.0 +jedi==0.20.0 +jinja2==3.1.6 +joblib==1.5.3 +jsonschema==4.26.0 +jsonschema-specifications==2025.9.1 +jupyter-client==8.9.0 +jupyter-core==5.9.1 +jupyterlab-widgets==3.0.16 +kiwisolver==1.5.0 +llvmlite==0.47.0 +markupsafe==3.0.3 +matplotlib==3.10.9 +matplotlib-inline==0.2.2 +narwhals==2.22.0 +nest-asyncio==1.6.0 +numba==0.65.1 +numpy==2.4.6 +packaging==26.2 +pandas==3.0.3 +parso==0.8.7 +pexpect==4.9.0 +pillow==12.2.0 +platformdirs==4.10.0 +plotly==6.8.0 +prompt-toolkit==3.0.52 +protobuf==7.35.0 +psutil==7.2.2 +ptyprocess==0.7.0 +pure-eval==0.2.3 +pyarrow==24.0.0 +pydeck==0.9.2 +pygments==2.20.0 +pynndescent==0.6.0 +pyparsing==3.3.2 +python-dateutil==2.9.0.post0 +python-multipart==0.0.32 +pyzmq==27.1.0 +referencing==0.37.0 +requests==2.34.2 +rpds-py==2026.5.1 +scikit-learn==1.9.0 +scipy==1.17.1 +six==1.17.0 +smmap==5.0.3 +stack-data==0.6.3 +starlette==1.2.1 +streamlit==1.58.0 +tenacity==9.1.4 +threadpoolctl==3.6.0 +toml==0.10.2 +tornado==6.5.7 +tqdm==4.67.3 +traitlets==5.15.1 +typing-extensions==4.15.0 +umap-learn==0.5.12 +urllib3==2.7.0 +uvicorn==0.49.0 +watchdog==6.0.0 +wcwidth==0.8.1 +websockets==16.0 +widgetsnbextension==4.0.15 diff --git a/9.webapp/test_notebook.ipynb b/9.webapp/test_notebook.ipynb deleted file mode 100644 index 920cffa..0000000 --- a/9.webapp/test_notebook.ipynb +++ /dev/null @@ -1,87569 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "394ffda4", - "metadata": {}, - "source": [ - "## latent umaps" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "883f1d01", - "metadata": {}, - "outputs": [], - "source": [ - "import pathlib\n", - "import random\n", - "import sys\n", - "\n", - "import joblib\n", - "import numpy as np\n", - "import pandas as pd\n", - "import plotly.express as px\n", - "import plotly.graph_objects as go\n", - "from app_utils import generate_random_palette, load_model_data\n", - "from sklearn.decomposition import PCA\n", - "from sklearn.preprocessing import StandardScaler" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "65bb91f4", - "metadata": {}, - "outputs": [], - "source": [ - "cancer_type_input_file = pathlib.Path(\"../0.data-download/data/Model.parquet\")\n", - "cancer_type_df = pd.read_parquet(cancer_type_input_file)\n", - "\n", - "reactome_dims = pathlib.Path(\n", - " \"../5.drug-dependency/results/all_reactome_results.parquet\"\n", - ")\n", - "reactome_df = pd.read_parquet(reactome_dims)\n", - "\n", - "corum_dims = pathlib.Path(\"../5.drug-dependency/results/all_corum_results.parquet\")\n", - "corum_df = pd.read_parquet(corum_dims)\n", - "\n", - "drug_dims = pathlib.Path(\"../5.drug-dependency/results/all_drug_results.parquet\")\n", - "drug_df = pd.read_parquet(drug_dims)\n", - "# Step 2: Subset based on matching keys\n", - "subset_keys = [\"model\", \"latent_dim_total\", \"init\", \"z\"]\n", - "\n", - "# Replace latent identifiers with pathway\n", - "reactome_df[\"feature\"] = reactome_df[\"reactome_pathway\"]\n", - "reactome_df = reactome_df.drop(\n", - " columns=[\"model\", \"latent_dim_total\", \"init\", \"seed\", \"z\", \"reactome_pathway\"]\n", - ")\n", - "\n", - "corum_df[\"feature\"] = corum_df[\"reactome_pathway\"]\n", - "corum_df = corum_df.drop(\n", - " columns=[\"model\", \"latent_dim_total\", \"init\", \"seed\", \"z\", \"reactome_pathway\"]\n", - ")\n", - "\n", - "drug_df[\"feature\"] = drug_df[\"name\"]\n", - "drug_df = drug_df.drop(\n", - " columns=[\"model\", \"latent_dim_total\", \"init\", \"seed\", \"z\", \"name\"]\n", - ")\n", - "drug_df_sorted = drug_df.sort_values(\n", - " by=[\"OncotreePrimaryDisease\", \"ModelID\", \"feature\"], ascending=True\n", - ")\n", - "# Create a unique column name by combining feature and source\n", - "meta_cols = [\"ModelID\", \"OncotreePrimaryDisease\"]\n", - "reactome_meta = reactome_df[meta_cols].drop_duplicates()\n", - "corum_meta = corum_df[meta_cols].drop_duplicates()\n", - "drug_meta = drug_df[meta_cols].drop_duplicates()\n", - "\n", - "# Pivot to wide format\n", - "reactome_matrix = reactome_df.pivot(\n", - " index=\"ModelID\", columns=\"feature\", values=\"latent_score\"\n", - ")\n", - "corum_matrix = corum_df.pivot(index=\"ModelID\", columns=\"feature\", values=\"latent_score\")\n", - "drug_matrix = drug_df.pivot(index=\"ModelID\", columns=\"feature\", values=\"latent_score\")\n", - "\n", - "# Join metadata back to each matrix\n", - "reactome_matrix = reactome_matrix.merge(reactome_meta, on=\"ModelID\", how=\"left\")\n", - "corum_matrix = corum_matrix.merge(corum_meta, on=\"ModelID\", how=\"left\")\n", - "drug_matrix = drug_matrix.merge(drug_meta, on=\"ModelID\", how=\"left\")" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "a6783a5b", - "metadata": {}, - "outputs": [], - "source": [ - "import colorsys\n", - "import random\n", - "\n", - "\n", - "def generate_random_palette(num_colors, seed=12):\n", - " # Generate random colors with varied lightness and saturation\n", - " random.seed(seed)\n", - "\n", - " colors = []\n", - "\n", - " for _ in range(num_colors):\n", - " h = random.random() # Random hue between 0 and 1\n", - " l = random.uniform(0.2, 0.8) # Lightness between 0.3 and 0.9 for contrast\n", - " s = random.uniform(0.5, 1.0) # Saturation between 0.6 and 1.0 for vivid colors\n", - " color = colorsys.hls_to_rgb(h, l, s) # Convert HLS to RGB color\n", - " colors.append(color)\n", - "\n", - " return colors" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "a6c8bafb", - "metadata": {}, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'gene_cols' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[31m---------------------------------------------------------------------------\u001b[39m", - "\u001b[31mNameError\u001b[39m Traceback (most recent call last)", - "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[8]\u001b[39m\u001b[32m, line 7\u001b[39m\n\u001b[32m 3\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m sklearn.decomposition \u001b[38;5;28;01mimport\u001b[39;00m PCA\n\u001b[32m 4\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m sklearn.preprocessing \u001b[38;5;28;01mimport\u001b[39;00m StandardScaler\n\u001b[32m 5\u001b[39m \n\u001b[32m 6\u001b[39m \u001b[38;5;66;03m# Prepare PCA input (excluding non-numeric columns)\u001b[39;00m\n\u001b[32m----> \u001b[39m\u001b[32m7\u001b[39m pca_input = combined_df[gene_cols].apply(pd.to_numeric, errors=\u001b[33m\"coerce\"\u001b[39m)\n\u001b[32m 8\u001b[39m pca = PCA(n_components=\u001b[32m2\u001b[39m, random_state=\u001b[32m0\u001b[39m)\n\u001b[32m 9\u001b[39m pca_embedding = pca.fit_transform(pca_input)\n\u001b[32m 10\u001b[39m \n", - "\u001b[31mNameError\u001b[39m: name 'gene_cols' is not defined" - ] - } - ], - "source": [ - "import plotly.express as px\n", - "import plotly.graph_objects as go\n", - "from sklearn.decomposition import PCA\n", - "from sklearn.preprocessing import StandardScaler\n", - "\n", - "# Prepare PCA input (excluding non-numeric columns)\n", - "pca_input = combined_df[gene_cols].apply(pd.to_numeric, errors=\"coerce\")\n", - "pca = PCA(n_components=2, random_state=0)\n", - "pca_embedding = pca.fit_transform(pca_input)\n", - "\n", - "# Add PCA components to the dataframe\n", - "combined_df[\"PCA1\"] = pca_embedding[:, 0]\n", - "combined_df[\"PCA2\"] = pca_embedding[:, 1]\n", - "\n", - "# Prepare color map for each cancer type\n", - "cancer_types = combined_df[\"OncotreePrimaryDisease\"].unique()\n", - "color_map = (\n", - " px.colors.qualitative.Plotly\n", - " + px.colors.qualitative.Light24\n", - " + px.colors.qualitative.Dark24\n", - ")\n", - "highlight_color_map = {\n", - " cancer: color_map[i % len(color_map)] for i, cancer in enumerate(cancer_types)\n", - "}\n", - "\n", - "# Create one trace per cancer type\n", - "traces = []\n", - "for cancer in cancer_types:\n", - " df_subset = combined_df[combined_df[\"OncotreePrimaryDisease\"] == cancer]\n", - " trace = go.Scatter(\n", - " x=df_subset[\"PCA1\"],\n", - " y=df_subset[\"PCA2\"],\n", - " mode=\"markers\",\n", - " name=cancer,\n", - " marker=dict(size=7),\n", - " text=[f\"{cancer} | {model_id}\" for model_id in df_subset[\"ModelID\"]],\n", - " hoverinfo=\"text\",\n", - " )\n", - " traces.append(trace)\n", - "\n", - "# Create dropdown buttons\n", - "dropdown_buttons = []\n", - "\n", - "for i, cancer in enumerate(cancer_types):\n", - " # Make all grey except the selected one\n", - " visibility = [True] * len(cancer_types)\n", - " colors = [\"lightgrey\"] * len(cancer_types)\n", - " colors[i] = highlight_color_map[cancer]\n", - "\n", - " button = dict(\n", - " method=\"update\",\n", - " label=cancer,\n", - " args=[\n", - " {\n", - " \"visible\": visibility,\n", - " \"marker\": [{\"color\": colors[j]} for j in range(len(cancer_types))],\n", - " },\n", - " {\"title\": f\"PCA Highlighted: {cancer}\"},\n", - " ],\n", - " )\n", - " dropdown_buttons.append(button)\n", - "\n", - "# Add a button to show all with normal colors\n", - "default_colors = [highlight_color_map[cancer] for cancer in cancer_types]\n", - "dropdown_buttons.insert(\n", - " 0,\n", - " dict(\n", - " method=\"update\",\n", - " label=\"Show All\",\n", - " args=[\n", - " {\n", - " \"visible\": [True] * len(cancer_types),\n", - " \"marker\": [\n", - " {\"color\": default_colors[j]} for j in range(len(cancer_types))\n", - " ],\n", - " },\n", - " {\"title\": \"PCA of DepMap Single Gene Data\"},\n", - " ],\n", - " ),\n", - ")\n", - "\n", - "# Create the figure\n", - "fig = go.Figure(data=traces)\n", - "\n", - "# Set default colors\n", - "for i, trace in enumerate(fig.data):\n", - " trace.marker.color = default_colors[i]\n", - "\n", - "fig.update_layout(\n", - " title=\"PCA of DepMap Single Gene Data\",\n", - " xaxis_title=\"PCA1\",\n", - " yaxis_title=\"PCA2\",\n", - " updatemenus=[\n", - " {\n", - " \"buttons\": dropdown_buttons,\n", - " \"direction\": \"down\",\n", - " \"showactive\": True,\n", - " \"x\": 1.15,\n", - " \"xanchor\": \"left\",\n", - " \"y\": 1.15,\n", - " \"yanchor\": \"top\",\n", - " }\n", - " ],\n", - " width=1500,\n", - " height=800,\n", - ")\n", - "\n", - "fig.show()\n", - "fig.write_html(\"achilles_pca.html\")" - ] - }, - { - "cell_type": "markdown", - "id": "5608470d", - "metadata": {}, - "source": [ - "## single-depedency-umaps" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "e4f4c4b8", - "metadata": {}, - "outputs": [], - "source": [ - "import colorsys\n", - "import pathlib\n", - "import random\n", - "\n", - "import ipywidgets as widgets\n", - "import pandas as pd\n", - "import plotly.express as px\n", - "import plotly.graph_objs as go\n", - "from sklearn.decomposition import PCA" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "61b1ea35", - "metadata": {}, - "outputs": [], - "source": [ - "cancer_type_input_file = pathlib.Path(\"../0.data-download/data/Model.parquet\")\n", - "cancer_type_df = pd.read_parquet(cancer_type_input_file)\n", - "\n", - "reactome_dims = pathlib.Path(\n", - " \"../5.drug-dependency/results/all_reactome_results.parquet\"\n", - ")\n", - "reactome_df = pd.read_parquet(reactome_dims)\n", - "\n", - "corum_dims = pathlib.Path(\"../5.drug-dependency/results/all_corum_results.parquet\")\n", - "corum_df = pd.read_parquet(corum_dims)\n", - "\n", - "drug_dims = pathlib.Path(\"../5.drug-dependency/results/all_drug_results.parquet\")\n", - "drug_df = pd.read_parquet(drug_dims)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "e4d005ac", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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    0ACH-000001betatcvae1641154917792Ovarian Epithelial Tumor10.306144Formation Of Incision Complex In GG-NER R-HSA-...3.2473450.306144
    1ACH-000001betatcvae250501796030Ovarian Epithelial Tumor10.657242Citric Acid (TCA) Cycle And Respiratory Electr...inf0.657242
    2ACH-000001betatcvae9001590696690Ovarian Epithelial Tumor10.455570Polymerase Switching On C-strand Of Telomere R...2.9176800.455570
    3ACH-000001betavae534066919116Ovarian Epithelial Tumor10.000000RHOC GTPase Cycle R-HSA-90131063.1494550.000000
    4ACH-000001betavae1021507182516Ovarian Epithelial Tumor10.159076Nephrin Family Interactions R-HSA-3737532.5826870.159076
    \n", - "
    " - ], - "text/plain": [ - " ModelID model latent_dim_total init seed \\\n", - "0 ACH-000001 betatcvae 16 4 1154917792 \n", - "1 ACH-000001 betatcvae 25 0 501796030 \n", - "2 ACH-000001 betatcvae 90 0 1590696690 \n", - "3 ACH-000001 betavae 5 3 4066919116 \n", - "4 ACH-000001 betavae 10 2 1507182516 \n", - "\n", - " OncotreePrimaryDisease z latent_score \\\n", - "0 Ovarian Epithelial Tumor 1 0.306144 \n", - "1 Ovarian Epithelial Tumor 1 0.657242 \n", - "2 Ovarian Epithelial Tumor 1 0.455570 \n", - "3 Ovarian Epithelial Tumor 1 0.000000 \n", - "4 Ovarian Epithelial Tumor 1 0.159076 \n", - "\n", - " reactome_pathway nes_score pathway_score \n", - "0 Formation Of Incision Complex In GG-NER R-HSA-... 3.247345 0.306144 \n", - "1 Citric Acid (TCA) Cycle And Respiratory Electr... inf 0.657242 \n", - "2 Polymerase Switching On C-strand Of Telomere R... 2.917680 0.455570 \n", - "3 RHOC GTPase Cycle R-HSA-9013106 3.149455 0.000000 \n", - "4 Nephrin Family Interactions R-HSA-373753 2.582687 0.159076 " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "reactome_df.head()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "fcc27123", - "metadata": {}, - "outputs": [], - "source": [ - "# Step 2: Subset based on matching keys\n", - "subset_keys = [\"model\", \"latent_dim_total\", \"init\", \"z\"]\n", - "\n", - "# Replace latent identifiers with pathway\n", - "reactome_df[\"feature\"] = reactome_df[\"reactome_pathway\"]\n", - "reactome_df = reactome_df.drop(\n", - " columns=[\"model\", \"latent_dim_total\", \"init\", \"seed\", \"z\", \"reactome_pathway\"]\n", - ")\n", - "\n", - "corum_df[\"feature\"] = corum_df[\"reactome_pathway\"]\n", - "corum_df = corum_df.drop(\n", - " columns=[\"model\", \"latent_dim_total\", \"init\", \"seed\", \"z\", \"reactome_pathway\"]\n", - ")\n", - "\n", - "drug_df[\"feature\"] = drug_df[\"name\"]\n", - "drug_df = drug_df.drop(\n", - " columns=[\"model\", \"latent_dim_total\", \"init\", \"seed\", \"z\", \"name\"]\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b65e2c71", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
    \n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
    ModelIDOncotreePrimaryDiseaselatent_scorepearson_correlationpathway_scorefeature
    597ACH-000004Acute Myeloid Leukemia0.543216-0.2639620.54321610-deacetylbaccatin
    716ACH-000004Acute Myeloid Leukemia0.740212-0.2529450.7402122,3-DCPE
    457ACH-000004Acute Myeloid Leukemia0.832806-0.2753880.8328063-deazaneplanocin-A
    678ACH-000004Acute Myeloid Leukemia0.641957-0.3206670.6419579-aminoacridine
    444ACH-000004Acute Myeloid Leukemia0.546763-0.2626310.546763ACY-1215
    \n", - "
    " - ], - "text/plain": [ - " ModelID OncotreePrimaryDisease latent_score pearson_correlation \\\n", - "597 ACH-000004 Acute Myeloid Leukemia 0.543216 -0.263962 \n", - "716 ACH-000004 Acute Myeloid Leukemia 0.740212 -0.252945 \n", - "457 ACH-000004 Acute Myeloid Leukemia 0.832806 -0.275388 \n", - "678 ACH-000004 Acute Myeloid Leukemia 0.641957 -0.320667 \n", - "444 ACH-000004 Acute Myeloid Leukemia 0.546763 -0.262631 \n", - "\n", - " pathway_score feature \n", - "597 0.543216 10-deacetylbaccatin \n", - "716 0.740212 2,3-DCPE \n", - "457 0.832806 3-deazaneplanocin-A \n", - "678 0.641957 9-aminoacridine \n", - "444 0.546763 ACY-1215 " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "drug_df_sorted = drug_df.sort_values(\n", - " by=[\"OncotreePrimaryDisease\", \"ModelID\", \"feature\"], ascending=True\n", - ")\n", - "drug_df_sorted.head()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6867f3ee", - "metadata": {}, - "outputs": [], - "source": [ - "# Create a unique column name by combining feature and source\n", - "meta_cols = [\"ModelID\", \"OncotreePrimaryDisease\"]\n", - "reactome_meta = reactome_df[meta_cols].drop_duplicates()\n", - "corum_meta = corum_df[meta_cols].drop_duplicates()\n", - "drug_meta = drug_df[meta_cols].drop_duplicates()\n", - "\n", - "# Pivot to wide format\n", - "reactome_matrix = reactome_df.pivot(\n", - " index=\"ModelID\", columns=\"feature\", values=\"latent_score\"\n", - ")\n", - "corum_matrix = corum_df.pivot(index=\"ModelID\", columns=\"feature\", values=\"latent_score\")\n", - "drug_matrix = drug_df.pivot(index=\"ModelID\", columns=\"feature\", values=\"latent_score\")\n", - "\n", - "# Join metadata back to each matrix\n", - "reactome_matrix = reactome_matrix.merge(reactome_meta, on=\"ModelID\", how=\"left\")\n", - "corum_matrix = corum_matrix.merge(corum_meta, on=\"ModelID\", how=\"left\")\n", - "drug_matrix = drug_matrix.merge(drug_meta, on=\"ModelID\", how=\"left\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "492bc932", - "metadata": {}, - "outputs": [], - "source": [ - "def generate_random_palette(num_colors, seed=12):\n", - " # Generate random colors with varied lightness and saturation\n", - " random.seed(seed)\n", - "\n", - " colors = []\n", - "\n", - " for _ in range(num_colors):\n", - " h = random.random() # Random hue between 0 and 1\n", - " l = random.uniform(0.2, 0.8) # Lightness between 0.3 and 0.9 for contrast\n", - " s = random.uniform(0.5, 1.0) # Saturation between 0.6 and 1.0 for vivid colors\n", - " color = colorsys.hls_to_rgb(h, l, s) # Convert HLS to RGB color\n", - " colors.append(color)\n", - "\n", - " return colors" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "5743bc28", - "metadata": {}, - "outputs": [], - "source": [ - "def make_dropdown_pca_with_selection(df, title=\"PCA Interactive Plot\"):\n", - " out = widgets.Output() # Create a fresh output for this plot!\n", - "\n", - " # Prepare PCA input\n", - " pca_input = df.drop(\n", - " columns=[\"OncotreePrimaryDisease\", \"source\", \"ModelID\"], errors=\"ignore\"\n", - " ).fillna(0)\n", - " pca = PCA(n_components=2, random_state=0)\n", - " embedding = pca.fit_transform(pca_input)\n", - "\n", - " # Add PCA coordinates to the dataframe\n", - " df[\"PCA1\"] = embedding[:, 0]\n", - " df[\"PCA2\"] = embedding[:, 1]\n", - "\n", - " # Prepare color map for each cancer type\n", - " cancer_types = df[\"OncotreePrimaryDisease\"].unique()\n", - " color_map = (\n", - " px.colors.qualitative.Plotly\n", - " + px.colors.qualitative.Light24\n", - " + px.colors.qualitative.Dark24\n", - " )\n", - " highlight_color_map = {\n", - " cancer: color_map[i % len(color_map)] for i, cancer in enumerate(cancer_types)\n", - " }\n", - "\n", - " # Create one trace per cancer type\n", - " traces = []\n", - " for cancer in cancer_types:\n", - " df_subset = df[df[\"OncotreePrimaryDisease\"] == cancer]\n", - " trace = go.Scattergl(\n", - " x=df_subset[\"PCA1\"],\n", - " y=df_subset[\"PCA2\"],\n", - " mode=\"markers\",\n", - " name=cancer,\n", - " marker=dict(size=7, color=highlight_color_map[cancer]),\n", - " text=[f\"{cancer} | {model_id}\" for model_id in df_subset[\"ModelID\"]],\n", - " customdata=df_subset[\"ModelID\"], # Attach ModelID to customdata\n", - " hoverinfo=\"text\",\n", - " )\n", - " traces.append(trace)\n", - "\n", - " # Dropdown buttons to highlight cancer types\n", - " dropdown_buttons = []\n", - " for i, cancer in enumerate(cancer_types):\n", - " visibility = [True] * len(cancer_types)\n", - " colors = [\"lightgrey\"] * len(cancer_types)\n", - " colors[i] = highlight_color_map[cancer]\n", - "\n", - " button = dict(\n", - " method=\"update\",\n", - " label=cancer,\n", - " args=[\n", - " {\n", - " \"visible\": visibility,\n", - " \"marker\": [{\"color\": colors[j]} for j in range(len(cancer_types))],\n", - " },\n", - " {\"title\": f\"PCA Highlighted: {cancer}\"},\n", - " ],\n", - " )\n", - " dropdown_buttons.append(button)\n", - "\n", - " # Default color button\n", - " default_colors = [highlight_color_map[cancer] for cancer in cancer_types]\n", - " dropdown_buttons.insert(\n", - " 0,\n", - " dict(\n", - " method=\"update\",\n", - " label=\"Show All\",\n", - " args=[\n", - " {\n", - " \"visible\": [True] * len(cancer_types),\n", - " \"marker\": [\n", - " {\"color\": default_colors[j]} for j in range(len(cancer_types))\n", - " ],\n", - " },\n", - " {\"title\": title},\n", - " ],\n", - " ),\n", - " )\n", - "\n", - " fig = go.Figure(data=traces)\n", - "\n", - " for i, trace in enumerate(fig.data):\n", - " trace.marker.color = default_colors[i]\n", - "\n", - " fig.update_layout(\n", - " title=title,\n", - " xaxis_title=\"PCA1\",\n", - " yaxis_title=\"PCA2\",\n", - " updatemenus=[\n", - " {\n", - " \"buttons\": dropdown_buttons,\n", - " \"direction\": \"down\",\n", - " \"showactive\": True,\n", - " \"x\": 1.15,\n", - " \"xanchor\": \"left\",\n", - " \"y\": 1.15,\n", - " \"yanchor\": \"top\",\n", - " }\n", - " ],\n", - " dragmode=\"lasso\", # Ensure Lasso is enabled\n", - " width=1500,\n", - " height=800,\n", - " )\n", - "\n", - " return fig, out # Return both the figure and the output widget for selection" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "06be719b", - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.plotly.v1+json": { - "config": { - "plotlyServerURL": "https://plot.ly" - }, - "data": [ - { - "customdata": [ - "ACH-000001", - "ACH-000013", - "ACH-000048", - "ACH-000103", - "ACH-000116", - "ACH-000123", - "ACH-000132", - "ACH-000237", - "ACH-000256", - "ACH-000278", - "ACH-000280", - "ACH-000291", - "ACH-000308", - "ACH-000324", - "ACH-000430", - "ACH-000460", - "ACH-000520", - "ACH-000524", - "ACH-000527", - "ACH-000542", - "ACH-000584", - "ACH-000608", - "ACH-000646", - "ACH-000657", - "ACH-000663", - "ACH-000688", - "ACH-000696", - "ACH-000701", - "ACH-000704", - "ACH-000713", - "ACH-000719", 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Epithelial Tumor | ACH-000278", - "Ovarian Epithelial Tumor | ACH-000280", - "Ovarian Epithelial Tumor | ACH-000291", - "Ovarian Epithelial Tumor | ACH-000308", - "Ovarian Epithelial Tumor | ACH-000324", - "Ovarian Epithelial Tumor | ACH-000430", - "Ovarian Epithelial Tumor | ACH-000460", - "Ovarian Epithelial Tumor | ACH-000520", - "Ovarian Epithelial Tumor | ACH-000524", - "Ovarian Epithelial Tumor | ACH-000527", - "Ovarian Epithelial Tumor | ACH-000542", - "Ovarian Epithelial Tumor | ACH-000584", - "Ovarian Epithelial Tumor | ACH-000608", - "Ovarian Epithelial Tumor | ACH-000646", - "Ovarian Epithelial Tumor | ACH-000657", - "Ovarian Epithelial Tumor | ACH-000663", - "Ovarian Epithelial Tumor | ACH-000688", - "Ovarian Epithelial Tumor | ACH-000696", - "Ovarian Epithelial Tumor | ACH-000701", - "Ovarian Epithelial Tumor | ACH-000704", - "Ovarian Epithelial Tumor | ACH-000713", - "Ovarian Epithelial Tumor | ACH-000719", - "Ovarian Epithelial Tumor | ACH-000796", - "Ovarian Epithelial Tumor | ACH-000811", - "Ovarian Epithelial Tumor | ACH-000885", - "Ovarian Epithelial Tumor | ACH-000906", - "Ovarian Epithelial Tumor | ACH-000936", - "Ovarian Epithelial Tumor | ACH-000947", - "Ovarian Epithelial Tumor | ACH-000962", - "Ovarian Epithelial Tumor | ACH-000966", - "Ovarian Epithelial Tumor | ACH-001048", - "Ovarian Epithelial Tumor | ACH-001063", - "Ovarian Epithelial Tumor | ACH-001145", - "Ovarian Epithelial Tumor | ACH-001151", - "Ovarian Epithelial Tumor | ACH-001278", - "Ovarian Epithelial Tumor | ACH-001279", - "Ovarian Epithelial Tumor | ACH-001340", - "Ovarian Epithelial Tumor | ACH-001370", - "Ovarian Epithelial Tumor | ACH-001403", - "Ovarian Epithelial Tumor | ACH-001418", - "Ovarian Epithelial Tumor | ACH-001628", - "Ovarian Epithelial Tumor | ACH-001630", - "Ovarian Epithelial Tumor | ACH-001632", - "Ovarian Epithelial Tumor | ACH-001719", - "Ovarian Epithelial Tumor | ACH-001991", - "Ovarian Epithelial Tumor | ACH-002140", - "Ovarian Epithelial Tumor | ACH-002181", - "Ovarian Epithelial Tumor | ACH-002183", - "Ovarian Epithelial Tumor | ACH-002486", - "Ovarian Epithelial Tumor | ACH-002524" - ], - "type": "scattergl", - "x": { - "bdata": "e4r5vXb+GEB3ZKhALgRQvzJvbj+zPJhAjuwfPx0F7r/s1PLAO+TywArKyD9QREE/sscBwMD76j9xNJdAA/IrQO14272HxvLAujMCQKPC8sDw4wNAr9TywI2/H8AMsvLAswDFPnB1pMAiym5AzegdwIiS0D8zZOU+ic/QvkXWZL9RyVPAhGu0QB/Tk0Beduw/74jkQNR3MUCgV+Y/osfywEW/8sDWK0VAzNcXP0e68sDsgZRA/7fywCK+8sAozPLAgK+iP1y98sDew/LAgtrywAni8sDkMKpAqLnywO/O8sAm6PLATQBxQMayjj8=", - "dtype": "f4" - }, - "y": { - "bdata": "up2uvu/orT/bEiK+/2xov8Jb2T8iOVm/OmQPQMi4l0D42aq/Mcuqv5bRO0BrxbA/dRoevryEBEDZ6Rg/b/3WvrOXCUAEdau/7DXjP/k+q7+V/Ba/wHSrv3Pdlj1Qfau/PiokQF6QM0Aafg9AafNoP09yCD+ACR++jcqlP4wGkr6AcEBA0kouP5xabD/5aj+/Y+rsvwkpMz+tetU+H/Sqvz0Jq78g3nw//1PCPxmDq7/vg308a0Krv0Bnq7/5Aau/IhtOv/tfq78i0qq/yraqv6Z5qr/wRQvAUZ2rv4Djqr9FmKq/kqGwP3VBeD4=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000004", - "ACH-000005", - "ACH-000045", - "ACH-000113", - "ACH-000146", - 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| ACH-000387", - "Acute Myeloid Leukemia | ACH-000406", - "Acute Myeloid Leukemia | ACH-000498", - "Acute Myeloid Leukemia | ACH-000557", - "Acute Myeloid Leukemia | ACH-000602", - "Acute Myeloid Leukemia | ACH-000770", - "Acute Myeloid Leukemia | ACH-001036", - "Acute Myeloid Leukemia | ACH-001129", - "Acute Myeloid Leukemia | ACH-001574", - "Acute Myeloid Leukemia | ACH-001577", - "Acute Myeloid Leukemia | ACH-001613", - "Acute Myeloid Leukemia | ACH-001618", - "Acute Myeloid Leukemia | ACH-001647", - "Acute Myeloid Leukemia | ACH-001656" - ], - "type": "scattergl", - "x": { - "bdata": "CJ/fP16jlT6TIrpAinkNQfzmdD6qGBi+C4skQLKkgT+lXzK/dFkmQJUt60Dc5rlAK434P0vczUCLIpk+4IwBwECUFEDt+pNAGDlGQOkUvb37sMRAtpkHQIODlUC0oEJAVFKOQL2JhEA=", - "dtype": "f4" - }, - "y": { - "bdata": "PxwGwL8xqL9U0oXAV4GbwBxNPMDLXgrAdhBnPvxjjb/64PG/C68qwACzkMBSwYXA0JwNwOuhesCgd/Y84oBMwOLsN8B/ZHLAV731vwxmR7/VaHfAJSQDwDgYGsA/xQjAlARnwAezc8A=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000007", - 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"color": "#00CC96", - "size": 7 - }, - "mode": "markers", - "name": "Colorectal Adenocarcinoma", - "text": [ - "Colorectal Adenocarcinoma | ACH-000007", - "Colorectal Adenocarcinoma | ACH-000009", - "Colorectal Adenocarcinoma | ACH-000202", - "Colorectal Adenocarcinoma | ACH-000249", - "Colorectal Adenocarcinoma | ACH-000252", - "Colorectal Adenocarcinoma | ACH-000253", - "Colorectal Adenocarcinoma | ACH-000286", - "Colorectal Adenocarcinoma | ACH-000296", - "Colorectal Adenocarcinoma | ACH-000350", - "Colorectal Adenocarcinoma | ACH-000381", - "Colorectal Adenocarcinoma | ACH-000403", - "Colorectal Adenocarcinoma | ACH-000421", - "Colorectal Adenocarcinoma | ACH-000467", - "Colorectal Adenocarcinoma | ACH-000470", - "Colorectal Adenocarcinoma | ACH-000489", - "Colorectal Adenocarcinoma | ACH-000491", - "Colorectal Adenocarcinoma | ACH-000501", - "Colorectal Adenocarcinoma | ACH-000532", - "Colorectal Adenocarcinoma | ACH-000552", - "Colorectal Adenocarcinoma | ACH-000565", - "Colorectal Adenocarcinoma | ACH-000651", - "Colorectal Adenocarcinoma | ACH-000683", - "Colorectal Adenocarcinoma | ACH-000722", - "Colorectal Adenocarcinoma | ACH-000798", - "Colorectal Adenocarcinoma | ACH-000820", - "Colorectal Adenocarcinoma | ACH-000926", - "Colorectal Adenocarcinoma | ACH-000935", - "Colorectal Adenocarcinoma | ACH-000943", - "Colorectal Adenocarcinoma | ACH-000950", - "Colorectal Adenocarcinoma | ACH-000957", - "Colorectal Adenocarcinoma | ACH-000958", - "Colorectal Adenocarcinoma | ACH-000959", - "Colorectal Adenocarcinoma | ACH-000963", - "Colorectal Adenocarcinoma | ACH-000969", - "Colorectal Adenocarcinoma | ACH-000970", - "Colorectal Adenocarcinoma | ACH-000971", - "Colorectal Adenocarcinoma | ACH-000985", - "Colorectal Adenocarcinoma | ACH-000986", - "Colorectal Adenocarcinoma | ACH-000991", - "Colorectal Adenocarcinoma | ACH-000997", - "Colorectal Adenocarcinoma | ACH-001039", - "Colorectal Adenocarcinoma | ACH-001061", - "Colorectal Adenocarcinoma | ACH-001081", - "Colorectal Adenocarcinoma | ACH-001345", - "Colorectal Adenocarcinoma | ACH-001399", - "Colorectal Adenocarcinoma | ACH-001454", - "Colorectal Adenocarcinoma | ACH-001458", - "Colorectal Adenocarcinoma | ACH-001459", - "Colorectal Adenocarcinoma | ACH-001460", - "Colorectal Adenocarcinoma | ACH-001461", - "Colorectal Adenocarcinoma | ACH-001786", - "Colorectal Adenocarcinoma | ACH-002024", - "Colorectal Adenocarcinoma | ACH-002025", - "Colorectal Adenocarcinoma | ACH-002233", - "Colorectal Adenocarcinoma | ACH-002535", - "Colorectal Adenocarcinoma | ACH-002654", - "Colorectal Adenocarcinoma | ACH-002659", - "Colorectal Adenocarcinoma | ACH-002660", - "Colorectal Adenocarcinoma | ACH-002662", - "Colorectal Adenocarcinoma | ACH-002664", - "Colorectal Adenocarcinoma | ACH-002669" - ], - "type": "scattergl", - "x": { - "bdata": 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"ACH-000741", - "ACH-000753", - "ACH-000802", - "ACH-000834", - "ACH-000862", - "ACH-000896", - "ACH-000905", - "ACH-001183", - "ACH-001407", - "ACH-001409", - "ACH-001412", - "ACH-001413", - "ACH-001414", - "ACH-001415", - "ACH-001416" - ], - "hoverinfo": "text", - "marker": { - "color": "#AB63FA", - "size": 7 - }, - "mode": "markers", - "name": "Bladder Urothelial Carcinoma", - "text": [ - "Bladder Urothelial Carcinoma | ACH-000011", - "Bladder Urothelial Carcinoma | ACH-000018", - "Bladder Urothelial Carcinoma | ACH-000026", - "Bladder Urothelial Carcinoma | ACH-000127", - "Bladder Urothelial Carcinoma | ACH-000142", - "Bladder Urothelial Carcinoma | ACH-000242", - "Bladder Urothelial Carcinoma | ACH-000396", - "Bladder Urothelial Carcinoma | ACH-000473", - "Bladder Urothelial Carcinoma | ACH-000486", - "Bladder Urothelial Carcinoma | ACH-000522", - "Bladder Urothelial Carcinoma | ACH-000545", - "Bladder Urothelial Carcinoma | ACH-000547", - "Bladder Urothelial Carcinoma | ACH-000593", - "Bladder Urothelial Carcinoma | ACH-000720", - "Bladder Urothelial Carcinoma | ACH-000724", - "Bladder Urothelial Carcinoma | ACH-000741", - "Bladder Urothelial Carcinoma | ACH-000753", - "Bladder Urothelial Carcinoma | ACH-000802", - "Bladder Urothelial Carcinoma | ACH-000834", - "Bladder Urothelial Carcinoma | ACH-000862", - "Bladder Urothelial Carcinoma | ACH-000896", - "Bladder Urothelial Carcinoma | ACH-000905", - "Bladder Urothelial Carcinoma | ACH-001183", - "Bladder Urothelial Carcinoma | ACH-001407", - "Bladder Urothelial Carcinoma | ACH-001409", - "Bladder Urothelial Carcinoma | ACH-001412", - "Bladder Urothelial Carcinoma | ACH-001413", - "Bladder Urothelial Carcinoma | ACH-001414", - "Bladder Urothelial Carcinoma | ACH-001415", - "Bladder Urothelial Carcinoma | ACH-001416" - ], - "type": "scattergl", - "x": { - "bdata": 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"ACH-000585", - "ACH-000587", - "ACH-000589", - "ACH-000596", - "ACH-000627", - "ACH-000638", - "ACH-000662", - "ACH-000665", - "ACH-000666", - "ACH-000667", - "ACH-000672", - "ACH-000677", - "ACH-000681", - "ACH-000700", - "ACH-000706", - "ACH-000718", - "ACH-000747", - "ACH-000757", - "ACH-000766", - "ACH-000769", - "ACH-000774", - "ACH-000781", - "ACH-000785", - "ACH-000787", - "ACH-000791", - "ACH-000826", - "ACH-000837", - "ACH-000840", - "ACH-000841", - "ACH-000843", - "ACH-000845", - "ACH-000851", - "ACH-000853", - "ACH-000858", - "ACH-000860", - "ACH-000861", - "ACH-000867", - "ACH-000869", - "ACH-000872", - "ACH-000878", - "ACH-000886", - "ACH-000888", - "ACH-000894", - "ACH-000900", - "ACH-000901", - "ACH-000916", - "ACH-000921", - "ACH-000924", - "ACH-000929", - "ACH-000945", - "ACH-000975", - "ACH-000980", - "ACH-001075", - "ACH-001137", - "ACH-001233", - "ACH-002035", - "ACH-002156", - "ACH-002522", - "ACH-002526", - "ACH-002531", - "ACH-002650", - "ACH-003012" - ], - "hoverinfo": "text", - "marker": { - "color": "#FFA15A", - "size": 7 - }, - "mode": "markers", - "name": "Non-Small Cell Lung Cancer", - "text": [ - "Non-Small Cell Lung Cancer | ACH-000012", - "Non-Small Cell Lung Cancer | ACH-000015", - "Non-Small Cell Lung Cancer | ACH-000021", - "Non-Small Cell Lung Cancer | ACH-000029", - "Non-Small Cell Lung Cancer | ACH-000030", - "Non-Small Cell Lung Cancer | ACH-000035", - "Non-Small Cell Lung Cancer | ACH-000143", - "Non-Small Cell Lung Cancer | ACH-000161", - "Non-Small Cell Lung Cancer | ACH-000176", - "Non-Small Cell Lung Cancer | ACH-000251", - "Non-Small Cell Lung Cancer | ACH-000261", - "Non-Small Cell Lung Cancer | ACH-000264", - "Non-Small Cell Lung Cancer | ACH-000311", - "Non-Small Cell Lung Cancer | ACH-000337", - "Non-Small Cell Lung Cancer | ACH-000339", - "Non-Small Cell Lung Cancer | ACH-000343", - "Non-Small Cell Lung Cancer | ACH-000378", - "Non-Small Cell Lung Cancer | ACH-000390", - "Non-Small Cell Lung Cancer | ACH-000395", - "Non-Small Cell Lung Cancer | ACH-000414", - "Non-Small Cell Lung Cancer | ACH-000416", - "Non-Small Cell Lung Cancer | ACH-000434", - "Non-Small Cell Lung Cancer | ACH-000438", - "Non-Small Cell Lung Cancer | ACH-000442", - "Non-Small Cell Lung Cancer | ACH-000444", - "Non-Small Cell Lung Cancer | ACH-000448", - "Non-Small Cell Lung Cancer | ACH-000454", - "Non-Small Cell Lung Cancer | ACH-000463", - "Non-Small Cell Lung Cancer | ACH-000481", - "Non-Small Cell Lung Cancer | ACH-000496", - "Non-Small Cell Lung Cancer | ACH-000510", - "Non-Small Cell Lung Cancer | ACH-000511", - "Non-Small Cell Lung Cancer | ACH-000521", - "Non-Small Cell Lung Cancer | ACH-000528", - "Non-Small Cell Lung Cancer | ACH-000562", - "Non-Small Cell Lung Cancer | ACH-000563", - "Non-Small Cell Lung Cancer | ACH-000585", - "Non-Small Cell Lung Cancer | ACH-000587", - "Non-Small Cell Lung Cancer | ACH-000589", - "Non-Small Cell Lung Cancer | ACH-000596", - "Non-Small Cell Lung Cancer | ACH-000627", - "Non-Small Cell Lung Cancer | ACH-000638", - "Non-Small Cell Lung Cancer | ACH-000662", - "Non-Small Cell Lung Cancer | ACH-000665", - "Non-Small Cell Lung Cancer | ACH-000666", - "Non-Small Cell Lung Cancer | ACH-000667", - "Non-Small Cell Lung Cancer | ACH-000672", - "Non-Small Cell Lung Cancer | ACH-000677", - "Non-Small Cell Lung Cancer | ACH-000681", - "Non-Small Cell Lung Cancer | ACH-000700", - "Non-Small Cell Lung Cancer | ACH-000706", - "Non-Small Cell Lung Cancer | ACH-000718", - "Non-Small Cell Lung Cancer | ACH-000747", - "Non-Small Cell Lung Cancer | ACH-000757", - "Non-Small Cell Lung Cancer | ACH-000766", - "Non-Small Cell Lung Cancer | ACH-000769", - "Non-Small Cell Lung Cancer | ACH-000774", - "Non-Small Cell Lung Cancer | ACH-000781", - "Non-Small Cell Lung Cancer | ACH-000785", - "Non-Small Cell Lung Cancer | ACH-000787", - "Non-Small Cell Lung Cancer | ACH-000791", - "Non-Small Cell Lung Cancer | ACH-000826", - "Non-Small Cell Lung Cancer | ACH-000837", - "Non-Small Cell Lung Cancer | ACH-000840", - "Non-Small Cell Lung Cancer | ACH-000841", - "Non-Small Cell Lung Cancer | ACH-000843", - "Non-Small Cell Lung Cancer | ACH-000845", - "Non-Small Cell Lung Cancer | ACH-000851", - "Non-Small Cell Lung Cancer | ACH-000853", - "Non-Small Cell Lung Cancer | ACH-000858", - "Non-Small Cell Lung Cancer | ACH-000860", - "Non-Small Cell Lung Cancer | ACH-000861", - "Non-Small Cell Lung Cancer | ACH-000867", - "Non-Small Cell Lung Cancer | ACH-000869", - "Non-Small Cell Lung Cancer | ACH-000872", - "Non-Small Cell Lung Cancer | ACH-000878", - "Non-Small Cell Lung Cancer | ACH-000886", - "Non-Small Cell Lung Cancer | ACH-000888", - "Non-Small Cell Lung Cancer | ACH-000894", - "Non-Small Cell Lung Cancer | ACH-000900", - "Non-Small Cell Lung Cancer | ACH-000901", - "Non-Small Cell Lung Cancer | ACH-000916", - "Non-Small Cell Lung Cancer | ACH-000921", - "Non-Small Cell Lung Cancer | ACH-000924", - "Non-Small Cell Lung Cancer | ACH-000929", - "Non-Small Cell Lung Cancer | ACH-000945", - "Non-Small Cell Lung Cancer | ACH-000975", - "Non-Small Cell Lung Cancer | ACH-000980", - "Non-Small Cell Lung Cancer | ACH-001075", - "Non-Small Cell Lung Cancer | ACH-001137", - "Non-Small Cell Lung Cancer | ACH-001233", - "Non-Small Cell Lung Cancer | ACH-002035", - "Non-Small Cell Lung Cancer | ACH-002156", - "Non-Small Cell Lung Cancer | ACH-002522", - "Non-Small Cell Lung Cancer | ACH-002526", - "Non-Small Cell Lung Cancer | ACH-002531", - "Non-Small Cell Lung Cancer | ACH-002650", - "Non-Small Cell Lung Cancer | ACH-003012" - ], - "type": "scattergl", - "x": { - "bdata": 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"ACH-000827", - "ACH-000881", - "ACH-000882", - "ACH-000884", - "ACH-000899", - "ACH-000915", - "ACH-000968", - "ACH-001041", - "ACH-001190", - "ACH-001239", - "ACH-001522", - "ACH-001563", - "ACH-001566", - "ACH-001567", - "ACH-001568", - "ACH-001570", - "ACH-001645", - "ACH-001970", - "ACH-001972", - "ACH-001973", - "ACH-001975", - "ACH-001982", - "ACH-001986", - "ACH-001990", - "ACH-002001", - "ACH-002002", - "ACH-002003", - "ACH-002004", - "ACH-002005", - "ACH-002084", - "ACH-002143", - "ACH-002458", - "ACH-002460", - "ACH-002461", - "ACH-002508", - "ACH-002510", - "ACH-002511", - "ACH-002512", - "ACH-002847", - "ACH-002928" - ], - "hoverinfo": "text", - "marker": { - "color": "#19D3F3", - "size": 7 - }, - "mode": "markers", - "name": "Melanoma", - "text": [ - "Melanoma | ACH-000014", - "Melanoma | ACH-000219", - "Melanoma | ACH-000274", - "Melanoma | ACH-000304", - "Melanoma | ACH-000322", - "Melanoma | ACH-000348", - "Melanoma | ACH-000401", - "Melanoma | ACH-000404", - "Melanoma | ACH-000425", - "Melanoma | ACH-000441", - "Melanoma | ACH-000450", - "Melanoma | ACH-000458", - "Melanoma | ACH-000477", - "Melanoma | ACH-000550", - "Melanoma | ACH-000579", - "Melanoma | ACH-000580", - "Melanoma | ACH-000614", - "Melanoma | ACH-000632", - "Melanoma | ACH-000661", - "Melanoma | ACH-000765", - "Melanoma | ACH-000788", - "Melanoma | ACH-000799", - "Melanoma | ACH-000801", - "Melanoma | ACH-000805", - "Melanoma | ACH-000810", - "Melanoma | ACH-000822", - "Melanoma | ACH-000827", - "Melanoma | ACH-000881", - "Melanoma | ACH-000882", - "Melanoma | ACH-000884", - "Melanoma | ACH-000899", - "Melanoma | ACH-000915", - "Melanoma | ACH-000968", - "Melanoma | ACH-001041", - "Melanoma | ACH-001190", - "Melanoma | ACH-001239", - "Melanoma | ACH-001522", - "Melanoma | ACH-001563", - "Melanoma | ACH-001566", - "Melanoma | ACH-001567", - "Melanoma | ACH-001568", - "Melanoma | ACH-001570", - "Melanoma | ACH-001645", - "Melanoma | ACH-001970", - "Melanoma | ACH-001972", - "Melanoma | ACH-001973", - "Melanoma | ACH-001975", - "Melanoma | ACH-001982", - "Melanoma | ACH-001986", - "Melanoma | ACH-001990", - "Melanoma | ACH-002001", - "Melanoma | ACH-002002", - "Melanoma | ACH-002003", - "Melanoma | ACH-002004", - "Melanoma | ACH-002005", - "Melanoma | ACH-002084", - "Melanoma | ACH-002143", - "Melanoma | ACH-002458", - "Melanoma | ACH-002460", - "Melanoma | ACH-002461", - "Melanoma | ACH-002508", - "Melanoma | ACH-002510", - "Melanoma | ACH-002511", - "Melanoma | ACH-002512", - "Melanoma | ACH-002847", - "Melanoma | ACH-002928" - ], - "type": "scattergl", - "x": { - "bdata": "7FguQHmL30A+qSDA8ygIPyhld0CrGKS/lgovQOSw8sDf0vLA5OaQQDLM8sDNs/LA9c2LPb0bEsC82/LAty3WvUNfc0BUbh1ANrPywAKysD8wpNE/1uCfvCPZ8sAykL4/dFanPvkxJ8D4G6I/1idpQLe8lkAYiltA1dDywOh/k0CW3YFAJnsiQG6/nL/vi35AYyK1P8/Y8sDq3fLA2OHywEPW8sB4w/LAAW70vX24CEDqtPLA/LvywPfA8sCaEGJALhuHQFgLrEDeeZFAz9DVQG8nC0DmyvLAma1oQP3jDr9cfDnAqgojQNYVFkB+fTU++15nvyDZdEAK217Auim3PktPfb0rfhvA", - "dtype": "f4" - }, - "y": { - "bdata": "Kl9BP2Ge2j7BjxFA8pFXPzmsjz8ffwdArok3P8R7q7/IHqu/TgOcPtx4qr8ChKu/m3C5PzCok0Cr+aq/MdJbP9SSOD9Q8C9AlSqrv90/qT/7LQxAh/4ZQLekqr9KqrY9LVMcP6+Kk76xFNA/RiTBvf2NJ7/Dzbm+2paqvxLSkb+fsIw9q57kP5rvEkCZyHw+v+KPPwlMq7+SyKq/Poeqv0E/q7+jBau/l/qTvdya7z8sXau/VBGrvwv0qr9OfkO/Xl6UPhUvr72rkpk9G5PAv1Xy4D43wKq/hWCivV4XwD+OGYk/tv0QQJSddz+15QA/HkaVQHNEn71HRbY/M0YDQO1dXkDohmY/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000017", - "ACH-000019", - "ACH-000028", - "ACH-000097", - "ACH-000111", - "ACH-000147", - "ACH-000148", - "ACH-000212", - "ACH-000223", - "ACH-000248", - "ACH-000258", - "ACH-000276", - "ACH-000277", - "ACH-000288", - "ACH-000330", - "ACH-000352", - "ACH-000374", - "ACH-000554", - "ACH-000573", - "ACH-000621", - "ACH-000668", - "ACH-000699", - "ACH-000711", - "ACH-000721", - "ACH-000768", - "ACH-000783", - "ACH-000849", - "ACH-000856", - "ACH-000876", - "ACH-000910", - "ACH-000934", - "ACH-001065", - "ACH-001388", - "ACH-001389", - "ACH-001390", - "ACH-001391", - "ACH-001392", - "ACH-001393", - "ACH-001394", - "ACH-001396", - "ACH-001419", - "ACH-001662", - "ACH-001683", - "ACH-001819", - "ACH-002179", - "ACH-002399", - "ACH-002401" - ], - "hoverinfo": "text", - "marker": { - "color": "#FF6692", - "size": 7 - }, - "mode": "markers", - "name": "Invasive Breast Carcinoma", - "text": [ - "Invasive Breast Carcinoma | ACH-000017", - "Invasive Breast Carcinoma | ACH-000019", - "Invasive Breast Carcinoma | ACH-000028", - "Invasive Breast Carcinoma | ACH-000097", - "Invasive Breast Carcinoma | ACH-000111", - "Invasive Breast Carcinoma | ACH-000147", - "Invasive Breast Carcinoma | ACH-000148", - "Invasive Breast Carcinoma | ACH-000212", - "Invasive Breast Carcinoma | ACH-000223", - "Invasive Breast Carcinoma | ACH-000248", - "Invasive Breast Carcinoma | ACH-000258", - "Invasive Breast Carcinoma | ACH-000276", - "Invasive Breast Carcinoma | ACH-000277", - "Invasive Breast Carcinoma | ACH-000288", - "Invasive Breast Carcinoma | ACH-000330", - "Invasive Breast Carcinoma | ACH-000352", - "Invasive Breast Carcinoma | ACH-000374", - "Invasive Breast Carcinoma | ACH-000554", - "Invasive Breast Carcinoma | ACH-000573", - "Invasive Breast Carcinoma | ACH-000621", - "Invasive Breast Carcinoma | ACH-000668", - "Invasive Breast Carcinoma | ACH-000699", - "Invasive Breast Carcinoma | ACH-000711", - "Invasive Breast Carcinoma | ACH-000721", - "Invasive Breast Carcinoma | ACH-000768", - "Invasive Breast Carcinoma | ACH-000783", - "Invasive Breast Carcinoma | ACH-000849", - "Invasive Breast Carcinoma | ACH-000856", - "Invasive Breast Carcinoma | ACH-000876", - "Invasive Breast Carcinoma | ACH-000910", - "Invasive Breast Carcinoma | ACH-000934", - "Invasive Breast Carcinoma | ACH-001065", - "Invasive Breast Carcinoma | ACH-001388", - "Invasive Breast Carcinoma | ACH-001389", - "Invasive Breast Carcinoma | ACH-001390", - "Invasive Breast Carcinoma | ACH-001391", - "Invasive Breast Carcinoma | ACH-001392", - "Invasive Breast Carcinoma | ACH-001393", - "Invasive Breast Carcinoma | ACH-001394", - "Invasive Breast Carcinoma | ACH-001396", - "Invasive Breast Carcinoma | ACH-001419", - "Invasive Breast Carcinoma | ACH-001662", - "Invasive Breast Carcinoma | ACH-001683", - "Invasive Breast Carcinoma | ACH-001819", - "Invasive Breast Carcinoma | ACH-002179", - "Invasive Breast Carcinoma | ACH-002399", - "Invasive Breast Carcinoma | ACH-002401" - ], - "type": "scattergl", - "x": { - "bdata": "rkW1vVsoAEC1uoxAFfaQPyCmQ0DKLFpAbvxLPyOzmz+cVMO/HdnmP3/4gr+78l2/4kURPS1q7z87dn0/WEV5P8gN6z/dOwzAAqDbPxi3YMB1QIq/UP/2v/OVE0B8c05ABCWeP5jKOsAQ9GZA6EPrQCD1eb9wwn1AgExdwCFbr0BMPAvAzsvywIwbxz+MbTPArtLywFrW8sCez/LAeu3ywG3mAz+T0LS+WhW8PonUvb9DUUdA7QmoPxqJEkA=", - "dtype": "f4" - }, - "y": { - "bdata": "2bE+v8uRlr/uW82/IfMhv8F8AcB+tZi/C1nlP9Abtz7lxHy9p5q1v5IsjT5cP4Y/GMIpv20cMkDw29G+SpiMvwIcrb6yKO2/piLDPkJOoj/6oYy/zqSpP1OKkr+gFWi/qcpCvgkCPL9qFEa/gxMJPEUssr/+thPAkVHSv+bVCsAyckg/nJ2qv1hXXT8Xl0k/Ewurv+Oyqr/OFKu/Z7+qv9uNGD7hwHY8PX7uvh4BAL9aYB7AyrsqvkJNu70=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000022", - "ACH-000023", - "ACH-000042", - "ACH-000060", - "ACH-000085", - "ACH-000093", - "ACH-000094", - "ACH-000114", - "ACH-000118", - "ACH-000138", - "ACH-000139", - "ACH-000155", - "ACH-000164", - "ACH-000178", - "ACH-000213", - "ACH-000222", - "ACH-000235", - "ACH-000243", - "ACH-000265", - "ACH-000266", - "ACH-000281", - "ACH-000307", - "ACH-000320", - "ACH-000332", - "ACH-000354", - "ACH-000417", - "ACH-000468", - "ACH-000502", - "ACH-000517", - "ACH-000535", - "ACH-000599", - "ACH-000601", - "ACH-000652", - "ACH-001098", - "ACH-001107", - "ACH-001353", - "ACH-001375", - "ACH-001377", - "ACH-001379", - "ACH-001380", - "ACH-001382", - "ACH-001999", - "ACH-002039", - "ACH-002186", - "ACH-002672" - ], - "hoverinfo": "text", - "marker": { - "color": "#B6E880", - "size": 7 - }, - "mode": "markers", - "name": "Pancreatic Adenocarcinoma", - "text": [ - "Pancreatic Adenocarcinoma | ACH-000022", - "Pancreatic Adenocarcinoma | ACH-000023", - "Pancreatic Adenocarcinoma | ACH-000042", - "Pancreatic Adenocarcinoma | ACH-000060", - "Pancreatic Adenocarcinoma | ACH-000085", - "Pancreatic Adenocarcinoma | ACH-000093", - "Pancreatic Adenocarcinoma | ACH-000094", - "Pancreatic Adenocarcinoma | ACH-000114", - "Pancreatic Adenocarcinoma | ACH-000118", - "Pancreatic Adenocarcinoma | ACH-000138", - "Pancreatic Adenocarcinoma | ACH-000139", - "Pancreatic Adenocarcinoma | ACH-000155", - "Pancreatic Adenocarcinoma | ACH-000164", - "Pancreatic Adenocarcinoma | ACH-000178", - "Pancreatic Adenocarcinoma | ACH-000213", - "Pancreatic Adenocarcinoma | ACH-000222", - "Pancreatic Adenocarcinoma | ACH-000235", - "Pancreatic Adenocarcinoma | ACH-000243", - "Pancreatic Adenocarcinoma | ACH-000265", - "Pancreatic Adenocarcinoma | ACH-000266", - "Pancreatic Adenocarcinoma | ACH-000281", - "Pancreatic Adenocarcinoma | ACH-000307", - "Pancreatic Adenocarcinoma | ACH-000320", - "Pancreatic Adenocarcinoma | ACH-000332", - "Pancreatic Adenocarcinoma | ACH-000354", - "Pancreatic Adenocarcinoma | ACH-000417", - "Pancreatic Adenocarcinoma | ACH-000468", - "Pancreatic Adenocarcinoma | ACH-000502", - "Pancreatic Adenocarcinoma | ACH-000517", - "Pancreatic Adenocarcinoma | ACH-000535", - "Pancreatic Adenocarcinoma | ACH-000599", - "Pancreatic Adenocarcinoma | ACH-000601", - "Pancreatic Adenocarcinoma | ACH-000652", - "Pancreatic Adenocarcinoma | ACH-001098", - "Pancreatic Adenocarcinoma | ACH-001107", - "Pancreatic Adenocarcinoma | ACH-001353", - "Pancreatic Adenocarcinoma | ACH-001375", - "Pancreatic Adenocarcinoma | ACH-001377", - "Pancreatic Adenocarcinoma | ACH-001379", - "Pancreatic Adenocarcinoma | ACH-001380", - "Pancreatic Adenocarcinoma | ACH-001382", - "Pancreatic Adenocarcinoma | ACH-001999", - "Pancreatic Adenocarcinoma | ACH-002039", - "Pancreatic Adenocarcinoma | ACH-002186", - "Pancreatic Adenocarcinoma | ACH-002672" - ], - "type": "scattergl", - "x": { - "bdata": "CDm1P29anEB1KCTAEwm3v+jJoL7n1Aq/uZukv/CL87/F7RVAUe3NP/wdNL8BFSm/l6y4P/rbC0AGF94/djFHwJG/mD57yL0/HILGQJlIWsC+N1i/zdHywELOA0B3tE8+LjHLPsJfob/f5PLAiSQ8Pz1k7r9FMTE/pIdoPjQClkBoG2A/LvHUP13emr44X6W/eriBvxxBMkCxutQ/H+hVQKoQmr/Uv/LAGdPywIPD8sCBrTE/", - "dtype": "f4" - }, - "y": { - "bdata": "rbL+vEFG2T/vqVo/fEijP2FkVD/eBNY/gwyTv4da1T85W0S/zlQJPxzD3D7owTY/tymPPS4Btj5qfJa/A2Swv6m5or7KtZ8/zKSePhpsyT851KI/ebqqv19FEz9m3qA/3p+Tv6vfoL4OyKq/PokiPs70wz8FcaA/iSesvwVzVr9ewlg/QZThviiHvz+Q2b4/a4GNPxiTaD+q9t8+gXJlPYqhC0Aq9aq/N4mqv+mxq7/oBgg/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000024", - "ACH-000106", - "ACH-000124", - "ACH-000167", - "ACH-000183", - "ACH-000204", - "ACH-000271", - "ACH-000315", - "ACH-000334", - "ACH-000346", - "ACH-000363", - "ACH-000365", - "ACH-000371", - "ACH-000398", - "ACH-000402", - "ACH-000405", - "ACH-000426", - "ACH-000436", - "ACH-000512", - "ACH-000541", - "ACH-000567", - "ACH-000576", - "ACH-000588", - "ACH-000653", - "ACH-000654", - "ACH-000656", - "ACH-000660", - "ACH-000697", - "ACH-000714", - "ACH-000763", - "ACH-000817", - "ACH-000821", - "ACH-000829", - "ACH-000838", - "ACH-000889", - "ACH-000914", - "ACH-000944", - "ACH-001450", - "ACH-001498", - "ACH-001533", - "ACH-001539", - "ACH-001616", - "ACH-001634", - "ACH-001639", - "ACH-001677", - "ACH-001707", - "ACH-001709", - "ACH-002055", - "ACH-002062", - "ACH-002214", - "ACH-002215", - "ACH-002478", - "ACH-002485", - "ACH-002500", - "ACH-002677", - "ACH-002678" - ], - "hoverinfo": "text", - "marker": { - "color": "#FF97FF", - "size": 7 - }, - "mode": "markers", - "name": "Mature B-Cell Neoplasms", - "text": [ - "Mature B-Cell Neoplasms | ACH-000024", - "Mature B-Cell Neoplasms | ACH-000106", - "Mature B-Cell Neoplasms | ACH-000124", - "Mature B-Cell Neoplasms | ACH-000167", - "Mature B-Cell Neoplasms | ACH-000183", - "Mature B-Cell Neoplasms | ACH-000204", - "Mature B-Cell Neoplasms | ACH-000271", - "Mature B-Cell Neoplasms | ACH-000315", - "Mature B-Cell Neoplasms | ACH-000334", - "Mature B-Cell Neoplasms | ACH-000346", - "Mature B-Cell Neoplasms | ACH-000363", - "Mature B-Cell Neoplasms | ACH-000365", - "Mature B-Cell Neoplasms | ACH-000371", - "Mature B-Cell Neoplasms | ACH-000398", - "Mature B-Cell Neoplasms | ACH-000402", - "Mature B-Cell Neoplasms | ACH-000405", - "Mature B-Cell Neoplasms | ACH-000426", - "Mature B-Cell Neoplasms | ACH-000436", - "Mature B-Cell Neoplasms | ACH-000512", - "Mature B-Cell Neoplasms | ACH-000541", - "Mature B-Cell Neoplasms | ACH-000567", - "Mature B-Cell Neoplasms | ACH-000576", - "Mature B-Cell Neoplasms | ACH-000588", - "Mature B-Cell Neoplasms | ACH-000653", - "Mature B-Cell Neoplasms | ACH-000654", - "Mature B-Cell Neoplasms | ACH-000656", - "Mature B-Cell Neoplasms | ACH-000660", - "Mature B-Cell Neoplasms | ACH-000697", - "Mature B-Cell Neoplasms | ACH-000714", - "Mature B-Cell Neoplasms | ACH-000763", - "Mature B-Cell Neoplasms | ACH-000817", - "Mature B-Cell Neoplasms | ACH-000821", - "Mature B-Cell Neoplasms | ACH-000829", - "Mature B-Cell Neoplasms | ACH-000838", - "Mature B-Cell Neoplasms | ACH-000889", - "Mature B-Cell Neoplasms | ACH-000914", - "Mature B-Cell Neoplasms | ACH-000944", - "Mature B-Cell Neoplasms | ACH-001450", - "Mature B-Cell Neoplasms | ACH-001498", - "Mature B-Cell Neoplasms | ACH-001533", - "Mature B-Cell Neoplasms | ACH-001539", - "Mature B-Cell Neoplasms | ACH-001616", - "Mature B-Cell Neoplasms | ACH-001634", - "Mature B-Cell Neoplasms | ACH-001639", - "Mature B-Cell Neoplasms | ACH-001677", - "Mature B-Cell Neoplasms | ACH-001707", - "Mature B-Cell Neoplasms | ACH-001709", - "Mature B-Cell Neoplasms | ACH-002055", - "Mature B-Cell Neoplasms | ACH-002062", - "Mature B-Cell Neoplasms | ACH-002214", - "Mature B-Cell Neoplasms | ACH-002215", - "Mature B-Cell Neoplasms | ACH-002478", - "Mature B-Cell Neoplasms | ACH-002485", - "Mature B-Cell Neoplasms | ACH-002500", - "Mature B-Cell Neoplasms | ACH-002677", - "Mature B-Cell Neoplasms | ACH-002678" - ], - "type": "scattergl", - "x": { - "bdata": "t7c4QLlv6z/HxuxAxpkSQLDVsUDIH59AtUsPQeZaD0D/9Zu/peWLQEmVKT6ps7xA9oyGQMmJWEA5xw1APPubQC/Krz3T4/LAeCpTQB254z+1tfLAmnn9PkI7okAJczNAkT0lQP+fBEF5/AVBQ7qEQNSVEkAMDMQ/qvlkQKZ88j/hrPLAxnbGP4d6yEDrAOBA+C6XQIWsg0A9WaFAGtPywD5rzT8HPspARrPywFo4+z+M3PA/JsPywLsb8EB39kxA1UYRQABdz0C/939AwwBAQM31LUDEy7lAeIW8QIZZKkA=", - "dtype": "f4" - }, - "y": { - "bdata": "66ZlwO87kr9NKYLAyH8mwEBRi8DqQJnAT1a/wANvNMCmyj/AQ2hVwBbIZ8DvjJTA3bFvwMSbU8D6BSnAlDhUwCZ4LMCQLqu/bCk1wOQqOcBxeau/UqpCwFT8csDWkGnAO11wwF4loMDNqXfA7VAjwPvWb8CqPj7An25ywPGBNcA1Z6u/dAFVwCWQeMAmNZXAP2dkwJEGicA0/WrAkxurv7NHHMADXq7AIYWrvzooiMClkeW/oeOqv5M/nsBc/1DA8DcVwEF7jsASMzjABUNKwPE2+b86uWbAs2WcwDUbWMA=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000025", - "ACH-001067", - "ACH-002070" - ], - "hoverinfo": "text", - "marker": { - "color": "#FECB52", - "size": 7 - }, - "mode": "markers", - "name": "Meningothelial Tumor", - "text": [ - "Meningothelial Tumor | ACH-000025", - "Meningothelial Tumor | ACH-001067", - "Meningothelial Tumor | ACH-002070" - ], - "type": "scattergl", - "x": { - "bdata": "28RMQHnG8sDmH4I/", - "dtype": "f4" - }, - "y": { - "bdata": "nxIiQJ+aqr9v4ds/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000036", - "ACH-000040", - "ACH-000067", - "ACH-000075", - "ACH-000098", - "ACH-000128", - "ACH-000137", - "ACH-000152", - "ACH-000200", - "ACH-000208", - "ACH-000215", - "ACH-000231", - "ACH-000232", - "ACH-000244", - "ACH-000269", - "ACH-000273", - "ACH-000323", - "ACH-000329", - "ACH-000368", - "ACH-000370", - "ACH-000376", - "ACH-000389", - "ACH-000437", - "ACH-000445", - "ACH-000455", - "ACH-000464", - "ACH-000469", - "ACH-000479", - "ACH-000504", - "ACH-000558", - "ACH-000570", - "ACH-000571", - "ACH-000591", - "ACH-000592", - "ACH-000595", - "ACH-000609", - "ACH-000622", - "ACH-000623", - "ACH-000631", - "ACH-000634", - "ACH-000655", - "ACH-000673", - "ACH-000676", - "ACH-000738", - "ACH-000756", - "ACH-000760", - "ACH-000807", - "ACH-000819", - "ACH-000863", - "ACH-000887", - "ACH-001016", - "ACH-001126", - "ACH-001172", - "ACH-001329", - "ACH-001605", - "ACH-001606", - "ACH-001608", - "ACH-001609", - "ACH-001610", - "ACH-001611", - "ACH-001622", - "ACH-001623", - "ACH-001624", - "ACH-002228", - "ACH-002229", - "ACH-002230", - "ACH-002257", - "ACH-002269", - "ACH-002304", - "ACH-002680" - ], - "hoverinfo": "text", - "marker": { - "color": "#FD3216", - "size": 7 - }, - "mode": "markers", - "name": "Diffuse Glioma", - "text": [ - "Diffuse Glioma | ACH-000036", - "Diffuse Glioma | ACH-000040", - "Diffuse Glioma | ACH-000067", - "Diffuse Glioma | ACH-000075", - "Diffuse Glioma | ACH-000098", - "Diffuse Glioma | ACH-000128", - "Diffuse Glioma | ACH-000137", - "Diffuse Glioma | ACH-000152", - "Diffuse Glioma | ACH-000200", - "Diffuse Glioma | ACH-000208", - "Diffuse Glioma | ACH-000215", - "Diffuse Glioma | ACH-000231", - "Diffuse Glioma | ACH-000232", - "Diffuse Glioma | ACH-000244", - "Diffuse Glioma | ACH-000269", - "Diffuse Glioma | ACH-000273", - "Diffuse Glioma | ACH-000323", - "Diffuse Glioma | ACH-000329", - "Diffuse Glioma | ACH-000368", - "Diffuse Glioma | ACH-000370", - "Diffuse Glioma | ACH-000376", - "Diffuse Glioma | ACH-000389", - "Diffuse Glioma | ACH-000437", - "Diffuse Glioma | ACH-000445", - "Diffuse Glioma | ACH-000455", - "Diffuse Glioma | ACH-000464", - "Diffuse Glioma | ACH-000469", - "Diffuse Glioma | ACH-000479", - "Diffuse Glioma | ACH-000504", - "Diffuse Glioma | ACH-000558", - "Diffuse Glioma | ACH-000570", - "Diffuse Glioma | ACH-000571", - "Diffuse Glioma | ACH-000591", - "Diffuse Glioma | ACH-000592", - "Diffuse Glioma | ACH-000595", - "Diffuse Glioma | ACH-000609", - "Diffuse Glioma | ACH-000622", - "Diffuse Glioma | ACH-000623", - "Diffuse Glioma | ACH-000631", - "Diffuse Glioma | ACH-000634", - "Diffuse Glioma | ACH-000655", - "Diffuse Glioma | ACH-000673", - "Diffuse Glioma | ACH-000676", - "Diffuse Glioma | ACH-000738", - "Diffuse Glioma | ACH-000756", - "Diffuse Glioma | ACH-000760", - "Diffuse Glioma | ACH-000807", - "Diffuse Glioma | ACH-000819", - "Diffuse Glioma | ACH-000863", - "Diffuse Glioma | ACH-000887", - "Diffuse Glioma | ACH-001016", - "Diffuse Glioma | ACH-001126", - "Diffuse Glioma | ACH-001172", - "Diffuse Glioma | ACH-001329", - "Diffuse Glioma | ACH-001605", - "Diffuse Glioma | ACH-001606", - "Diffuse Glioma | ACH-001608", - "Diffuse Glioma | ACH-001609", - "Diffuse Glioma | ACH-001610", - "Diffuse Glioma | ACH-001611", - "Diffuse Glioma | ACH-001622", - "Diffuse Glioma | ACH-001623", - "Diffuse Glioma | ACH-001624", - "Diffuse Glioma | ACH-002228", - "Diffuse Glioma | ACH-002229", - "Diffuse Glioma | ACH-002230", - "Diffuse Glioma | ACH-002257", - "Diffuse Glioma | ACH-002269", - "Diffuse Glioma | ACH-002304", - "Diffuse Glioma | ACH-002680" - ], - "type": "scattergl", - "x": { - "bdata": "mh/hPVQB678x6tS/KOW3v/dpHT8lrPE/mnBjP14Hzb8X1PLASxKsvqTiD0CPJ+Y+wFaLQMRhVMA15j2+W1oSQN3XjD4pmb696Ux9vxwwrb+8bK5Ak16WvrwJTD9vE12/iNCAQBk8N8CVJqc/ykCZPtr/UMAvm8s/rKj4Pw0KJsBXzSs+pyIDwOfulD8KwX69m7I0wKcv17+u7X6/wujBP85Qgj7W0vLAj2OCQL0vhkAApx5AN1NhPxh4uT+L8Dg/l2YiQDfh2z81yARAfLjywGiXmkDAzgDAJaMwvmKG978AIA1ArVWKP8kgOj4SdIw/orEtvwdNHsBZeCG/767ywDrL8sCfwvLA+1m6velSX0CDyfLAASCkPQ==", - "dtype": "f4" - }, - "y": { - "bdata": "dVSBQJ5QkkCBQHhA32Z2QHhKnEBHHlI/EaJaQERHU0CHtaq/YZHkP5dKJEC+4kxAGIGRP1E2mkAg6nM/BXwiQLspF0BZ1bo/MTumQArZhz9JDMQ/LdJSQDadOkDw2mJAlt8vP6CKiECdrU1AM5QXQHcUcEBPAkZAoUttQE/oGkCEOZFAkcBZQDjAOUAl21xAuK7kP6XFfkD2cwlA6TYNQI79xD9ET6u/bqt1vweQoz+BnG1AhVhUP/tYuz70tBZAx7tCQO/Nnj/UBrc/HWSrv29tDT/d0YJAtCkuQNs8HEAaLwRAKf8FQHGeB0Be8hJABWOPQO2ni0Dy3J8/QMGrv1xIq78e8Kq/M7SjQER6uj9Q36q/DzOEQA==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000037" - ], - "hoverinfo": "text", - "marker": { - "color": "#00FE35", - "size": 7 - }, - "mode": "markers", - "name": "Sarcoma, NOS", - "text": [ - "Sarcoma, NOS | ACH-000037" - ], - "type": "scattergl", - "x": { - "bdata": "P0j4vw==", - "dtype": "f4" - }, - "y": { - "bdata": "yalAQA==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000039", - "ACH-000041", - "ACH-000052", - "ACH-000087", - "ACH-000210", - "ACH-000279", - "ACH-000391", - "ACH-000424", - "ACH-000499", - "ACH-001029", - "ACH-001038", - "ACH-001192", - "ACH-001193", - "ACH-001205", - "ACH-001283", - "ACH-001430", - "ACH-001431", - "ACH-002105", - "ACH-002106", - "ACH-002109", - "ACH-002110", - "ACH-002114", - "ACH-002116", - "ACH-002119", - "ACH-002160" - ], - "hoverinfo": "text", - "marker": { - "color": "#6A76FC", - "size": 7 - }, - "mode": "markers", - "name": "Ewing Sarcoma", - "text": [ - "Ewing Sarcoma | ACH-000039", - "Ewing Sarcoma | ACH-000041", - "Ewing Sarcoma | ACH-000052", - "Ewing Sarcoma | ACH-000087", - "Ewing Sarcoma | ACH-000210", - "Ewing Sarcoma | ACH-000279", - "Ewing Sarcoma | ACH-000391", - "Ewing Sarcoma | ACH-000424", - "Ewing Sarcoma | ACH-000499", - "Ewing Sarcoma | ACH-001029", - "Ewing Sarcoma | ACH-001038", - "Ewing Sarcoma | ACH-001192", - "Ewing Sarcoma | ACH-001193", - "Ewing Sarcoma | ACH-001205", - "Ewing Sarcoma | ACH-001283", - "Ewing Sarcoma | ACH-001430", - "Ewing Sarcoma | ACH-001431", - "Ewing Sarcoma | ACH-002105", - "Ewing Sarcoma | ACH-002106", - "Ewing Sarcoma | ACH-002109", - "Ewing Sarcoma | ACH-002110", - "Ewing Sarcoma | ACH-002114", - "Ewing Sarcoma | ACH-002116", - "Ewing Sarcoma | ACH-002119", - "Ewing Sarcoma | ACH-002160" - ], - "type": "scattergl", - "x": { - "bdata": "/wQSv7AlDb3bRMc+yCtKQOPfhT986IZAAj6OQCvLu0AnEVdADYStQHagTUDuKeo/G0GIP47ntz/g1CFAAqWKP1SgBkCcbHU/J7CIQOQ79z8jCM1ALs/ywJ3w8sBIC7FAhNuoQA==", - "dtype": "f4" - }, - "y": { - "bdata": "IXZBP4dmHb4FDwpA7+bKvkKtt75+OHm/UULXPw9Wiz/OXy8/OH50P0YH7b9y5B4/IKjGP47Tpb2pkLI+6oPIPvlNur5i51pA5uLuvzqBhz8Jrtm9eJ+qv/hpqr8LSEc/4wmlvg==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000047", - "ACH-000144", - "ACH-000216", - "ACH-000239", - "ACH-000247", - "ACH-000255", - "ACH-000303", - "ACH-000325", - "ACH-000344", - "ACH-000356", - "ACH-000383", - "ACH-000427", - "ACH-000466", - "ACH-000485", - "ACH-000507", - "ACH-000581", - "ACH-000616", - "ACH-000633", - "ACH-000736", - "ACH-000746", - "ACH-000758", - "ACH-000764", - "ACH-000793", - "ACH-000847", - "ACH-000880", - "ACH-000898", - "ACH-000911", - "ACH-000919", - "ACH-000932", - "ACH-000948", - "ACH-001368", - "ACH-001496", - "ACH-001497", - "ACH-001500", - "ACH-001544", - "ACH-001653", - "ACH-001654", - "ACH-001664", - "ACH-002141", - "ACH-002161", - "ACH-002202", - "ACH-002446", - "ACH-002705", - "ACH-002706" - ], - "hoverinfo": "text", - "marker": { - "color": "#FED4C4", - "size": 7 - }, - "mode": "markers", - "name": "Esophagogastric Adenocarcinoma", - "text": [ - "Esophagogastric Adenocarcinoma | ACH-000047", - "Esophagogastric Adenocarcinoma | ACH-000144", - "Esophagogastric Adenocarcinoma | ACH-000216", - "Esophagogastric Adenocarcinoma | ACH-000239", - "Esophagogastric Adenocarcinoma | ACH-000247", - "Esophagogastric Adenocarcinoma | ACH-000255", - "Esophagogastric Adenocarcinoma | ACH-000303", - "Esophagogastric Adenocarcinoma | ACH-000325", - "Esophagogastric Adenocarcinoma | ACH-000344", - "Esophagogastric Adenocarcinoma | ACH-000356", - "Esophagogastric Adenocarcinoma | ACH-000383", - "Esophagogastric Adenocarcinoma | ACH-000427", - "Esophagogastric Adenocarcinoma | ACH-000466", - "Esophagogastric Adenocarcinoma | ACH-000485", - "Esophagogastric Adenocarcinoma | ACH-000507", - "Esophagogastric Adenocarcinoma | ACH-000581", - "Esophagogastric Adenocarcinoma | ACH-000616", - "Esophagogastric Adenocarcinoma | ACH-000633", - "Esophagogastric Adenocarcinoma | ACH-000736", - "Esophagogastric Adenocarcinoma | ACH-000746", - "Esophagogastric Adenocarcinoma | ACH-000758", - "Esophagogastric Adenocarcinoma | ACH-000764", - "Esophagogastric Adenocarcinoma | ACH-000793", - "Esophagogastric Adenocarcinoma | ACH-000847", - "Esophagogastric Adenocarcinoma | ACH-000880", - "Esophagogastric Adenocarcinoma | ACH-000898", - "Esophagogastric Adenocarcinoma | ACH-000911", - "Esophagogastric Adenocarcinoma | ACH-000919", - "Esophagogastric Adenocarcinoma | ACH-000932", - "Esophagogastric Adenocarcinoma | ACH-000948", - "Esophagogastric Adenocarcinoma | ACH-001368", - "Esophagogastric Adenocarcinoma | ACH-001496", - "Esophagogastric Adenocarcinoma | ACH-001497", - "Esophagogastric Adenocarcinoma | ACH-001500", - "Esophagogastric Adenocarcinoma | ACH-001544", - "Esophagogastric Adenocarcinoma | ACH-001653", - "Esophagogastric Adenocarcinoma | ACH-001654", - "Esophagogastric Adenocarcinoma | ACH-001664", - "Esophagogastric Adenocarcinoma | ACH-002141", - "Esophagogastric Adenocarcinoma | ACH-002161", - "Esophagogastric Adenocarcinoma | ACH-002202", - "Esophagogastric Adenocarcinoma | ACH-002446", - "Esophagogastric Adenocarcinoma | ACH-002705", - "Esophagogastric Adenocarcinoma | ACH-002706" - ], - "type": "scattergl", - "x": { - "bdata": "KoaZQC9qNMBw1tA/jXZwvdRGM0CQRqg/qqQNQHFKaEA+XU0/QySWP2aYA70+vPLA0QapvpPCBEBPEINAa5HKP3I5Bb8/nlNAS45eQJ5Dqj9d00tAUsTywLk9V0ALwvLAwCWMQNPURT/CqHhAbIHPP9eYf0CSKWRAZMUnQGiUdj+6a38/0I5OQJx+8b6tEPs/BXkBQNnFo0C1QKZAcmweQLj4GEC/AEBAIDotQFyygEA=", - "dtype": "f4" - }, - "y": { - "bdata": "AGfAv1HNsT7J2oA/1BMQPfTowL+UAxZA/U0avyNRPsAAwJA/3xu/vqk24r+rcau/4AgrQOu9nb+kqtW/OfgTwMB4B0AdwZW/ZH3+v514H8AyYZK/t6+qv+/uJ8Dj5qq/wtBDvro4/L9y65m/0dqmvq/wCcCEp22/P3IJwCJc6b8WUdy/3156PwCYyr9u+J2/6QsaQJqvSsBhSBHAhFpRv34Rhr407t++hIfGvoyKM78=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000053", - "ACH-000101", - "ACH-000226", - "ACH-000233", - "ACH-000338", - "ACH-000664", - "ACH-000773", - "ACH-001111", - "ACH-001119", - "ACH-001737" - ], - "hoverinfo": "text", - "marker": { - "color": "#FE00CE", - "size": 7 - }, - "mode": "markers", - "name": "Mature T and NK Neoplasms", - "text": [ - "Mature T and NK Neoplasms | ACH-000053", - "Mature T and NK Neoplasms | ACH-000101", - "Mature T and NK Neoplasms | ACH-000226", - "Mature T and NK Neoplasms | ACH-000233", - "Mature T and NK Neoplasms | ACH-000338", - "Mature T and NK Neoplasms | ACH-000664", - "Mature T and NK Neoplasms | ACH-000773", - "Mature T and NK Neoplasms | ACH-001111", - "Mature T and NK Neoplasms | ACH-001119", - "Mature T and NK Neoplasms | ACH-001737" - ], - "type": "scattergl", - "x": { - "bdata": "kZnlP2+nqEBMknFAuvBdQGr/jj9RsuJAmrENQOb/+z++WrK/hmjrPw==", - "dtype": "f4" - }, - "y": { - "bdata": "tmFQwKdKgMAN1j3AB/4hwLk+Or8kLIHAvropwMsj378zGhe/0hKxvg==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000054" - ], - "hoverinfo": "text", - "marker": { - "color": "#0DF9FF", - "size": 7 - }, - "mode": "markers", - "name": "Fibrosarcoma", - "text": [ - "Fibrosarcoma | ACH-000054" - ], - "type": "scattergl", - "x": { - "bdata": "PNxYPw==", - "dtype": "f4" - }, - "y": { - "bdata": "DSHFPw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000055", - "ACH-000095", - "ACH-000160", - "ACH-000211", - "ACH-000776", - "ACH-001020", - "ACH-001028", - "ACH-001031", - "ACH-001033", - "ACH-001053", - "ACH-001054", - "ACH-001232", - "ACH-001289", - "ACH-001670", - "ACH-001711" - ], - "hoverinfo": "text", - "marker": { - "color": "#F6F926", - "size": 7 - }, - "mode": "markers", - "name": "Embryonal Tumor", - "text": [ - "Embryonal Tumor | ACH-000055", - "Embryonal Tumor | ACH-000095", - "Embryonal Tumor | ACH-000160", - "Embryonal Tumor | ACH-000211", - "Embryonal Tumor | ACH-000776", - "Embryonal Tumor | ACH-001020", - "Embryonal Tumor | ACH-001028", - "Embryonal Tumor | ACH-001031", - "Embryonal Tumor | ACH-001033", - "Embryonal Tumor | ACH-001053", - "Embryonal Tumor | ACH-001054", - "Embryonal Tumor | ACH-001232", - "Embryonal Tumor | ACH-001289", - "Embryonal Tumor | ACH-001670", - "Embryonal Tumor | ACH-001711" - ], - "type": "scattergl", - "x": { - "bdata": "ibw6QBroEkA4irRAfyyLPZb46D+ejrw/0uaPQJ17kEBURLY/J0DBP77nl0CjfDe9KxjUP/8xOkCFPRVA", - "dtype": "f4" - }, - "y": { - "bdata": "0WiPvyMvKb8AIUM/ENcrQI1QfT/FTaI/7yUfv9/oYz/PRRE/uqc+vmJit79VYYVAs9OKviGNGT+/kg0/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000070", - "ACH-000151", - "ACH-000782", - "ACH-000922", - "ACH-000938", - "ACH-000960", - "ACH-001484", - "ACH-001520", - "ACH-001669", - "ACH-001735", - "ACH-001736", - "ACH-001993", - "ACH-002059" - ], - "hoverinfo": "text", - "marker": { - "color": "#FF9616", - "size": 7 - }, - "mode": "markers", - "name": "B-Lymphoblastic Leukemia/Lymphoma", - "text": [ - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000070", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000151", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000782", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000922", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000938", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000960", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001484", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001520", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001669", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001735", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001736", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001993", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-002059" - ], - "type": "scattergl", - "x": { - "bdata": "eseKQDzO9j+rn3lALfbDQH0Ko0A+wYpAkSFnQMFolkChZ7tA2M9NQDSNy0Cd//w/hnqAQA==", - "dtype": "f4" - }, - "y": { - "bdata": "so+AwHF9b8AWLHnATSSYwLuiocAAvYrA1lhHwKBpWsBjKIvANv+JwFY3nsDjc0fAuUFAwA==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000074", - "ACH-000076", - "ACH-000198", - "ACH-000295", - "ACH-000326", - "ACH-000551", - "ACH-000604", - "ACH-000920", - "ACH-000983", - "ACH-002061" - ], - "hoverinfo": "text", - "marker": { - "color": "#479B55", - "size": 7 - }, - "mode": "markers", - "name": "Myeloproliferative Neoplasms", - "text": [ - "Myeloproliferative Neoplasms | ACH-000074", - "Myeloproliferative Neoplasms | ACH-000076", - "Myeloproliferative Neoplasms | ACH-000198", - "Myeloproliferative Neoplasms | ACH-000295", - "Myeloproliferative Neoplasms | ACH-000326", - "Myeloproliferative Neoplasms | ACH-000551", - "Myeloproliferative Neoplasms | ACH-000604", - "Myeloproliferative Neoplasms | ACH-000920", - "Myeloproliferative Neoplasms | ACH-000983", - "Myeloproliferative Neoplasms | ACH-002061" - ], - "type": "scattergl", - "x": { - "bdata": "y4VSQKHkfkCcTfFACYRtP2RbjUA2u25AEyctQKPzlD9a4qlAwRBtQA==", - "dtype": "f4" - }, - "y": { - "bdata": "2f9GwOTuL8AlO5zAdLUgwKg8XMC82UjAr2sKwEFHmL/URoXAujoxwA==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000077", - "ACH-000583", - "ACH-001197", - "ACH-001642" - ], - "hoverinfo": "text", - "marker": { - "color": "#EEA6FB", - "size": 7 - }, - "mode": "markers", - "name": "Non-Hodgkin Lymphoma", - "text": [ - "Non-Hodgkin Lymphoma | ACH-000077", - "Non-Hodgkin Lymphoma | ACH-000583", - "Non-Hodgkin Lymphoma | ACH-001197", - "Non-Hodgkin Lymphoma | ACH-001642" - ], - "type": "scattergl", - "x": { - "bdata": "RAV+QLuy8sBfUS1AmUrJPw==", - "dtype": "f4" - }, - "y": { - "bdata": "nuzZv5vMq7/8YULAFh0GwA==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000078", - "ACH-000099", - "ACH-000120", - "ACH-000149", - "ACH-000203", - "ACH-000227", - "ACH-000259", - "ACH-000260", - "ACH-000310", - "ACH-000312", - "ACH-000341", - "ACH-000366", - "ACH-000804", - "ACH-001188", - "ACH-001300", - "ACH-001301", - "ACH-001302", - "ACH-001303", - "ACH-001338", - "ACH-001344", - "ACH-001354", - "ACH-001366", - "ACH-001367", - "ACH-001481", - "ACH-001548", - "ACH-001603", - "ACH-001674", - "ACH-002080", - "ACH-002083", - "ACH-002261", - "ACH-002278", - "ACH-002280", - "ACH-002282", - "ACH-002283", - "ACH-002284", - "ACH-002285", - "ACH-002922" - ], - "hoverinfo": "text", - "marker": { - "color": "#DC587D", - "size": 7 - }, - "mode": "markers", - "name": "Neuroblastoma", - "text": [ - "Neuroblastoma | ACH-000078", - "Neuroblastoma | ACH-000099", - "Neuroblastoma | ACH-000120", - "Neuroblastoma | ACH-000149", - "Neuroblastoma | ACH-000203", - "Neuroblastoma | ACH-000227", - "Neuroblastoma | ACH-000259", - "Neuroblastoma | ACH-000260", - "Neuroblastoma | ACH-000310", - "Neuroblastoma | ACH-000312", - "Neuroblastoma | ACH-000341", - "Neuroblastoma | ACH-000366", - "Neuroblastoma | ACH-000804", - "Neuroblastoma | ACH-001188", - "Neuroblastoma | ACH-001300", - "Neuroblastoma | ACH-001301", - "Neuroblastoma | ACH-001302", - "Neuroblastoma | ACH-001303", - "Neuroblastoma | ACH-001338", - "Neuroblastoma | ACH-001344", - "Neuroblastoma | ACH-001354", - "Neuroblastoma | ACH-001366", - "Neuroblastoma | ACH-001367", - "Neuroblastoma | ACH-001481", - "Neuroblastoma | ACH-001548", - "Neuroblastoma | ACH-001603", - "Neuroblastoma | ACH-001674", - "Neuroblastoma | ACH-002080", - "Neuroblastoma | ACH-002083", - "Neuroblastoma | ACH-002261", - "Neuroblastoma | ACH-002278", - "Neuroblastoma | ACH-002280", - "Neuroblastoma | ACH-002282", - "Neuroblastoma | ACH-002283", - "Neuroblastoma | ACH-002284", - "Neuroblastoma | ACH-002285", - "Neuroblastoma | ACH-002922" - ], - "type": "scattergl", - "x": { - "bdata": "UFyKP4JEekBzgac/o8FAQPj7Kb77VQzAUhuzQJnPHUC9svW/1R/IPx4gbTs0E/o/gnmLQIEiL0B3vHdAjkHHvjGtbj9/mB0+5haEQLW5BD+KJ8U/APQwQG/1VECjwjc9n6V4PiH+JEAEaUpAl8jywFYHpUC0cpxAUqGKQOQFiECHcV1A/XIjQPTd8sAnQQlBSiFVQA==", - "dtype": "f4" - }, - "y": { - "bdata": "hVWhvtdvWr8hXNE/WGtiPyQrFT8T/Ri/tm2fv7sP3z9pcyc+2AmPv0ZyfT/xAyi+6YkPv5cqiT/9Vnq+VaizP1X1Xr6pb0c+yob4v2iexj8lOA29fNvCvouDfL9Saw1AFR4pP8loBD4gwNK/UGirv8a0F0D0g5y/rK+5vv39Zb9aLn++Ldu1P5LOqr/ph/M+WT6Wvw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000082", - "ACH-000359", - "ACH-000364", - "ACH-000410", - "ACH-000748", - "ACH-001001", - "ACH-001526", - "ACH-001715", - "ACH-001814", - "ACH-002067", - "ACH-002069", - "ACH-002471", - "ACH-002834" - ], - "hoverinfo": "text", - "marker": { - "color": "#D626FF", - "size": 7 - }, - "mode": "markers", - "name": "Osteosarcoma", - "text": [ - "Osteosarcoma | ACH-000082", - "Osteosarcoma | ACH-000359", - "Osteosarcoma | ACH-000364", - "Osteosarcoma | ACH-000410", - "Osteosarcoma | ACH-000748", - "Osteosarcoma | ACH-001001", - "Osteosarcoma | ACH-001526", - "Osteosarcoma | ACH-001715", - "Osteosarcoma | ACH-001814", - "Osteosarcoma | ACH-002067", - "Osteosarcoma | ACH-002069", - "Osteosarcoma | ACH-002471", - "Osteosarcoma | ACH-002834" - ], - "type": "scattergl", - "x": { - "bdata": "EnVawMOUMcDiTxpADp+MP5wg7z+jKbNAbqTPvwOL5r9wLgvALquoP1StSr6meHK+RtzywA==", - "dtype": "f4" - }, - "y": { - "bdata": "QxswQIzgH0DaOTlAKN31P82cl0AWuxu/S8kEQNwSFEDOGFtA84k5P90HaEDuvf8/dQ+qvw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000086", - "ACH-000092", - "ACH-000153", - "ACH-000319", - "ACH-000331", - "ACH-000335", - "ACH-000367", - "ACH-000569", - "ACH-000645", - "ACH-000648", - "ACH-001547", - "ACH-001555", - "ACH-001556", - "ACH-001557", - "ACH-001558", - "ACH-001559", - "ACH-001560", - "ACH-001562", - "ACH-001977", - "ACH-001992", - "ACH-002033" - ], - "hoverinfo": "text", - "marker": { - "color": "#6E899C", - "size": 7 - }, - "mode": "markers", - "name": "Pleural Mesothelioma", - "text": [ - "Pleural Mesothelioma | ACH-000086", - "Pleural Mesothelioma | ACH-000092", - "Pleural Mesothelioma | ACH-000153", - "Pleural Mesothelioma | ACH-000319", - "Pleural Mesothelioma | ACH-000331", - "Pleural Mesothelioma | ACH-000335", - "Pleural Mesothelioma | ACH-000367", - "Pleural Mesothelioma | ACH-000569", - "Pleural Mesothelioma | ACH-000645", - "Pleural Mesothelioma | ACH-000648", - "Pleural Mesothelioma | ACH-001547", - "Pleural Mesothelioma | ACH-001555", - "Pleural Mesothelioma | ACH-001556", - "Pleural Mesothelioma | ACH-001557", - "Pleural Mesothelioma | ACH-001558", - "Pleural Mesothelioma | ACH-001559", - "Pleural Mesothelioma | ACH-001560", - "Pleural Mesothelioma | ACH-001562", - "Pleural Mesothelioma | ACH-001977", - "Pleural Mesothelioma | ACH-001992", - "Pleural Mesothelioma | ACH-002033" - ], - "type": "scattergl", - "x": { - "bdata": "ImwZQIuoAcBTe7K/QTeqv+c9OD+dNw5AOMfywPV0TD91Ce2/yq6OP5m5Kr8eA6U97IXOP8afVD+J2fLAgsLywHra8sBIxfLAF79+QAAuQkAv6zbA", - "dtype": "f4" - }, - "y": { - "bdata": "5XcEQIBPJEDI01ZAspNiQOJKGkDeEPs+VP+rv165bz8TVD9AFGYNQG1BfkDfRzVA49qIP+baNEDeyqq/H46qv3ilqr8dnaq/dlcHv35Zej+R9oc/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000090", - "ACH-000115", - "ACH-000956", - "ACH-000977", - "ACH-000979", - "ACH-001422", - "ACH-001627", - "ACH-001648", - "ACH-001649" - ], - "hoverinfo": "text", - "marker": { - "color": "#00B5F7", - "size": 7 - }, - "mode": "markers", - "name": "Prostate Adenocarcinoma", - "text": [ - "Prostate Adenocarcinoma | ACH-000090", - "Prostate Adenocarcinoma | ACH-000115", - "Prostate Adenocarcinoma | ACH-000956", - "Prostate Adenocarcinoma | ACH-000977", - "Prostate Adenocarcinoma | ACH-000979", - "Prostate Adenocarcinoma | ACH-001422", - "Prostate Adenocarcinoma | ACH-001627", - "Prostate Adenocarcinoma | ACH-001648", - "Prostate Adenocarcinoma | ACH-001649" - ], - "type": "scattergl", - "x": { - "bdata": "Qx5RPLnXUsAjDwBAGFSZQBp4mz+jInPAhLrywHHG8sC75fLA", - "dtype": "f4" - }, - "y": { - "bdata": "CzfJP0aODz4te76/ZnG/vxHlbj8DVC+/hC6rv6wSq7/FGau/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000096", - "ACH-000172", - "ACH-000533", - "ACH-000597", - "ACH-001099", - "ACH-001128", - "ACH-001211", - "ACH-001212", - "ACH-001532" - ], - "hoverinfo": "text", - "marker": { - "color": "#B68E00", - "size": 7 - }, - "mode": "markers", - "name": "Rhabdoid Cancer", - "text": [ - "Rhabdoid Cancer | ACH-000096", - "Rhabdoid Cancer | ACH-000172", - "Rhabdoid Cancer | ACH-000533", - "Rhabdoid Cancer | ACH-000597", - "Rhabdoid Cancer | ACH-001099", - "Rhabdoid Cancer | ACH-001128", - "Rhabdoid Cancer | ACH-001211", - "Rhabdoid Cancer | ACH-001212", - "Rhabdoid Cancer | ACH-001532" - ], - "type": "scattergl", - "x": { - "bdata": "KC8dQOZq5T92lqdAPdU+QBx0s0AjmglAIPAaQM3byz+GFZ9A", - "dtype": "f4" - }, - "y": { - "bdata": "1uU3P0X8sD/F6YY+bzzJP0w2gz85/gk/vWdUP4MR9T9elDW/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000100", - "ACH-000169", - "ACH-000607", - "ACH-000833", - "ACH-001050", - "ACH-001096", - "ACH-001184", - "ACH-001196", - "ACH-001740", - "ACH-001745", - "ACH-001750", - "ACH-001765", - "ACH-002048" - ], - "hoverinfo": "text", - "marker": { - "color": "#C9FBE5", - "size": 7 - }, - "mode": "markers", - "name": "Rhabdomyosarcoma", - "text": [ - "Rhabdomyosarcoma | ACH-000100", - "Rhabdomyosarcoma | ACH-000169", - "Rhabdomyosarcoma | ACH-000607", - "Rhabdomyosarcoma | ACH-000833", - "Rhabdomyosarcoma | ACH-001050", - "Rhabdomyosarcoma | ACH-001096", - "Rhabdomyosarcoma | ACH-001184", - "Rhabdomyosarcoma | ACH-001196", - "Rhabdomyosarcoma | ACH-001740", - "Rhabdomyosarcoma | ACH-001745", - "Rhabdomyosarcoma | ACH-001750", - "Rhabdomyosarcoma | ACH-001765", - "Rhabdomyosarcoma | ACH-002048" - ], - "type": "scattergl", - "x": { - "bdata": "qXQqQFUJJkC3nuo/NOU5QIYyA7/KMpdAOpZ7QNwtOECMSsU/giAaQOOIFECPO25A37yjQA==", - "dtype": "f4" - }, - "y": { - "bdata": "bPFCvwcwqT1p1Gs/EpI+vhoIfkDJjea+1rBhv2kaMT9o7AY++0vrvp/xsz8YnZS/nOiovg==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000108", - "ACH-000685" - ], - "hoverinfo": "text", - "marker": { - "color": "#FF0092", - "size": 7 - }, - "mode": "markers", - "name": "Adenosquamous Carcinoma of the Pancreas", - "text": [ - "Adenosquamous Carcinoma of the Pancreas | ACH-000108", - "Adenosquamous Carcinoma of the Pancreas | ACH-000685" - ], - "type": "scattergl", - "x": { - "bdata": "lUUdwEgzN0A=", - "dtype": "f4" - }, - "y": { - "bdata": "nnF5P1tXFUA=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000133", - "ACH-001310", - "ACH-001453", - "ACH-002210", - "ACH-002247", - "ACH-002462", - "ACH-002463", - "ACH-002464", - "ACH-002465", - "ACH-002467" - ], - "hoverinfo": "text", - "marker": { - "color": "#22FFA7", - "size": 7 - }, - "mode": "markers", - "name": "Non-Cancerous", - "text": [ - "Non-Cancerous | ACH-000133", - "Non-Cancerous | ACH-001310", - "Non-Cancerous | ACH-001453", - "Non-Cancerous | ACH-002210", - "Non-Cancerous | ACH-002247", - "Non-Cancerous | ACH-002462", - "Non-Cancerous | ACH-002463", - "Non-Cancerous | ACH-002464", - "Non-Cancerous | ACH-002465", - "Non-Cancerous | ACH-002467" - ], - "type": "scattergl", - "x": { - "bdata": "xpyUPBm98sAHz1w/koekQLDJ8sDb3vLA+NnywMPV8sCF1PLAB9/ywA==", - "dtype": "f4" - }, - "y": { - "bdata": "DslqQBMhq7+sQA1A/LdgwGbCqr8mIqu/sUyrv90brL+yi6u/ylOrvw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000141", - "ACH-001607", - "ACH-001619", - "ACH-001850", - "ACH-001861", - "ACH-001961" - ], - "hoverinfo": "text", - "marker": { - "color": "#E3EE9E", - "size": 7 - }, - "mode": "markers", - "name": "Intracholecystic Papillary Neoplasm", - "text": [ - "Intracholecystic Papillary Neoplasm | ACH-000141", - "Intracholecystic Papillary Neoplasm | ACH-001607", - "Intracholecystic Papillary Neoplasm | ACH-001619", - "Intracholecystic Papillary Neoplasm | ACH-001850", - "Intracholecystic Papillary Neoplasm | ACH-001861", - "Intracholecystic Papillary Neoplasm | ACH-001961" - ], - "type": "scattergl", - "x": { - "bdata": "xNbywAldL0DOXdq/eU8xQJ6x8sBfE/s/", - "dtype": "f4" - }, - "y": { - "bdata": "kQmrvzzujL+Vag1AmPI2vuvxqr8/nh6/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000145", - "ACH-000505", - "ACH-002785" - ], - "hoverinfo": "text", - "marker": { - "color": "#86CE00", - "size": 7 - }, - "mode": "markers", - "name": "Leiomyosarcoma", - "text": [ - "Leiomyosarcoma | ACH-000145", - "Leiomyosarcoma | ACH-000505", - "Leiomyosarcoma | ACH-002785" - ], - "type": "scattergl", - "x": { - "bdata": "AiMRwNwxQ8C4Iey/", - "dtype": "f4" - }, - "y": { - "bdata": "GXs6QN11QkAodWw/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000159", - "ACH-000189", - "ACH-000234", - "ACH-000246", - "ACH-000250", - "ACH-000262", - "ACH-000272", - "ACH-000313", - "ACH-000317", - "ACH-000375", - "ACH-000385", - "ACH-000411", - "ACH-000433", - "ACH-000459", - "ACH-000484", - "ACH-000495", - "ACH-000649", - "ACH-000684", - "ACH-000709", - "ACH-000792", - "ACH-000907", - "ACH-001163", - "ACH-001194", - "ACH-001398", - "ACH-001687", - "ACH-001688", - "ACH-002150", - "ACH-002189", - "ACH-002533" - ], - "hoverinfo": "text", - "marker": { - "color": "#BC7196", - "size": 7 - }, - "mode": "markers", - "name": "Renal Cell Carcinoma", - "text": [ - "Renal Cell Carcinoma | ACH-000159", - "Renal Cell Carcinoma | ACH-000189", - "Renal Cell Carcinoma | ACH-000234", - "Renal Cell Carcinoma | ACH-000246", - "Renal Cell Carcinoma | ACH-000250", - "Renal Cell Carcinoma | ACH-000262", - "Renal Cell Carcinoma | ACH-000272", - "Renal Cell Carcinoma | ACH-000313", - "Renal Cell Carcinoma | ACH-000317", - "Renal Cell Carcinoma | ACH-000375", - "Renal Cell Carcinoma | ACH-000385", - "Renal Cell Carcinoma | ACH-000411", - "Renal Cell Carcinoma | ACH-000433", - "Renal Cell Carcinoma | ACH-000459", - "Renal Cell Carcinoma | ACH-000484", - "Renal Cell Carcinoma | ACH-000495", - "Renal Cell Carcinoma | ACH-000649", - "Renal Cell Carcinoma | ACH-000684", - "Renal Cell Carcinoma | ACH-000709", - "Renal Cell Carcinoma | ACH-000792", - "Renal Cell Carcinoma | ACH-000907", - "Renal Cell Carcinoma | ACH-001163", - "Renal Cell Carcinoma | ACH-001194", - "Renal Cell Carcinoma | ACH-001398", - "Renal Cell Carcinoma | ACH-001687", - "Renal Cell Carcinoma | ACH-001688", - "Renal Cell Carcinoma | ACH-002150", - "Renal Cell Carcinoma | ACH-002189", - "Renal Cell Carcinoma | ACH-002533" - ], - "type": "scattergl", - "x": { - "bdata": "iFm1v3ff8sAKpB7Aq8DywNyv8sDQt/LAuc7ywHSHOcC5u/LA1OV1QGs+Sz4ieps/xIBtv98pvMDy3fLAQgjFv3ZD8T+uFQu/i+YkwNTE9T5Kv1XAiGOqPxC88sDIc1e+osTywHTC8sD2wfLAQBpXwKOMQkA=", - "dtype": "f4" - }, - "y": { - "bdata": "OxmZPwgTq7/qY0pAPJCrvwpCq78hFqu/W+mqv9ODC0AUj6u/bEubPN+NCkAVYhNAqhhKQEdNJj/ayaq/Ro4xQGIKEkDuC1NAoYcUQMJHj0BzcXFAY2Wuvzz4qr91Vm8/9E6rv7Owq79U8aq/EakbQH3cXb4=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000163", - "ACH-000181", - "ACH-000188", - "ACH-000207", - "ACH-000228", - "ACH-000238", - "ACH-000415", - "ACH-000472", - "ACH-000500", - "ACH-000503", - "ACH-000518", - "ACH-000546", - "ACH-000548", - "ACH-000549", - "ACH-000606", - "ACH-000618", - "ACH-000619", - "ACH-000630", - "ACH-000682", - "ACH-000732", - "ACH-000735", - "ACH-000740", - "ACH-000762", - "ACH-000771", - "ACH-000778", - "ACH-000794", - "ACH-000832", - "ACH-000836", - "ACH-000846", - "ACH-001228", - "ACH-001229", - "ACH-001331", - "ACH-001332", - "ACH-001346", - "ACH-001347", - "ACH-001385", - "ACH-001509", - "ACH-001510", - "ACH-001511", - "ACH-001542", - "ACH-001543", - "ACH-001625", - "ACH-001626", - "ACH-001641", - "ACH-001675", - "ACH-001690", - "ACH-001691", - "ACH-001692", - "ACH-001694", - "ACH-001695", - "ACH-001696", - "ACH-001698", - "ACH-001699", - "ACH-001701", - "ACH-002029", - "ACH-002030", - "ACH-002042", - "ACH-002043", - "ACH-002044", - "ACH-002045", - "ACH-002212", - "ACH-002249", - "ACH-002250", - "ACH-002251", - "ACH-002265", - "ACH-002294", - "ACH-002295", - "ACH-002296", - "ACH-002297", - "ACH-002298", - "ACH-002305" - ], - "hoverinfo": "text", - "marker": { - "color": "#7E7DCD", - "size": 7 - }, - "mode": "markers", - "name": "Head and Neck Squamous Cell Carcinoma", - "text": [ - "Head and Neck Squamous Cell Carcinoma | ACH-000163", - "Head and Neck Squamous Cell Carcinoma | ACH-000181", - "Head and Neck Squamous Cell Carcinoma | ACH-000188", - "Head and Neck Squamous Cell Carcinoma | ACH-000207", - "Head and Neck Squamous Cell Carcinoma | ACH-000228", - "Head and Neck Squamous Cell Carcinoma | ACH-000238", - "Head and Neck Squamous Cell Carcinoma | ACH-000415", - "Head and Neck Squamous Cell Carcinoma | ACH-000472", - "Head and Neck Squamous Cell Carcinoma | ACH-000500", - "Head and Neck Squamous Cell Carcinoma | ACH-000503", - "Head and Neck Squamous Cell Carcinoma | ACH-000518", - "Head and Neck Squamous Cell Carcinoma | ACH-000546", - "Head and Neck Squamous Cell Carcinoma | ACH-000548", - "Head and Neck Squamous Cell Carcinoma | ACH-000549", - "Head and Neck Squamous Cell Carcinoma | ACH-000606", - "Head and Neck Squamous Cell Carcinoma | ACH-000618", - "Head and Neck Squamous Cell Carcinoma | ACH-000619", - "Head and Neck Squamous Cell Carcinoma | ACH-000630", - "Head and Neck Squamous Cell Carcinoma | ACH-000682", - "Head and Neck Squamous Cell Carcinoma | ACH-000732", - "Head and Neck Squamous Cell Carcinoma | ACH-000735", - "Head and Neck Squamous Cell Carcinoma | ACH-000740", - "Head and Neck Squamous Cell Carcinoma | ACH-000762", - "Head and Neck Squamous Cell Carcinoma | ACH-000771", - "Head and Neck Squamous Cell Carcinoma | ACH-000778", - "Head and Neck Squamous Cell Carcinoma | ACH-000794", - "Head and Neck Squamous Cell Carcinoma | ACH-000832", - "Head and Neck Squamous Cell Carcinoma | ACH-000836", - "Head and Neck Squamous Cell Carcinoma | ACH-000846", - "Head and Neck Squamous Cell Carcinoma | ACH-001228", - "Head and Neck Squamous Cell Carcinoma | ACH-001229", - "Head and Neck Squamous Cell Carcinoma | ACH-001331", - "Head and Neck Squamous Cell Carcinoma | ACH-001332", - "Head and Neck Squamous Cell Carcinoma | ACH-001346", - "Head and Neck Squamous Cell Carcinoma | ACH-001347", - "Head and Neck Squamous Cell Carcinoma | ACH-001385", - "Head and Neck Squamous Cell Carcinoma | ACH-001509", - "Head and Neck Squamous Cell Carcinoma | ACH-001510", - "Head and Neck Squamous Cell Carcinoma | ACH-001511", - "Head and Neck Squamous Cell Carcinoma | ACH-001542", - "Head and Neck Squamous Cell Carcinoma | ACH-001543", - "Head and Neck Squamous Cell Carcinoma | ACH-001625", - "Head and Neck Squamous Cell Carcinoma | ACH-001626", - "Head and Neck Squamous Cell Carcinoma | ACH-001641", - "Head and Neck Squamous Cell Carcinoma | ACH-001675", - "Head and Neck Squamous Cell Carcinoma | ACH-001690", - "Head and Neck Squamous Cell Carcinoma | ACH-001691", - "Head and Neck Squamous Cell Carcinoma | ACH-001692", - "Head and Neck Squamous Cell Carcinoma | ACH-001694", - "Head and Neck Squamous Cell Carcinoma | ACH-001695", - "Head and Neck Squamous Cell Carcinoma | ACH-001696", - "Head and Neck Squamous Cell Carcinoma | ACH-001698", - "Head and Neck Squamous Cell Carcinoma | ACH-001699", - "Head and Neck Squamous Cell Carcinoma | ACH-001701", - "Head and Neck Squamous Cell Carcinoma | ACH-002029", - "Head and Neck Squamous Cell Carcinoma | ACH-002030", - "Head and Neck Squamous Cell Carcinoma | ACH-002042", - "Head and Neck Squamous Cell Carcinoma | ACH-002043", - "Head and Neck Squamous Cell Carcinoma | ACH-002044", - "Head and Neck Squamous Cell Carcinoma | ACH-002045", - "Head and Neck Squamous Cell Carcinoma | ACH-002212", - "Head and Neck Squamous Cell Carcinoma | ACH-002249", - "Head and Neck Squamous Cell Carcinoma | ACH-002250", - "Head and Neck Squamous Cell Carcinoma | ACH-002251", - "Head and Neck Squamous Cell Carcinoma | ACH-002265", - "Head and Neck Squamous Cell Carcinoma | ACH-002294", - "Head and Neck Squamous Cell Carcinoma | ACH-002295", - "Head and Neck Squamous Cell Carcinoma | ACH-002296", - "Head and Neck Squamous Cell Carcinoma | ACH-002297", - "Head and Neck Squamous Cell Carcinoma | ACH-002298", - "Head and Neck Squamous Cell Carcinoma | ACH-002305" - ], - "type": "scattergl", - "x": { - "bdata": "IlGvvfQ1rj/+Wb4/CczywC3o8sDUZmg/Fc/ywNEWkL8miAq/gLzywGasUEBEnixAWAGtv2w/8j+UJCZA63GiQIxzOEBWUhFAuCM8QB6qiD8oYVA/biaNP3cUQD8GvfLAjmXHv2QIBEATP6lAaVzUP4N3dEB7Kay/Ir0FQHDX8sBG1PLAd6DTP/Zj4T/pHsFAiDIYv4mo0T89dJi/E8WIQOim4D9Z8h7AReAgwDTR8sCmq8M/wLBMQP6TZL6D24ZA7bUoQNzz3T/Olt0/WO3fP1LDr0DlxilAERaaQFm9WkDcLt6/dAYmQAUmw0AugRdA0crywJVHQUAtz5Y/7nsMQKnM8sAlGvA/7RfwvQ99o0A2/UBAYQNrQOfe8sA=", - "dtype": "f4" - }, - "y": { - "bdata": 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ACH-002041" - ], - "type": "scattergl", - "x": { - "bdata": "Jcs/P0u0kz+XX2K/r5sPwM9wZsACtIc9nYvUvg==", - "dtype": "f4" - }, - "y": { - "bdata": "HsMGQOEBA0BZpnZA/JHSP1cDWj8AVPA/VXRpQA==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000182", - "ACH-000377", - "ACH-001862", - "ACH-002023" - ], - "hoverinfo": "text", - "marker": { - "color": "#E48F72", - "size": 7 - }, - "mode": "markers", - "name": "Ampullary Carcinoma", - "text": [ - "Ampullary Carcinoma | ACH-000182", - "Ampullary Carcinoma | ACH-000377", - "Ampullary Carcinoma | ACH-001862", - "Ampullary Carcinoma | ACH-002023" - ], - "type": "scattergl", - "x": { - "bdata": "4szywHC08sArakG/uNjiPw==", - "dtype": "f4" - }, - "y": { - "bdata": "Ceuqv1E3q7+AyuM+Zu6Dvw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000187", - "ACH-000257", - "ACH-000290", - "ACH-000292", - "ACH-000355", - "ACH-000431", - "ACH-000514", - "ACH-000515", - "ACH-000525", - "ACH-000559", - "ACH-000639", - "ACH-000695", - "ACH-000698", - "ACH-000749", - "ACH-000767", - "ACH-000775", - "ACH-000790", - "ACH-000800", - "ACH-000866", - "ACH-000871", - "ACH-000890", - "ACH-000912", - "ACH-001386", - "ACH-001549", - "ACH-002051", - "ACH-002052", - "ACH-002077" - ], - "hoverinfo": "text", - "marker": { - "color": "#2E91E5", - "size": 7 - }, - "mode": "markers", - "name": "Lung Neuroendocrine Tumor", - "text": [ - "Lung Neuroendocrine Tumor | ACH-000187", - "Lung Neuroendocrine Tumor | ACH-000257", - "Lung Neuroendocrine Tumor | ACH-000290", - "Lung Neuroendocrine Tumor | ACH-000292", - "Lung Neuroendocrine Tumor | ACH-000355", - "Lung Neuroendocrine Tumor | ACH-000431", - "Lung Neuroendocrine Tumor | ACH-000514", - "Lung Neuroendocrine Tumor | ACH-000515", - "Lung Neuroendocrine Tumor | ACH-000525", - "Lung Neuroendocrine Tumor | ACH-000559", - "Lung Neuroendocrine Tumor | ACH-000639", - "Lung Neuroendocrine Tumor | ACH-000695", - "Lung Neuroendocrine Tumor | ACH-000698", - "Lung Neuroendocrine Tumor | ACH-000749", - "Lung Neuroendocrine Tumor | ACH-000767", - "Lung Neuroendocrine Tumor | ACH-000775", - "Lung Neuroendocrine Tumor | ACH-000790", - "Lung Neuroendocrine Tumor | ACH-000800", - "Lung Neuroendocrine Tumor | ACH-000866", - "Lung Neuroendocrine Tumor | ACH-000871", - "Lung Neuroendocrine Tumor | ACH-000890", - "Lung Neuroendocrine Tumor | ACH-000912", - "Lung Neuroendocrine Tumor | ACH-001386", - "Lung Neuroendocrine Tumor | ACH-001549", - "Lung Neuroendocrine Tumor | ACH-002051", - "Lung Neuroendocrine Tumor | ACH-002052", - "Lung Neuroendocrine Tumor | ACH-002077" - ], - "type": "scattergl", - "x": { - "bdata": "uHgBQAA+jr25G9s/tuWaQBpOk0BCgcM+JtRXv3mmDECGrrc/IOyMvxmujEDMhaO/eYg2QEhLLEDDtoS/S00RQOwqP0D1SdI/T2iUQGJriUCh/FK/rjcYQMKIzj6R3zE/vd0ewNk42L50XLe/", - "dtype": "f4" - }, - "y": { - "bdata": "2GMzwLV+lr8WegjA9hkIP+jXQb9Q0ia/0HCvvx2Utr8ybai/ljV2v/K0Q8CgKEm/OjIswHEVb77S1dm/n1qwvnGvzb+q0pc/qrHdvw+Bo7/PY0JASD81PwcNr7/nd6S/lxyhv3Xs0L/LuB2/", - "dtype": "f4" - } - }, - { - "customdata": [ - 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"Endometrial Carcinoma | ACH-000941", - "Endometrial Carcinoma | ACH-000946", - "Endometrial Carcinoma | ACH-000961", - "Endometrial Carcinoma | ACH-000965", - "Endometrial Carcinoma | ACH-000972", - "Endometrial Carcinoma | ACH-000974", - "Endometrial Carcinoma | ACH-000978", - "Endometrial Carcinoma | ACH-000984", - "Endometrial Carcinoma | ACH-000988", - "Endometrial Carcinoma | ACH-000993", - "Endometrial Carcinoma | ACH-000994", - "Endometrial Carcinoma | ACH-000996", - "Endometrial Carcinoma | ACH-001495", - "Endometrial Carcinoma | ACH-001517", - "Endometrial Carcinoma | ACH-001518", - "Endometrial Carcinoma | ACH-002026", - "Endometrial Carcinoma | ACH-002027", - "Endometrial Carcinoma | ACH-002046" - ], - "type": "scattergl", - "x": { - "bdata": "ZTcuwCzRLsDBcVu8TuEAv6aAtT6YD3W/drbywG21EEDZ3V5AYZFaQApj+L+P3RtA+REyQJp7sUCL2PLA+pRWQPJwzT7YVuW/uXrFve9fMT6uyPLAnf2dviX/wr8mBHHAIuHywKrySUDSLbQ/gCDwvg==", - "dtype": "f4" - }, - "y": { - "bdata": 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Carcinoma | ACH-000493", - "Hepatocellular Carcinoma | ACH-000537", - "Hepatocellular Carcinoma | ACH-000577", - "Hepatocellular Carcinoma | ACH-000620", - "Hepatocellular Carcinoma | ACH-000734", - "Hepatocellular Carcinoma | ACH-000848", - "Hepatocellular Carcinoma | ACH-001318", - "Hepatocellular Carcinoma | ACH-002523" - ], - "type": "scattergl", - "x": { - "bdata": "C8IYQLSbnEDLQwM/r8ouP+Q1TcCdpbq/DVD+P7pqHj4X2yxANUxjv0J6rb/+zlVAXTfFv25pzD3xjsU/7iBvwPY/4T8dmIlAexSEQA6oE0Bx5sM/", - "dtype": "f4" - }, - "y": { - "bdata": "+cqaPv8JDr9wwItAC26nP0F4U0AfMS9AdtCGQP6lSEDZxE0+olJoP7t6OkAF5ck/AaBSQDY4N0D/ygJAuZ4eQCMOyzviuRK/DDxpv71zDD/7PpdA", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000305", - "ACH-000318", - "ACH-000408", - "ACH-000452", - "ACH-000488", - "ACH-000544", - "ACH-000561", - "ACH-000605", - "ACH-000637", - "ACH-000647", - "ACH-000693", - "ACH-000694", - "ACH-000717", - "ACH-000777", - "ACH-000784", - "ACH-000809", - "ACH-000823", - "ACH-000824", - "ACH-000855", - 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Carcinoma", - "text": [ - "Bladder Urothelial Carcinoma | ACH-000011", - "Bladder Urothelial Carcinoma | ACH-000018", - "Bladder Urothelial Carcinoma | ACH-000026", - "Bladder Urothelial Carcinoma | ACH-000127", - "Bladder Urothelial Carcinoma | ACH-000142", - "Bladder Urothelial Carcinoma | ACH-000242", - "Bladder Urothelial Carcinoma | ACH-000396", - "Bladder Urothelial Carcinoma | ACH-000473", - "Bladder Urothelial Carcinoma | ACH-000486", - "Bladder Urothelial Carcinoma | ACH-000522", - "Bladder Urothelial Carcinoma | ACH-000545", - "Bladder Urothelial Carcinoma | ACH-000547", - "Bladder Urothelial Carcinoma | ACH-000593", - "Bladder Urothelial Carcinoma | ACH-000720", - "Bladder Urothelial Carcinoma | ACH-000724", - "Bladder Urothelial Carcinoma | ACH-000741", - "Bladder Urothelial Carcinoma | ACH-000753", - "Bladder Urothelial Carcinoma | ACH-000802", - "Bladder Urothelial Carcinoma | ACH-000834", - "Bladder Urothelial Carcinoma | ACH-000862", - "Bladder Urothelial Carcinoma | ACH-000896", - "Bladder Urothelial Carcinoma | ACH-000905", - "Bladder Urothelial Carcinoma | ACH-001183", - "Bladder Urothelial Carcinoma | ACH-001407", - "Bladder Urothelial Carcinoma | ACH-001409", - "Bladder Urothelial Carcinoma | ACH-001412", - "Bladder Urothelial Carcinoma | ACH-001413", - "Bladder Urothelial Carcinoma | ACH-001414", - "Bladder Urothelial Carcinoma | ACH-001415", - "Bladder Urothelial Carcinoma | ACH-001416" - ], - "type": "scattergl", - "x": { - "bdata": "a2SrPrsmbT434gA/Qaa4P1Xo/D4Llu8+CH/EvjAUNcCJSoQ/qZ0xwDF4NMARPDg/xVvqPuCvGz8/dia/19TnPp5AqT+pI4E/LESYP1jkNsB/cws/wgE8P8iyMsDVYDDAB1Y4wDj+OMB5/TTAWjQxwFA5PMCxYjjA", - "dtype": "f4" - }, - "y": { - "bdata": "b7urPpHvAT/Xy4k+JvUqv/EiTj4zFbQ+qLeXPzyRQL9XeIi+DA1jv4KJS79VsTk+JwS+PkJSXj7bj60/AvspPqV3Br+9eyS+icPhvtheKL/TSyw+/WKyO/p0Yb+cn4O/4Tkcv+jiCb/SOUG/1sd5v+zryr53hxu/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000012", - "ACH-000015", - "ACH-000021", - "ACH-000029", - "ACH-000030", - "ACH-000035", - "ACH-000143", - "ACH-000161", - "ACH-000176", - "ACH-000251", - "ACH-000261", - "ACH-000264", - "ACH-000311", - "ACH-000337", - "ACH-000339", - "ACH-000343", - "ACH-000378", - "ACH-000390", - "ACH-000395", - "ACH-000414", - "ACH-000416", - "ACH-000434", - "ACH-000438", - "ACH-000442", - "ACH-000444", - "ACH-000448", - "ACH-000454", - "ACH-000463", - "ACH-000481", - "ACH-000496", - "ACH-000510", - "ACH-000511", - "ACH-000521", - "ACH-000528", - "ACH-000562", - "ACH-000563", - "ACH-000585", - "ACH-000587", - "ACH-000589", - "ACH-000596", - "ACH-000627", - "ACH-000638", - "ACH-000662", - "ACH-000665", - "ACH-000666", - "ACH-000667", - "ACH-000672", - "ACH-000677", - "ACH-000681", - "ACH-000700", - "ACH-000706", - "ACH-000718", - "ACH-000747", - "ACH-000757", - "ACH-000766", - "ACH-000769", - "ACH-000774", - "ACH-000781", - "ACH-000785", - "ACH-000787", - "ACH-000791", - "ACH-000826", - "ACH-000837", - "ACH-000840", - "ACH-000841", - "ACH-000843", - "ACH-000845", - "ACH-000851", - "ACH-000853", - "ACH-000858", - "ACH-000860", - "ACH-000861", - "ACH-000867", - "ACH-000869", - "ACH-000872", - "ACH-000878", - "ACH-000886", - "ACH-000888", - "ACH-000894", - "ACH-000900", - "ACH-000901", - "ACH-000916", - "ACH-000921", - "ACH-000924", - "ACH-000929", - "ACH-000945", - "ACH-000975", - "ACH-000980", - "ACH-001075", - "ACH-001137", - "ACH-001233", - "ACH-002035", - "ACH-002156", - "ACH-002522", - "ACH-002526", - "ACH-002531", - "ACH-002650", - "ACH-003012" - ], - "hoverinfo": "text", - "marker": { - "color": "#FFA15A", - "size": 7 - }, - "mode": "markers", - "name": "Non-Small Cell Lung Cancer", - "text": [ - "Non-Small Cell Lung Cancer | ACH-000012", - "Non-Small Cell Lung Cancer | ACH-000015", - "Non-Small Cell Lung Cancer | ACH-000021", - "Non-Small Cell Lung Cancer | ACH-000029", - "Non-Small Cell Lung Cancer | ACH-000030", - "Non-Small Cell Lung Cancer | ACH-000035", - "Non-Small Cell Lung Cancer | ACH-000143", - "Non-Small Cell Lung Cancer | ACH-000161", - "Non-Small Cell Lung Cancer | ACH-000176", - "Non-Small Cell Lung Cancer | ACH-000251", - "Non-Small Cell Lung Cancer | ACH-000261", - "Non-Small Cell Lung Cancer | ACH-000264", - "Non-Small Cell Lung Cancer | ACH-000311", - "Non-Small Cell Lung Cancer | ACH-000337", - "Non-Small Cell Lung Cancer | ACH-000339", - "Non-Small Cell Lung Cancer | ACH-000343", - "Non-Small Cell Lung Cancer | ACH-000378", - "Non-Small Cell Lung Cancer | ACH-000390", - "Non-Small Cell Lung Cancer | ACH-000395", - "Non-Small Cell Lung Cancer | ACH-000414", - "Non-Small Cell Lung Cancer | ACH-000416", - "Non-Small Cell Lung Cancer | ACH-000434", - "Non-Small Cell Lung Cancer | ACH-000438", - "Non-Small Cell Lung Cancer | ACH-000442", - "Non-Small Cell Lung Cancer | ACH-000444", - "Non-Small Cell Lung Cancer | ACH-000448", - "Non-Small Cell Lung Cancer | ACH-000454", - "Non-Small Cell Lung Cancer | ACH-000463", - "Non-Small Cell Lung Cancer | ACH-000481", - "Non-Small Cell Lung Cancer | ACH-000496", - "Non-Small Cell Lung Cancer | ACH-000510", - "Non-Small Cell Lung Cancer | ACH-000511", - "Non-Small Cell Lung Cancer | ACH-000521", - "Non-Small Cell Lung Cancer | ACH-000528", - "Non-Small Cell Lung Cancer | ACH-000562", - "Non-Small Cell Lung Cancer | ACH-000563", - "Non-Small Cell Lung Cancer | ACH-000585", - "Non-Small Cell Lung Cancer | ACH-000587", - "Non-Small Cell Lung Cancer | ACH-000589", - "Non-Small Cell Lung Cancer | ACH-000596", - "Non-Small Cell Lung Cancer | ACH-000627", - "Non-Small Cell Lung Cancer | ACH-000638", - "Non-Small Cell Lung Cancer | ACH-000662", - "Non-Small Cell Lung Cancer | ACH-000665", - "Non-Small Cell Lung Cancer | ACH-000666", - "Non-Small Cell Lung Cancer | ACH-000667", - "Non-Small Cell Lung Cancer | ACH-000672", - "Non-Small Cell Lung Cancer | ACH-000677", - "Non-Small Cell Lung Cancer | ACH-000681", - "Non-Small Cell Lung Cancer | ACH-000700", - "Non-Small Cell Lung Cancer | ACH-000706", - "Non-Small Cell Lung Cancer | ACH-000718", - "Non-Small Cell Lung Cancer | ACH-000747", - "Non-Small Cell Lung Cancer | ACH-000757", - "Non-Small Cell Lung Cancer | ACH-000766", - "Non-Small Cell Lung Cancer | ACH-000769", - "Non-Small Cell Lung Cancer | ACH-000774", - "Non-Small Cell Lung Cancer | ACH-000781", - "Non-Small Cell Lung Cancer | ACH-000785", - "Non-Small Cell Lung Cancer | ACH-000787", - "Non-Small Cell Lung Cancer | ACH-000791", - "Non-Small Cell Lung Cancer | ACH-000826", - "Non-Small Cell Lung Cancer | ACH-000837", - "Non-Small Cell Lung Cancer | ACH-000840", - "Non-Small Cell Lung Cancer | ACH-000841", - "Non-Small Cell Lung Cancer | ACH-000843", - "Non-Small Cell Lung Cancer | ACH-000845", - "Non-Small Cell Lung Cancer | ACH-000851", - "Non-Small Cell Lung Cancer | ACH-000853", - "Non-Small Cell Lung Cancer | ACH-000858", - "Non-Small Cell Lung Cancer | ACH-000860", - "Non-Small Cell Lung Cancer | ACH-000861", - "Non-Small Cell Lung Cancer | ACH-000867", - "Non-Small Cell Lung Cancer | ACH-000869", - "Non-Small Cell Lung Cancer | ACH-000872", - "Non-Small Cell Lung Cancer | ACH-000878", - "Non-Small Cell Lung Cancer | ACH-000886", - "Non-Small Cell Lung Cancer | ACH-000888", - "Non-Small Cell Lung Cancer | ACH-000894", - "Non-Small Cell Lung Cancer | ACH-000900", - "Non-Small Cell Lung Cancer | ACH-000901", - "Non-Small Cell Lung Cancer | ACH-000916", - "Non-Small Cell Lung Cancer | ACH-000921", - "Non-Small Cell Lung Cancer | ACH-000924", - "Non-Small Cell Lung Cancer | ACH-000929", - "Non-Small Cell Lung Cancer | ACH-000945", - "Non-Small Cell Lung Cancer | ACH-000975", - "Non-Small Cell Lung Cancer | ACH-000980", - "Non-Small Cell Lung Cancer | ACH-001075", - "Non-Small Cell Lung Cancer | ACH-001137", - "Non-Small Cell Lung Cancer | ACH-001233", - "Non-Small Cell Lung Cancer | ACH-002035", - "Non-Small Cell Lung Cancer | ACH-002156", - "Non-Small Cell Lung Cancer | ACH-002522", - "Non-Small Cell Lung Cancer | ACH-002526", - "Non-Small Cell Lung Cancer | ACH-002531", - "Non-Small Cell Lung Cancer | ACH-002650", - "Non-Small Cell Lung Cancer | ACH-003012" - ], - "type": "scattergl", - "x": { - "bdata": "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", - "dtype": "f4" - }, - "y": { - "bdata": 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"ACH-000827", - "ACH-000881", - "ACH-000882", - "ACH-000884", - "ACH-000899", - "ACH-000915", - "ACH-000968", - "ACH-001041", - "ACH-001190", - "ACH-001239", - "ACH-001522", - "ACH-001563", - "ACH-001566", - "ACH-001567", - "ACH-001568", - "ACH-001570", - "ACH-001645", - "ACH-001970", - "ACH-001972", - "ACH-001973", - "ACH-001975", - "ACH-001982", - "ACH-001986", - "ACH-001990", - "ACH-002001", - "ACH-002002", - "ACH-002003", - "ACH-002004", - "ACH-002005", - "ACH-002084", - "ACH-002143", - "ACH-002458", - "ACH-002460", - "ACH-002461", - "ACH-002508", - "ACH-002510", - "ACH-002511", - "ACH-002512", - "ACH-002847", - "ACH-002928" - ], - "hoverinfo": "text", - "marker": { - "color": "#19D3F3", - "size": 7 - }, - "mode": "markers", - "name": "Melanoma", - "text": [ - "Melanoma | ACH-000014", - "Melanoma | ACH-000219", - "Melanoma | ACH-000274", - "Melanoma | ACH-000304", - "Melanoma | ACH-000322", - "Melanoma | ACH-000348", - "Melanoma | ACH-000401", - "Melanoma | ACH-000404", - "Melanoma | ACH-000425", - "Melanoma | ACH-000441", - "Melanoma | ACH-000450", - "Melanoma | ACH-000458", - "Melanoma | ACH-000477", - "Melanoma | ACH-000550", - "Melanoma | ACH-000579", - "Melanoma | ACH-000580", - "Melanoma | ACH-000614", - "Melanoma | ACH-000632", - "Melanoma | ACH-000661", - "Melanoma | ACH-000765", - "Melanoma | ACH-000788", - "Melanoma | ACH-000799", - "Melanoma | ACH-000801", - "Melanoma | ACH-000805", - "Melanoma | ACH-000810", - "Melanoma | ACH-000822", - "Melanoma | ACH-000827", - "Melanoma | ACH-000881", - "Melanoma | ACH-000882", - "Melanoma | ACH-000884", - "Melanoma | ACH-000899", - "Melanoma | ACH-000915", - "Melanoma | ACH-000968", - "Melanoma | ACH-001041", - "Melanoma | ACH-001190", - "Melanoma | ACH-001239", - "Melanoma | ACH-001522", - "Melanoma | ACH-001563", - "Melanoma | ACH-001566", - "Melanoma | ACH-001567", - "Melanoma | ACH-001568", - "Melanoma | ACH-001570", - "Melanoma | ACH-001645", - "Melanoma | ACH-001970", - "Melanoma | ACH-001972", - "Melanoma | ACH-001973", - "Melanoma | ACH-001975", - "Melanoma | ACH-001982", - "Melanoma | ACH-001986", - "Melanoma | ACH-001990", - "Melanoma | ACH-002001", - "Melanoma | ACH-002002", - "Melanoma | ACH-002003", - "Melanoma | ACH-002004", - "Melanoma | ACH-002005", - "Melanoma | ACH-002084", - "Melanoma | ACH-002143", - "Melanoma | ACH-002458", - "Melanoma | ACH-002460", - "Melanoma | ACH-002461", - "Melanoma | ACH-002508", - "Melanoma | ACH-002510", - "Melanoma | ACH-002511", - "Melanoma | ACH-002512", - "Melanoma | ACH-002847", - "Melanoma | ACH-002928" - ], - "type": "scattergl", - "x": { - "bdata": "wIZwPwrOCUCZ4C6/IkRkPknklz+lRba+GRFjP70HM8ChWDTAD8S2P2WHMMApJDPAxRvdPQ4HLb9umDbA2HjgPZLpnj/KWE4/6rMwwLF6CD+hPgQ/agByPeDZMsD2ExU/fql2PrH1S7/AbQM/yHCfP0Djyj9SMo8/rjkwwM/cuz+22KE/q09PP06whb53SaA/iiwFP/XxM8BTXTPAdxw0wJYwNsCtMTDAkv8aPtl4PD9OxCrAOuMxwOYoLsBDp5M/ZNOyP0OEzT81d7s/pPQHQJBsQj9ekjTAj4qTP1Bahr2KFoO/GqlfP/GyWj+PEDQ9yrKcvs6dnD/lyne/WH4OPhGo5zvh/D+/", - "dtype": "f4" - }, - "y": { - "bdata": 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"ACH-001393", - "ACH-001394", - "ACH-001396", - "ACH-001419", - "ACH-001662", - "ACH-001683", - "ACH-001819", - "ACH-002179", - "ACH-002399", - "ACH-002401" - ], - "hoverinfo": "text", - "marker": { - "color": "#FF6692", - "size": 7 - }, - "mode": "markers", - "name": "Invasive Breast Carcinoma", - "text": [ - "Invasive Breast Carcinoma | ACH-000017", - "Invasive Breast Carcinoma | ACH-000019", - "Invasive Breast Carcinoma | ACH-000028", - "Invasive Breast Carcinoma | ACH-000097", - "Invasive Breast Carcinoma | ACH-000111", - "Invasive Breast Carcinoma | ACH-000147", - "Invasive Breast Carcinoma | ACH-000148", - "Invasive Breast Carcinoma | ACH-000212", - "Invasive Breast Carcinoma | ACH-000223", - "Invasive Breast Carcinoma | ACH-000248", - "Invasive Breast Carcinoma | ACH-000258", - "Invasive Breast Carcinoma | ACH-000276", - "Invasive Breast Carcinoma | ACH-000277", - "Invasive Breast Carcinoma | ACH-000288", - "Invasive Breast Carcinoma | ACH-000330", - "Invasive Breast Carcinoma | ACH-000352", - "Invasive Breast Carcinoma | ACH-000374", - "Invasive Breast Carcinoma | ACH-000554", - "Invasive Breast Carcinoma | ACH-000573", - "Invasive Breast Carcinoma | ACH-000621", - "Invasive Breast Carcinoma | ACH-000668", - "Invasive Breast Carcinoma | ACH-000699", - "Invasive Breast Carcinoma | ACH-000711", - "Invasive Breast Carcinoma | ACH-000721", - "Invasive Breast Carcinoma | ACH-000768", - "Invasive Breast Carcinoma | ACH-000783", - "Invasive Breast Carcinoma | ACH-000849", - "Invasive Breast Carcinoma | ACH-000856", - "Invasive Breast Carcinoma | ACH-000876", - "Invasive Breast Carcinoma | ACH-000910", - "Invasive Breast Carcinoma | ACH-000934", - "Invasive Breast Carcinoma | ACH-001065", - "Invasive Breast Carcinoma | ACH-001388", - "Invasive Breast Carcinoma | ACH-001389", - "Invasive Breast Carcinoma | ACH-001390", - "Invasive Breast Carcinoma | ACH-001391", - "Invasive Breast Carcinoma | ACH-001392", - "Invasive Breast Carcinoma | ACH-001393", - "Invasive Breast Carcinoma | ACH-001394", - "Invasive Breast Carcinoma | ACH-001396", - "Invasive Breast Carcinoma | ACH-001419", - "Invasive Breast Carcinoma | ACH-001662", - "Invasive Breast Carcinoma | ACH-001683", - "Invasive Breast Carcinoma | ACH-001819", - "Invasive Breast Carcinoma | ACH-002179", - "Invasive Breast Carcinoma | ACH-002399", - "Invasive Breast Carcinoma | ACH-002401" - ], - "type": "scattergl", - "x": { - "bdata": "ty4IPkG2SD8wkr8/Ryr7PkxfkD9HrpU/IPKMPqLb2T4Fr8O+ytY0P0QcMb7ZmfC9A2nIPaU9CT9dRwM/j3f1Pn+ZQD+I5xW/Au0TP5Rfg7+4vfa98V0Rv7zDQD+lpYw/NtbjPg4COb+uRZk/opENQJd7OL6hX68/WUptv2iQ5D/GtQ2/EwUxwISDFz/XVEq/CU45wIwoM8CkKDjAlWA6wIppcj4a2PO8CDtuPg4osr78rY8/dS78PqoWUj8=", - "dtype": "f4" - }, - "y": { - "bdata": "Pn1sPuZ3PLzIXkW/BV3lPYBms76TddK+pDbtPq6BCD7e5zU/fnWpvY1JPT/QlUY/rZikPsJqtj7nbsy8ZuQNO2XTj70nfpI/EuTkOwR9vj8NS1I/TsFmP8s+qr4YUuS+RFMePkBkij/VOJu+WTSav+K/Uz+AuBu/Ny/YP9ZqV79KupE/Up58v/OMmD6NHKg/2BIHv5xSYr+PRCG/j23ZvhyXpT4rOfE+mKyxPsvJJD+q0uS+/zWcPseZIL4=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000022", - "ACH-000023", - "ACH-000042", - "ACH-000060", - "ACH-000085", - "ACH-000093", - "ACH-000094", - "ACH-000114", - "ACH-000118", - "ACH-000138", - "ACH-000139", - "ACH-000155", - "ACH-000164", - "ACH-000178", - "ACH-000213", - "ACH-000222", - "ACH-000235", - "ACH-000243", - "ACH-000265", - "ACH-000266", - "ACH-000281", - "ACH-000307", - "ACH-000320", - "ACH-000332", - "ACH-000354", - "ACH-000417", - "ACH-000468", - "ACH-000502", - "ACH-000517", - "ACH-000535", - "ACH-000599", - "ACH-000601", - "ACH-000652", - "ACH-001098", - "ACH-001107", - "ACH-001353", - "ACH-001375", - "ACH-001377", - "ACH-001379", - "ACH-001380", - "ACH-001382", - "ACH-001999", - "ACH-002039", - "ACH-002186", - "ACH-002672" - ], - "hoverinfo": "text", - "marker": { - "color": "#B6E880", - "size": 7 - }, - "mode": "markers", - "name": "Pancreatic Adenocarcinoma", - "text": [ - "Pancreatic Adenocarcinoma | ACH-000022", - "Pancreatic Adenocarcinoma | ACH-000023", - "Pancreatic Adenocarcinoma | ACH-000042", - "Pancreatic Adenocarcinoma | ACH-000060", - "Pancreatic Adenocarcinoma | ACH-000085", - "Pancreatic Adenocarcinoma | ACH-000093", - "Pancreatic Adenocarcinoma | ACH-000094", - "Pancreatic Adenocarcinoma | ACH-000114", - "Pancreatic Adenocarcinoma | ACH-000118", - "Pancreatic Adenocarcinoma | ACH-000138", - "Pancreatic Adenocarcinoma | ACH-000139", - "Pancreatic Adenocarcinoma | ACH-000155", - "Pancreatic Adenocarcinoma | ACH-000164", - "Pancreatic Adenocarcinoma | ACH-000178", - "Pancreatic Adenocarcinoma | ACH-000213", - "Pancreatic Adenocarcinoma | ACH-000222", - "Pancreatic Adenocarcinoma | ACH-000235", - "Pancreatic Adenocarcinoma | ACH-000243", - "Pancreatic Adenocarcinoma | ACH-000265", - "Pancreatic Adenocarcinoma | ACH-000266", - "Pancreatic Adenocarcinoma | ACH-000281", - "Pancreatic Adenocarcinoma | ACH-000307", - "Pancreatic Adenocarcinoma | ACH-000320", - "Pancreatic Adenocarcinoma | ACH-000332", - "Pancreatic Adenocarcinoma | ACH-000354", - "Pancreatic Adenocarcinoma | ACH-000417", - "Pancreatic Adenocarcinoma | ACH-000468", - "Pancreatic Adenocarcinoma | ACH-000502", - "Pancreatic Adenocarcinoma | ACH-000517", - "Pancreatic Adenocarcinoma | ACH-000535", - "Pancreatic Adenocarcinoma | ACH-000599", - "Pancreatic Adenocarcinoma | ACH-000601", - "Pancreatic Adenocarcinoma | ACH-000652", - "Pancreatic Adenocarcinoma | ACH-001098", - "Pancreatic Adenocarcinoma | ACH-001107", - "Pancreatic Adenocarcinoma | ACH-001353", - "Pancreatic Adenocarcinoma | ACH-001375", - "Pancreatic Adenocarcinoma | ACH-001377", - "Pancreatic Adenocarcinoma | ACH-001379", - "Pancreatic Adenocarcinoma | ACH-001380", - "Pancreatic Adenocarcinoma | ACH-001382", - "Pancreatic Adenocarcinoma | ACH-001999", - "Pancreatic Adenocarcinoma | ACH-002039", - "Pancreatic Adenocarcinoma | ACH-002186", - "Pancreatic Adenocarcinoma | ACH-002672" - ], - "type": "scattergl", - "x": { - "bdata": "DUkOP/NXtT9uYiG/+prRvi57sbvfgOi9MMY7vq/0/b6coFQ/FlUbP1mzAr2f7/G9CLIBP8QLPz8f90k/FA12v7kbZT7QeQs/e/3uPyscZr+ufDC+1XEywJEgPj/8uUg+AExQPhjlb76xfTvA/eu+PnzgCr8wipY+9ElzPsoXyD+n+Jg+UXAoP2rX5b1BNnu+g5VDvmjwYz+YTBg/kXSJPx++qr4TyDLAy9U1wGbjNsAtR6g+", - "dtype": "f4" - }, - "y": { - "bdata": "WNYxPstiOb6LCYs/j7x5P5szJz83ikI/goEKP0yLfD8vU8C+MDlTPQpQET8krww/Z7FvPvPvar5AE5o95vpfP78p6j2ssAE8qTg+vzZ9pj/36lU/Ok1pv6CU7jxanL8+akyFPqSRHj+z6uC+kos2Pnwzjz9/Zs8+RQnrPkeOV7/fX8g+ktCivTdwOz/NMUs/hRkxP7onLb6SeSc94v/MvhbdmT9Gc2y/1Po7vyExH7+1WfU9", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000024", - "ACH-000106", - "ACH-000124", - "ACH-000167", - "ACH-000183", - "ACH-000204", - "ACH-000271", - "ACH-000315", - "ACH-000334", - "ACH-000346", - "ACH-000363", - "ACH-000365", - "ACH-000371", - "ACH-000398", - "ACH-000402", - "ACH-000405", - "ACH-000426", - "ACH-000436", - "ACH-000512", - "ACH-000541", - "ACH-000567", - "ACH-000576", - "ACH-000588", - "ACH-000653", - "ACH-000654", - "ACH-000656", - "ACH-000660", - "ACH-000697", - "ACH-000714", - "ACH-000763", - "ACH-000817", - "ACH-000821", - "ACH-000829", - "ACH-000838", - "ACH-000889", - "ACH-000914", - "ACH-000944", - "ACH-001450", - "ACH-001498", - "ACH-001533", - "ACH-001539", - "ACH-001616", - "ACH-001634", - "ACH-001639", - "ACH-001677", - "ACH-001707", - "ACH-001709", - "ACH-002055", - "ACH-002062", - "ACH-002214", - "ACH-002215", - "ACH-002478", - "ACH-002485", - "ACH-002500", - "ACH-002677", - "ACH-002678" - ], - "hoverinfo": "text", - "marker": { - "color": "#FF97FF", - "size": 7 - }, - "mode": "markers", - "name": "Mature B-Cell Neoplasms", - "text": [ - "Mature B-Cell Neoplasms | ACH-000024", - "Mature B-Cell Neoplasms | ACH-000106", - "Mature B-Cell Neoplasms | ACH-000124", - "Mature B-Cell Neoplasms | ACH-000167", - "Mature B-Cell Neoplasms | ACH-000183", - "Mature B-Cell Neoplasms | ACH-000204", - "Mature B-Cell Neoplasms | ACH-000271", - "Mature B-Cell Neoplasms | ACH-000315", - "Mature B-Cell Neoplasms | ACH-000334", - "Mature B-Cell Neoplasms | ACH-000346", - "Mature B-Cell Neoplasms | ACH-000363", - "Mature B-Cell Neoplasms | ACH-000365", - "Mature B-Cell Neoplasms | ACH-000371", - "Mature B-Cell Neoplasms | ACH-000398", - "Mature B-Cell Neoplasms | ACH-000402", - "Mature B-Cell Neoplasms | ACH-000405", - "Mature B-Cell Neoplasms | ACH-000426", - "Mature B-Cell Neoplasms | ACH-000436", - "Mature B-Cell Neoplasms | ACH-000512", - "Mature B-Cell Neoplasms | ACH-000541", - "Mature B-Cell Neoplasms | ACH-000567", - "Mature B-Cell Neoplasms | ACH-000576", - "Mature B-Cell Neoplasms | ACH-000588", - "Mature B-Cell Neoplasms | ACH-000653", - "Mature B-Cell Neoplasms | ACH-000654", - "Mature B-Cell Neoplasms | ACH-000656", - "Mature B-Cell Neoplasms | ACH-000660", - "Mature B-Cell Neoplasms | ACH-000697", - "Mature B-Cell Neoplasms | ACH-000714", - "Mature B-Cell Neoplasms | ACH-000763", - "Mature B-Cell Neoplasms | ACH-000817", - "Mature B-Cell Neoplasms | ACH-000821", - "Mature B-Cell Neoplasms | ACH-000829", - "Mature B-Cell Neoplasms | ACH-000838", - "Mature B-Cell Neoplasms | ACH-000889", - "Mature B-Cell Neoplasms | ACH-000914", - "Mature B-Cell Neoplasms | ACH-000944", - "Mature B-Cell Neoplasms | ACH-001450", - "Mature B-Cell Neoplasms | ACH-001498", - "Mature B-Cell Neoplasms | ACH-001533", - "Mature B-Cell Neoplasms | ACH-001539", - "Mature B-Cell Neoplasms | ACH-001616", - "Mature B-Cell Neoplasms | ACH-001634", - "Mature B-Cell Neoplasms | ACH-001639", - "Mature B-Cell Neoplasms | ACH-001677", - "Mature B-Cell Neoplasms | ACH-001707", - "Mature B-Cell Neoplasms | ACH-001709", - "Mature B-Cell Neoplasms | ACH-002055", - "Mature B-Cell Neoplasms | ACH-002062", - "Mature B-Cell Neoplasms | ACH-002214", - "Mature B-Cell Neoplasms | ACH-002215", - "Mature B-Cell Neoplasms | ACH-002478", - "Mature B-Cell Neoplasms | ACH-002485", - "Mature B-Cell Neoplasms | ACH-002500", - "Mature B-Cell Neoplasms | ACH-002677", - "Mature B-Cell Neoplasms | ACH-002678" - ], - "type": "scattergl", - "x": { - "bdata": "NsiSPwC+Pz8hXiFABlJxP3Eq7T/SW9w/wAEzQDOXaT8lb8+9VWLKP+b6mD4RNvc/jpa5P+24oT8SvVk/qZLSPxK1kj5r8TPAToyeP3xcVj+ROC7AL+zwPrdI3z/84ow/YJ+QP87RJ0BuqyBAn+e0P16xhj9EaDE/8datP0xhTz/h4S/ApqBKPz5uAUBjWQtA2ZPRP09ozj+RT9w/3ZYwwGjeLj88OAlAn04zwNlVij9apT8/KyAzwKiWGEDihJo/73FbP1dxBkDYKbM/TdyaPxqUiT+tY/w/kr4BQMyihT8=", - "dtype": "f4" - }, - "y": { - "bdata": "nU04v2ntF7x+Wb6/1RnFvqnEvL8mYpG/ojLzv8Sm4r6b9gU/fwQyv2iwj70GBra/J1RXv9XTD79vsFq+L5iLvy7FAb6XtVi/nFQev/6UXL66OI2/rKsivv3Nnr+ZayO/yzoRv4pO0L9PWMC/DLdev6XoJb9aGq2+dYxSv1ido74nqYq/hW7qvv5avb+cScK/JX5xv/xuWb+IfYi/Jid/vyQiOr7xoNm/D7ZUvyfjOr7MuxO+DY1jv2qC3r+FuCK/vQJjvmPjp7/JZ1e/n8k3v0jHBb9J+ai/FxLDv+Sg8r4=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000025", - "ACH-001067", - "ACH-002070" - ], - "hoverinfo": "text", - "marker": { - "color": "#FECB52", - "size": 7 - }, - "mode": "markers", - "name": "Meningothelial Tumor", - "text": [ - "Meningothelial Tumor | ACH-000025", - "Meningothelial Tumor | ACH-001067", - "Meningothelial Tumor | ACH-002070" - ], - "type": "scattergl", - "x": { - "bdata": "BkN0P2IBL8BrNME+", - "dtype": "f4" - }, - "y": { - "bdata": "dSz3vbf5iL9jX7k+", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000036", - "ACH-000040", - "ACH-000067", - "ACH-000075", - "ACH-000098", - "ACH-000128", - "ACH-000137", - "ACH-000152", - "ACH-000200", - "ACH-000208", - "ACH-000215", - "ACH-000231", - "ACH-000232", - "ACH-000244", - "ACH-000269", - "ACH-000273", - "ACH-000323", - "ACH-000329", - "ACH-000368", - "ACH-000370", - "ACH-000376", - "ACH-000389", - "ACH-000437", - "ACH-000445", - "ACH-000455", - "ACH-000464", - "ACH-000469", - "ACH-000479", - "ACH-000504", - "ACH-000558", - "ACH-000570", - "ACH-000571", - "ACH-000591", - "ACH-000592", - "ACH-000595", - "ACH-000609", - "ACH-000622", - "ACH-000623", - "ACH-000631", - "ACH-000634", - "ACH-000655", - "ACH-000673", - "ACH-000676", - "ACH-000738", - "ACH-000756", - "ACH-000760", - "ACH-000807", - "ACH-000819", - "ACH-000863", - "ACH-000887", - "ACH-001016", - "ACH-001126", - "ACH-001172", - "ACH-001329", - "ACH-001605", - "ACH-001606", - "ACH-001608", - "ACH-001609", - "ACH-001610", - "ACH-001611", - "ACH-001622", - "ACH-001623", - "ACH-001624", - "ACH-002228", - "ACH-002229", - "ACH-002230", - "ACH-002257", - "ACH-002269", - "ACH-002304", - "ACH-002680" - ], - "hoverinfo": "text", - "marker": { - "color": "#FD3216", - "size": 7 - }, - "mode": "markers", - "name": "Diffuse Glioma", - "text": [ - "Diffuse Glioma | ACH-000036", - "Diffuse Glioma | ACH-000040", - "Diffuse Glioma | ACH-000067", - "Diffuse Glioma | ACH-000075", - "Diffuse Glioma | ACH-000098", - "Diffuse Glioma | ACH-000128", - "Diffuse Glioma | ACH-000137", - "Diffuse Glioma | ACH-000152", - "Diffuse Glioma | ACH-000200", - "Diffuse Glioma | ACH-000208", - "Diffuse Glioma | ACH-000215", - "Diffuse Glioma | ACH-000231", - "Diffuse Glioma | ACH-000232", - "Diffuse Glioma | ACH-000244", - "Diffuse Glioma | ACH-000269", - "Diffuse Glioma | ACH-000273", - "Diffuse Glioma | ACH-000323", - "Diffuse Glioma | ACH-000329", - "Diffuse Glioma | ACH-000368", - "Diffuse Glioma | ACH-000370", - "Diffuse Glioma | ACH-000376", - "Diffuse Glioma | ACH-000389", - "Diffuse Glioma | ACH-000437", - "Diffuse Glioma | ACH-000445", - "Diffuse Glioma | ACH-000455", - "Diffuse Glioma | ACH-000464", - "Diffuse Glioma | ACH-000469", - "Diffuse Glioma | ACH-000479", - "Diffuse Glioma | ACH-000504", - "Diffuse Glioma | ACH-000558", - "Diffuse Glioma | ACH-000570", - "Diffuse Glioma | ACH-000571", - "Diffuse Glioma | ACH-000591", - "Diffuse Glioma | ACH-000592", - "Diffuse Glioma | ACH-000595", - "Diffuse Glioma | ACH-000609", - "Diffuse Glioma | ACH-000622", - "Diffuse Glioma | ACH-000623", - "Diffuse Glioma | ACH-000631", - "Diffuse Glioma | ACH-000634", - "Diffuse Glioma | ACH-000655", - "Diffuse Glioma | ACH-000673", - "Diffuse Glioma | ACH-000676", - "Diffuse Glioma | ACH-000738", - "Diffuse Glioma | ACH-000756", - "Diffuse Glioma | ACH-000760", - "Diffuse Glioma | ACH-000807", - "Diffuse Glioma | ACH-000819", - "Diffuse Glioma | ACH-000863", - "Diffuse Glioma | ACH-000887", - "Diffuse Glioma | ACH-001016", - "Diffuse Glioma | ACH-001126", - "Diffuse Glioma | ACH-001172", - "Diffuse Glioma | ACH-001329", - "Diffuse Glioma | ACH-001605", - "Diffuse Glioma | ACH-001606", - "Diffuse Glioma | ACH-001608", - "Diffuse Glioma | ACH-001609", - "Diffuse Glioma | ACH-001610", - "Diffuse Glioma | ACH-001611", - "Diffuse Glioma | ACH-001622", - "Diffuse Glioma | ACH-001623", - "Diffuse Glioma | ACH-001624", - "Diffuse Glioma | ACH-002228", - "Diffuse Glioma | ACH-002229", - "Diffuse Glioma | ACH-002230", - "Diffuse Glioma | ACH-002257", - "Diffuse Glioma | ACH-002269", - "Diffuse Glioma | ACH-002304", - "Diffuse Glioma | ACH-002680" - ], - "type": "scattergl", - "x": { - "bdata": 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[ - "Sarcoma, NOS | ACH-000037" - ], - "type": "scattergl", - "x": { - "bdata": "YKEUvw==", - "dtype": "f4" - }, - "y": { - "bdata": "DF+/Pw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000039", - "ACH-000041", - "ACH-000052", - "ACH-000087", - "ACH-000210", - "ACH-000279", - "ACH-000391", - "ACH-000424", - "ACH-000499", - "ACH-001029", - "ACH-001038", - "ACH-001192", - "ACH-001193", - "ACH-001205", - "ACH-001283", - "ACH-001430", - "ACH-001431", - "ACH-002105", - "ACH-002106", - "ACH-002109", - "ACH-002110", - "ACH-002114", - "ACH-002116", - "ACH-002119", - "ACH-002160" - ], - "hoverinfo": "text", - "marker": { - "color": "#6A76FC", - "size": 7 - }, - "mode": "markers", - "name": "Ewing Sarcoma", - "text": [ - "Ewing Sarcoma | ACH-000039", - "Ewing Sarcoma | ACH-000041", - "Ewing Sarcoma | ACH-000052", - "Ewing Sarcoma | ACH-000087", - "Ewing Sarcoma | ACH-000210", - "Ewing Sarcoma | ACH-000279", - "Ewing Sarcoma | ACH-000391", - "Ewing Sarcoma | ACH-000424", - "Ewing Sarcoma | ACH-000499", - "Ewing Sarcoma | ACH-001029", - "Ewing Sarcoma | ACH-001038", - "Ewing Sarcoma | ACH-001192", - "Ewing Sarcoma | ACH-001193", - "Ewing Sarcoma | ACH-001205", - "Ewing Sarcoma | ACH-001283", - "Ewing Sarcoma | ACH-001430", - "Ewing Sarcoma | ACH-001431", - "Ewing Sarcoma | ACH-002105", - "Ewing Sarcoma | ACH-002106", - "Ewing Sarcoma | ACH-002109", - "Ewing Sarcoma | ACH-002110", - "Ewing Sarcoma | ACH-002114", - "Ewing Sarcoma | ACH-002116", - "Ewing Sarcoma | ACH-002119", - "Ewing Sarcoma | ACH-002160" - ], - "type": "scattergl", - "x": { - "bdata": "5HyQve9fPT7rWWM+IvSFP54S8D4hQq4/A7vCPxxv8j+INpA/RBjTPx75kT+FYCY/TIzSPuAKID+2OWw/3FzoPtVdTj/netk+fujFPwDMQD/M+QBARHo1wD8pNcC+ouQ/VZDcPw==", - "dtype": "f4" - }, - "y": { - "bdata": "/ERmPwqqKz8gjiY/q2bgvaov5j4OhwK/nx10vpMNGr8AyXC+O3MgvzoEqb4/uoE+jpa9PmD2KT1J0K29hzjDPnaf5L0K2Dc/ZLUgv94Haj57XF2/cgY+v/J1Pb/Ctii/7+4Svw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000047", - "ACH-000144", - "ACH-000216", - "ACH-000239", - "ACH-000247", - "ACH-000255", - "ACH-000303", - "ACH-000325", - "ACH-000344", - "ACH-000356", - "ACH-000383", - "ACH-000427", - "ACH-000466", - "ACH-000485", - "ACH-000507", - "ACH-000581", - "ACH-000616", - "ACH-000633", - "ACH-000736", - "ACH-000746", - "ACH-000758", - "ACH-000764", - "ACH-000793", - "ACH-000847", - "ACH-000880", - "ACH-000898", - "ACH-000911", - "ACH-000919", - "ACH-000932", - "ACH-000948", - "ACH-001368", - "ACH-001496", - "ACH-001497", - "ACH-001500", - "ACH-001544", - "ACH-001653", - "ACH-001654", - "ACH-001664", - "ACH-002141", - "ACH-002161", - "ACH-002202", - "ACH-002446", - "ACH-002705", - "ACH-002706" - ], - "hoverinfo": "text", - "marker": { - "color": "#FED4C4", - "size": 7 - }, - "mode": "markers", - "name": "Esophagogastric Adenocarcinoma", - "text": [ - "Esophagogastric Adenocarcinoma | ACH-000047", - "Esophagogastric Adenocarcinoma | ACH-000144", - "Esophagogastric Adenocarcinoma | ACH-000216", - "Esophagogastric Adenocarcinoma | ACH-000239", - "Esophagogastric Adenocarcinoma | ACH-000247", - "Esophagogastric Adenocarcinoma | ACH-000255", - "Esophagogastric Adenocarcinoma | ACH-000303", - "Esophagogastric Adenocarcinoma | ACH-000325", - "Esophagogastric Adenocarcinoma | ACH-000344", - "Esophagogastric Adenocarcinoma | ACH-000356", - "Esophagogastric Adenocarcinoma | ACH-000383", - "Esophagogastric Adenocarcinoma | ACH-000427", - "Esophagogastric Adenocarcinoma | ACH-000466", - "Esophagogastric Adenocarcinoma | ACH-000485", - "Esophagogastric Adenocarcinoma | ACH-000507", - "Esophagogastric Adenocarcinoma | ACH-000581", - "Esophagogastric Adenocarcinoma | ACH-000616", - "Esophagogastric Adenocarcinoma | ACH-000633", - "Esophagogastric Adenocarcinoma | ACH-000736", - "Esophagogastric Adenocarcinoma | ACH-000746", - "Esophagogastric Adenocarcinoma | ACH-000758", - "Esophagogastric Adenocarcinoma | ACH-000764", - "Esophagogastric Adenocarcinoma | ACH-000793", - "Esophagogastric Adenocarcinoma | ACH-000847", - "Esophagogastric Adenocarcinoma | ACH-000880", - "Esophagogastric Adenocarcinoma | ACH-000898", - "Esophagogastric Adenocarcinoma | ACH-000911", - "Esophagogastric Adenocarcinoma | ACH-000919", - "Esophagogastric Adenocarcinoma | ACH-000932", - "Esophagogastric Adenocarcinoma | ACH-000948", - "Esophagogastric Adenocarcinoma | ACH-001368", - "Esophagogastric Adenocarcinoma | ACH-001496", - "Esophagogastric Adenocarcinoma | ACH-001497", - "Esophagogastric Adenocarcinoma | ACH-001500", - "Esophagogastric Adenocarcinoma | ACH-001544", - "Esophagogastric Adenocarcinoma | ACH-001653", - "Esophagogastric Adenocarcinoma | ACH-001654", - "Esophagogastric Adenocarcinoma | ACH-001664", - "Esophagogastric Adenocarcinoma | ACH-002141", - "Esophagogastric Adenocarcinoma | ACH-002161", - "Esophagogastric Adenocarcinoma | ACH-002202", - "Esophagogastric Adenocarcinoma | ACH-002446", - "Esophagogastric Adenocarcinoma | ACH-002705", - "Esophagogastric Adenocarcinoma | ACH-002706" - ], - "type": "scattergl", - "x": { - "bdata": "yozFPzWfT7+uzh8/IfiKPRGGhz+1ueY+QRE4P6SSnz/XTrE+JlTqPiF3AT4UozPAn5vFveLgVD+4bqo/qQYvP/bv2L2OdIo/LxaZP6/yDz+Ubow/Nv42wGf5kj/MIC/AcY63P3tm8j7W+J8/6kggP/b7tz+2/qA/VuN4P81eDD+spOI+iFKHP4KtjD2TZz4/Y2UwPyLV2z/e5OI/7tVkPwqcYz/ac4A/XT5hP6GipD8=", - "dtype": "f4" - }, - "y": { - "bdata": "0F1Iv6dvtj/qPNU9u6IaPzXfA7+959o+QgVIvWKaIL9qzHo+GNOBPuGfaz4CUFK/F20uP01TJb0XkzS/d8FYvSOCRT+XwT2+mPv1vqlOKT50V6u+3FgqvxEyDr/ap42/gMgjv3QDbL3Q8+e++R0KPpbUUr801Da//gXGvmVANL6M1H49pV9Rvq0urT7PEay9v7xMPgXXib+k9GK/INs8vurXg75LK+S+LvIDvsvnIr8=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000053", - "ACH-000101", - "ACH-000226", - "ACH-000233", - "ACH-000338", - "ACH-000664", - "ACH-000773", - "ACH-001111", - "ACH-001119", - "ACH-001737" - ], - "hoverinfo": "text", - "marker": { - "color": "#FE00CE", - "size": 7 - }, - "mode": "markers", - "name": "Mature T and NK Neoplasms", - "text": [ - "Mature T and NK Neoplasms | ACH-000053", - "Mature T and NK Neoplasms | ACH-000101", - "Mature T and NK Neoplasms | ACH-000226", - "Mature T and NK Neoplasms | ACH-000233", - "Mature T and NK Neoplasms | ACH-000338", - "Mature T and NK Neoplasms | ACH-000664", - "Mature T and NK Neoplasms | ACH-000773", - "Mature T and NK Neoplasms | ACH-001111", - "Mature T and NK Neoplasms | ACH-001119", - "Mature T and NK Neoplasms | ACH-001737" - ], - "type": "scattergl", - "x": { - "bdata": "w/RRP0TM5j9x3Lc/5rKhP7Xy/D5hARJAzPhuPxnvNz/1NZ++yX8zPw==", - "dtype": "f4" - }, - "y": { - "bdata": "CX/IvjNkh78QJlS/lw0iv6BQyT4pp62/yj3Zvoh6Cz3D43I/75TxPQ==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000054" - ], - "hoverinfo": "text", - "marker": { - "color": "#0DF9FF", - "size": 7 - }, - "mode": "markers", - "name": "Fibrosarcoma", - "text": [ - "Fibrosarcoma | ACH-000054" - ], - "type": "scattergl", - "x": { - "bdata": "Xb2cPg==", - "dtype": "f4" - }, - "y": { - "bdata": "2PABPw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000055", - "ACH-000095", - "ACH-000160", - "ACH-000211", - "ACH-000776", - "ACH-001020", - "ACH-001028", - "ACH-001031", - "ACH-001033", - "ACH-001053", - "ACH-001054", - "ACH-001232", - "ACH-001289", - "ACH-001670", - "ACH-001711" - ], - "hoverinfo": "text", - "marker": { - "color": "#F6F926", - "size": 7 - }, - "mode": "markers", - "name": "Embryonal Tumor", - "text": [ - "Embryonal Tumor | ACH-000055", - "Embryonal Tumor | ACH-000095", - "Embryonal Tumor | ACH-000160", - "Embryonal Tumor | ACH-000211", - "Embryonal Tumor | ACH-000776", - "Embryonal Tumor | ACH-001020", - "Embryonal Tumor | ACH-001028", - "Embryonal Tumor | ACH-001031", - "Embryonal Tumor | ACH-001033", - "Embryonal Tumor | ACH-001053", - "Embryonal Tumor | ACH-001054", - "Embryonal Tumor | ACH-001232", - "Embryonal Tumor | ACH-001289", - "Embryonal Tumor | ACH-001670", - "Embryonal Tumor | ACH-001711" - ], - "type": "scattergl", - "x": { - "bdata": "J8WEP0P6Xz//2OA/5R6aPSWYIT+tPQY//We+P+DJvj/qpyU/l18bP7Ziyz8j2AA9uvk0P14NgT+i1Eo/", - "dtype": "f4" - }, - "y": { - "bdata": "CwenvkQ2Lr5OaFu/WsE7PySRKj7i35g+uEIXvyqTFb8zmE8+mSwJPU8nUr/zUIs/ofHDPekKPb6OtoY+", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000070", - "ACH-000151", - "ACH-000782", - "ACH-000922", - "ACH-000938", - "ACH-000960", - "ACH-001484", - "ACH-001520", - "ACH-001669", - "ACH-001735", - "ACH-001736", - "ACH-001993", - "ACH-002059" - ], - "hoverinfo": "text", - "marker": { - "color": "#FF9616", - "size": 7 - }, - "mode": "markers", - "name": "B-Lymphoblastic Leukemia/Lymphoma", - "text": [ - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000070", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000151", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000782", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000922", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000938", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000960", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001484", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001520", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001669", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001735", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001736", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001993", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-002059" - ], - "type": "scattergl", - "x": { - "bdata": "zSnTPzVNcz8uvbk/E4gKQGpV8j+lytg/BXGlP1VYzj/+fP8/H+OjPymGCUA5A2k/MN+7Pw==", - "dtype": "f4" - }, - "y": { - "bdata": "xTR/vxyTAr+8Ekq/TKrJv/jokL/9A2y/jZ4zvzMNa78I/6W//So6vyh6tb+YgbG+cUZQvw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000074", - "ACH-000076", - "ACH-000198", - "ACH-000295", - "ACH-000326", - "ACH-000551", - "ACH-000604", - "ACH-000920", - "ACH-000983", - "ACH-002061" - ], - "hoverinfo": "text", - "marker": { - "color": "#479B55", - "size": 7 - }, - "mode": "markers", - "name": "Myeloproliferative Neoplasms", - "text": [ - "Myeloproliferative Neoplasms | ACH-000074", - "Myeloproliferative Neoplasms | ACH-000076", - "Myeloproliferative Neoplasms | ACH-000198", - "Myeloproliferative Neoplasms | ACH-000295", - "Myeloproliferative Neoplasms | ACH-000326", - "Myeloproliferative Neoplasms | ACH-000551", - "Myeloproliferative Neoplasms | ACH-000604", - "Myeloproliferative Neoplasms | ACH-000920", - "Myeloproliferative Neoplasms | ACH-000983", - "Myeloproliferative Neoplasms | ACH-002061" - ], - "type": "scattergl", - "x": { - "bdata": "sTGYPxZyqj/zjR1ATKYGPzTrwj+qiak/eXpjP73FAz8B8+c/QSymPw==", - "dtype": "f4" - }, - "y": { - "bdata": "fh4hv2Z8Kb8ddN2/YQOTPdfsfL/O4Bm/QXJYvrfEPT5FRpi/R6YDvw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000077", - "ACH-000583", - "ACH-001197", - "ACH-001642" - ], - "hoverinfo": "text", - "marker": { - "color": "#EEA6FB", - "size": 7 - }, - "mode": "markers", - "name": "Non-Hodgkin Lymphoma", - "text": [ - "Non-Hodgkin Lymphoma | ACH-000077", - "Non-Hodgkin Lymphoma | ACH-000583", - "Non-Hodgkin Lymphoma | ACH-001197", - "Non-Hodgkin Lymphoma | ACH-001642" - ], - "type": "scattergl", - "x": { - "bdata": "OgKzPwCyI8CdJ48/JesyPw==", - "dtype": "f4" - }, - "y": { - "bdata": "/9oovw5V0r+ougS/V/CsvA==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000078", - "ACH-000099", - "ACH-000120", - "ACH-000149", - "ACH-000203", - "ACH-000227", - "ACH-000259", - "ACH-000260", - "ACH-000310", - "ACH-000312", - "ACH-000341", - "ACH-000366", - "ACH-000804", - "ACH-001188", - "ACH-001300", - "ACH-001301", - "ACH-001302", - "ACH-001303", - "ACH-001338", - "ACH-001344", - "ACH-001354", - "ACH-001366", - "ACH-001367", - "ACH-001481", - "ACH-001548", - "ACH-001603", - "ACH-001674", - "ACH-002080", - "ACH-002083", - "ACH-002261", - "ACH-002278", - "ACH-002280", - "ACH-002282", - "ACH-002283", - "ACH-002284", - "ACH-002285", - "ACH-002922" - ], - "hoverinfo": "text", - "marker": { - "color": "#DC587D", - "size": 7 - }, - "mode": "markers", - "name": "Neuroblastoma", - "text": [ - "Neuroblastoma | ACH-000078", - "Neuroblastoma | ACH-000099", - "Neuroblastoma | ACH-000120", - "Neuroblastoma | ACH-000149", - "Neuroblastoma | ACH-000203", - "Neuroblastoma | ACH-000227", - "Neuroblastoma | ACH-000259", - "Neuroblastoma | ACH-000260", - "Neuroblastoma | ACH-000310", - "Neuroblastoma | ACH-000312", - "Neuroblastoma | ACH-000341", - "Neuroblastoma | ACH-000366", - "Neuroblastoma | ACH-000804", - "Neuroblastoma | ACH-001188", - "Neuroblastoma | ACH-001300", - "Neuroblastoma | ACH-001301", - "Neuroblastoma | ACH-001302", - "Neuroblastoma | ACH-001303", - "Neuroblastoma | ACH-001338", - "Neuroblastoma | ACH-001344", - "Neuroblastoma | ACH-001354", - "Neuroblastoma | ACH-001366", - "Neuroblastoma | ACH-001367", - "Neuroblastoma | ACH-001481", - "Neuroblastoma | ACH-001548", - "Neuroblastoma | ACH-001603", - "Neuroblastoma | ACH-001674", - "Neuroblastoma | ACH-002080", - "Neuroblastoma | ACH-002083", - "Neuroblastoma | ACH-002261", - "Neuroblastoma | ACH-002278", - "Neuroblastoma | ACH-002280", - "Neuroblastoma | ACH-002282", - "Neuroblastoma | ACH-002283", - "Neuroblastoma | ACH-002284", - "Neuroblastoma | ACH-002285", - "Neuroblastoma | ACH-002922" - ], - "type": "scattergl", - "x": { - "bdata": "m1kbP34SqD9tt+k+wRKDP57ogT0vgsu+5AnmP4aRZz91B8++cVg3P95kWj2qlT0/lnK3P0SWdD8FI6g/vs0SvMan8D5qo2I+LrK5P259kj6XTSA/4p9qPzEmlT85EA4+pMkWPhP/eT8srJM/3aMywO+Jzj/DrNk/G0fQP7ejzD/sp6Q/E+ZaP5NgM8DlfyFAwZCWPw==", - "dtype": "f4" - }, - "y": { - "bdata": "BQ2OPmMv/b4UQXU+99mcvDTAKD856qA/tFZ3v18FLb6ca5c/09sgPZ++Aj/NFRE9OUcwvwTpcr6hKeC+/ZRCPxQWyj4uUQk/X1kEv7UK+T6tdDY+JpBFvj7PxL4+kAk/NK4YP+I25b3K1vy+EFxSv+TQvL5BPkq/Sy8Vv3VJAL//c+S+IYgcvXtIUr9ENpK/UX7jvg==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000082", - "ACH-000359", - "ACH-000364", - "ACH-000410", - "ACH-000748", - "ACH-001001", - "ACH-001526", - "ACH-001715", - "ACH-001814", - "ACH-002067", - "ACH-002069", - "ACH-002471", - "ACH-002834" - ], - "hoverinfo": "text", - "marker": { - "color": "#D626FF", - "size": 7 - }, - "mode": "markers", - "name": "Osteosarcoma", - "text": [ - "Osteosarcoma | ACH-000082", - "Osteosarcoma | ACH-000359", - "Osteosarcoma | ACH-000364", - "Osteosarcoma | ACH-000410", - "Osteosarcoma | ACH-000748", - "Osteosarcoma | ACH-001001", - "Osteosarcoma | ACH-001526", - "Osteosarcoma | ACH-001715", - "Osteosarcoma | ACH-001814", - "Osteosarcoma | ACH-002067", - "Osteosarcoma | ACH-002069", - "Osteosarcoma | ACH-002471", - "Osteosarcoma | ACH-002834" - ], - "type": "scattergl", - "x": { - "bdata": "iIiEv+/OTb/Yl0c/yCXgPsQFND+4+OE/EprBvpuiB78lsSq/ZUTdPrrhNr2ve5C7aVM4wA==", - "dtype": "f4" - }, - "y": { - "bdata": "O5zRP+sHrT8CqIo9GdyvPp1FAj/SXAa/rROPP13Mhz8Zq8E/rV+GPhWMQT9HzGc/fiYavw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000086", - "ACH-000092", - "ACH-000153", - "ACH-000319", - "ACH-000331", - "ACH-000335", - "ACH-000367", - "ACH-000569", - "ACH-000645", - "ACH-000648", - "ACH-001547", - "ACH-001555", - "ACH-001556", - "ACH-001557", - "ACH-001558", - "ACH-001559", - "ACH-001560", - "ACH-001562", - "ACH-001977", - "ACH-001992", - "ACH-002033" - ], - "hoverinfo": "text", - "marker": { - "color": "#6E899C", - "size": 7 - }, - "mode": "markers", - "name": "Pleural Mesothelioma", - "text": [ - "Pleural Mesothelioma | ACH-000086", - "Pleural Mesothelioma | ACH-000092", - "Pleural Mesothelioma | ACH-000153", - "Pleural Mesothelioma | ACH-000319", - "Pleural Mesothelioma | ACH-000331", - "Pleural Mesothelioma | ACH-000335", - "Pleural Mesothelioma | ACH-000367", - "Pleural Mesothelioma | ACH-000569", - "Pleural Mesothelioma | ACH-000645", - "Pleural Mesothelioma | ACH-000648", - "Pleural Mesothelioma | ACH-001547", - "Pleural Mesothelioma | ACH-001555", - "Pleural Mesothelioma | ACH-001556", - "Pleural Mesothelioma | ACH-001557", - "Pleural Mesothelioma | ACH-001558", - "Pleural Mesothelioma | ACH-001559", - "Pleural Mesothelioma | ACH-001560", - "Pleural Mesothelioma | ACH-001562", - "Pleural Mesothelioma | ACH-001977", - "Pleural Mesothelioma | ACH-001992", - "Pleural Mesothelioma | ACH-002033" - ], - "type": "scattergl", - "x": { - "bdata": "h88/P0wYCr/maMS+Xl61vgigiz6T7U0/GCk5wM3GqT7FFPy+jRPNPnShcb6/dn89WugUP0dBij4OczrA0/s2wKY5NMBN6zDA1G+jPwiEcT+wSUq/", - "dtype": "f4" - }, - "y": { - "bdata": "jfPtPUJbnj8D45Y/ty2SPyCD0T6nzRE+z2gGv6coAj+7N6A/Qgq7Pj9yRj+iOhk//gSHPvaPGj/HUf++ChExvychV7+ta4C/5kERvwwDKb5wOL8/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000090", - "ACH-000115", - "ACH-000956", - "ACH-000977", - "ACH-000979", - "ACH-001422", - "ACH-001627", - "ACH-001648", - "ACH-001649" - ], - "hoverinfo": "text", - "marker": { - "color": "#00B5F7", - "size": 7 - }, - "mode": "markers", - "name": "Prostate Adenocarcinoma", - "text": [ - "Prostate Adenocarcinoma | ACH-000090", - "Prostate Adenocarcinoma | ACH-000115", - "Prostate Adenocarcinoma | ACH-000956", - "Prostate Adenocarcinoma | ACH-000977", - "Prostate Adenocarcinoma | ACH-000979", - "Prostate Adenocarcinoma | ACH-001422", - "Prostate Adenocarcinoma | ACH-001627", - "Prostate Adenocarcinoma | ACH-001648", - "Prostate Adenocarcinoma | ACH-001649" - ], - "type": "scattergl", - "x": { - "bdata": "aZDAPF8mXb8lu1M/6fbKPxuS6D7/ZoK/a0IswDp6LcAZojbA", - "dtype": "f4" - }, - "y": { - "bdata": "fb4gPwLimT+eLEu9xFtTv6K0Sj5qAso/MySav9AHlL8X8SW/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000096", - "ACH-000172", - "ACH-000533", - "ACH-000597", - "ACH-001099", - "ACH-001128", - "ACH-001211", - "ACH-001212", - "ACH-001532" - ], - "hoverinfo": "text", - "marker": { - "color": "#B68E00", - "size": 7 - }, - "mode": "markers", - "name": "Rhabdoid Cancer", - "text": [ - "Rhabdoid Cancer | ACH-000096", - "Rhabdoid Cancer | ACH-000172", - "Rhabdoid Cancer | ACH-000533", - "Rhabdoid Cancer | ACH-000597", - "Rhabdoid Cancer | ACH-001099", - "Rhabdoid Cancer | ACH-001128", - "Rhabdoid Cancer | ACH-001211", - "Rhabdoid Cancer | ACH-001212", - "Rhabdoid Cancer | ACH-001532" - ], - "type": "scattergl", - "x": { - "bdata": "BFprPyOAHz/qLtI/X6h9Pz2v2j9ULD8/HMBjP3B/GT8+FM8/", - "dtype": "f4" - }, - "y": { - "bdata": "So8FPSP5mD4e9Tm/pBJBvoR+Rr8MpZi6Nekyvtl5iT5pYWW/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000100", - "ACH-000169", - "ACH-000607", - "ACH-000833", - "ACH-001050", - "ACH-001096", - "ACH-001184", - "ACH-001196", - "ACH-001740", - "ACH-001745", - "ACH-001750", - "ACH-001765", - "ACH-002048" - ], - "hoverinfo": "text", - "marker": { - "color": "#C9FBE5", - "size": 7 - }, - "mode": "markers", - "name": "Rhabdomyosarcoma", - "text": [ - "Rhabdomyosarcoma | ACH-000100", - "Rhabdomyosarcoma | ACH-000169", - "Rhabdomyosarcoma | ACH-000607", - "Rhabdomyosarcoma | ACH-000833", - "Rhabdomyosarcoma | ACH-001050", - "Rhabdomyosarcoma | ACH-001096", - "Rhabdomyosarcoma | ACH-001184", - "Rhabdomyosarcoma | ACH-001196", - "Rhabdomyosarcoma | ACH-001740", - "Rhabdomyosarcoma | ACH-001745", - "Rhabdomyosarcoma | ACH-001750", - "Rhabdomyosarcoma | ACH-001765", - "Rhabdomyosarcoma | ACH-002048" - ], - "type": "scattergl", - "x": { - "bdata": "wPV0P5vxbD8mlCY/0gCBP0xqk72jI80/tUKsP998cz8DFB4/eelmP+7uVT/a8aY/YmnTPw==", - "dtype": "f4" - }, - "y": { - "bdata": "QLjSvH6p+70UzwI+f1slvgtZPj8iN1G/w0Iev5fhsL562HA9YLuDvr4AET4DafO+BiBTvw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000108", - "ACH-000685" - ], - "hoverinfo": "text", - "marker": { - "color": "#FF0092", - "size": 7 - }, - "mode": "markers", - "name": "Adenosquamous Carcinoma of the Pancreas", - "text": [ - "Adenosquamous Carcinoma of the Pancreas | ACH-000108", - "Adenosquamous Carcinoma of the Pancreas | ACH-000685" - ], - "type": "scattergl", - "x": { - "bdata": "Fy0zv7paYj8=", - "dtype": "f4" - }, - "y": { - "bdata": "QiSGPyPcpD0=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000133", - "ACH-001310", - "ACH-001453", - "ACH-002210", - "ACH-002247", - "ACH-002462", - "ACH-002463", - "ACH-002464", - "ACH-002465", - "ACH-002467" - ], - "hoverinfo": "text", - "marker": { - "color": "#22FFA7", - "size": 7 - }, - "mode": "markers", - "name": "Non-Cancerous", - "text": [ - "Non-Cancerous | ACH-000133", - "Non-Cancerous | ACH-001310", - "Non-Cancerous | ACH-001453", - "Non-Cancerous | ACH-002210", - "Non-Cancerous | ACH-002247", - "Non-Cancerous | ACH-002462", - "Non-Cancerous | ACH-002463", - "Non-Cancerous | ACH-002464", - "Non-Cancerous | ACH-002465", - "Non-Cancerous | ACH-002467" - ], - "type": "scattergl", - "x": { - "bdata": "JhcjPXM/MsC1s5o+rurhP1gZNsBN1zTAsqU3wHZuPMBl9jHAnOg2wA==", - "dtype": "f4" - }, - "y": { - "bdata": "/Wk5P4COZ78Rx7I++RuVvz2fPb965Ei/+FQfv73xyL5Vo2+/pNAtvw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000141", - "ACH-001607", - "ACH-001619", - "ACH-001850", - "ACH-001861", - "ACH-001961" - ], - "hoverinfo": "text", - "marker": { - "color": "#E3EE9E", - "size": 7 - }, - "mode": "markers", - "name": "Intracholecystic Papillary Neoplasm", - "text": [ - "Intracholecystic Papillary Neoplasm | ACH-000141", - "Intracholecystic Papillary Neoplasm | ACH-001607", - "Intracholecystic Papillary Neoplasm | ACH-001619", - "Intracholecystic Papillary Neoplasm | ACH-001850", - "Intracholecystic Papillary Neoplasm | ACH-001861", - "Intracholecystic Papillary Neoplasm | ACH-001961" - ], - "type": "scattergl", - "x": { - "bdata": "MJ45wJ7+cj8S3/a+1jtqP/MLMMAOAyw/", - "dtype": "f4" - }, - "y": { - "bdata": "B8ABv0adib6RoJo/keaTvpd3hr8pXLy8", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000145", - "ACH-000505", - "ACH-002785" - ], - "hoverinfo": "text", - "marker": { - "color": "#86CE00", - "size": 7 - }, - "mode": "markers", - "name": "Leiomyosarcoma", - "text": [ - "Leiomyosarcoma | ACH-000145", - "Leiomyosarcoma | ACH-000505", - "Leiomyosarcoma | ACH-002785" - ], - "type": "scattergl", - "x": { - "bdata": "atgmv5foZr+U+tK+", - "dtype": "f4" - }, - "y": { - "bdata": "oT+zP0oCyz8Zl6Y/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000159", - "ACH-000189", - "ACH-000234", - "ACH-000246", - "ACH-000250", - "ACH-000262", - "ACH-000272", - "ACH-000313", - "ACH-000317", - "ACH-000375", - "ACH-000385", - "ACH-000411", - "ACH-000433", - "ACH-000459", - "ACH-000484", - "ACH-000495", - "ACH-000649", - "ACH-000684", - "ACH-000709", - "ACH-000792", - "ACH-000907", - "ACH-001163", - "ACH-001194", - "ACH-001398", - "ACH-001687", - "ACH-001688", - "ACH-002150", - "ACH-002189", - "ACH-002533" - ], - "hoverinfo": "text", - "marker": { - "color": "#BC7196", - "size": 7 - }, - "mode": "markers", - "name": "Renal Cell Carcinoma", - "text": [ - "Renal Cell Carcinoma | ACH-000159", - "Renal Cell Carcinoma | ACH-000189", - "Renal Cell Carcinoma | ACH-000234", - "Renal Cell Carcinoma | ACH-000246", - "Renal Cell Carcinoma | ACH-000250", - "Renal Cell Carcinoma | ACH-000262", - "Renal Cell Carcinoma | ACH-000272", - "Renal Cell Carcinoma | ACH-000313", - "Renal Cell Carcinoma | ACH-000317", - "Renal Cell Carcinoma | ACH-000375", - "Renal Cell Carcinoma | ACH-000385", - "Renal Cell Carcinoma | ACH-000411", - "Renal Cell Carcinoma | ACH-000433", - "Renal Cell Carcinoma | ACH-000459", - "Renal Cell Carcinoma | ACH-000484", - "Renal Cell Carcinoma | ACH-000495", - "Renal Cell Carcinoma | ACH-000649", - "Renal Cell Carcinoma | ACH-000684", - "Renal Cell Carcinoma | ACH-000709", - "Renal Cell Carcinoma | ACH-000792", - "Renal Cell Carcinoma | ACH-000907", - "Renal Cell Carcinoma | ACH-001163", - "Renal Cell Carcinoma | ACH-001194", - "Renal Cell Carcinoma | ACH-001398", - "Renal Cell Carcinoma | ACH-001687", - "Renal Cell Carcinoma | ACH-001688", - "Renal Cell Carcinoma | ACH-002150", - "Renal Cell Carcinoma | ACH-002189", - "Renal Cell Carcinoma | ACH-002533" - ], - "type": "scattergl", - "x": { - "bdata": "ORHTvlekN8DrbDq/io4wwB8PNsB+wzTAwg04wITiYL/oQjPAzf2kP3oNwjxO+cs+XS6GvtRIB8ByOTzARZTLvkMLHT/0ok69XFhCvwqJMz7pYIa/gkcSP14HPsCzxsG8gpwzwEL1OsBrrjLAyaKSv5x2gj8=", - "dtype": "f4" - }, - "y": { - "bdata": "VmFzPzSDH795Wq8/BiaDv+1yOL+SMVC/Usggv3ZauD9L12m/qhm7vo4uHz/pXlI+yQiGP6R9LUA6S8G+KTmHP2rioT02Zog/RmTAPx94ID+AjeU/QhS9PeLsl75gF0g/j+9evxvg/L4Pl22/gwLDPxAOAL8=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000163", - "ACH-000181", - "ACH-000188", - "ACH-000207", - "ACH-000228", - "ACH-000238", - "ACH-000415", - "ACH-000472", - "ACH-000500", - "ACH-000503", - "ACH-000518", - "ACH-000546", - "ACH-000548", - "ACH-000549", - "ACH-000606", - "ACH-000618", - "ACH-000619", - "ACH-000630", - "ACH-000682", - "ACH-000732", - "ACH-000735", - "ACH-000740", - "ACH-000762", - "ACH-000771", - "ACH-000778", - "ACH-000794", - "ACH-000832", - "ACH-000836", - "ACH-000846", - "ACH-001228", - "ACH-001229", - "ACH-001331", - "ACH-001332", - "ACH-001346", - "ACH-001347", - "ACH-001385", - "ACH-001509", - "ACH-001510", - "ACH-001511", - "ACH-001542", - "ACH-001543", - "ACH-001625", - "ACH-001626", - "ACH-001641", - "ACH-001675", - "ACH-001690", - "ACH-001691", - "ACH-001692", - "ACH-001694", - "ACH-001695", - "ACH-001696", - "ACH-001698", - "ACH-001699", - "ACH-001701", - "ACH-002029", - "ACH-002030", - "ACH-002042", - "ACH-002043", - "ACH-002044", - "ACH-002045", - "ACH-002212", - "ACH-002249", - "ACH-002250", - "ACH-002251", - "ACH-002265", - "ACH-002294", - "ACH-002295", - "ACH-002296", - "ACH-002297", - "ACH-002298", - "ACH-002305" - ], - "hoverinfo": "text", - "marker": { - "color": "#7E7DCD", - "size": 7 - }, - "mode": "markers", - "name": "Head and Neck Squamous Cell Carcinoma", - "text": [ - "Head and Neck Squamous Cell Carcinoma | ACH-000163", - "Head and Neck Squamous Cell Carcinoma | ACH-000181", - "Head and Neck Squamous Cell Carcinoma | ACH-000188", - "Head and Neck Squamous Cell Carcinoma | ACH-000207", - "Head and Neck Squamous Cell Carcinoma | ACH-000228", - "Head and Neck Squamous Cell Carcinoma | ACH-000238", - "Head and Neck Squamous Cell Carcinoma | ACH-000415", - "Head and Neck Squamous Cell Carcinoma | ACH-000472", - "Head and Neck Squamous Cell Carcinoma | ACH-000500", - "Head and Neck Squamous Cell Carcinoma | ACH-000503", - "Head and Neck Squamous Cell Carcinoma | ACH-000518", - "Head and Neck Squamous Cell Carcinoma | ACH-000546", - "Head and Neck Squamous Cell Carcinoma | ACH-000548", - "Head and Neck Squamous Cell Carcinoma | ACH-000549", - "Head and Neck Squamous Cell Carcinoma | ACH-000606", - "Head and Neck Squamous Cell Carcinoma | ACH-000618", - "Head and Neck Squamous Cell Carcinoma | ACH-000619", - "Head and Neck Squamous Cell Carcinoma | ACH-000630", - "Head and Neck Squamous Cell Carcinoma | ACH-000682", - "Head and Neck Squamous Cell Carcinoma | ACH-000732", - "Head and Neck Squamous Cell Carcinoma | ACH-000735", - "Head and Neck Squamous Cell Carcinoma | ACH-000740", - "Head and Neck Squamous Cell Carcinoma | ACH-000762", - "Head and Neck Squamous Cell Carcinoma | ACH-000771", - "Head and Neck Squamous Cell Carcinoma | ACH-000778", - "Head and Neck Squamous Cell Carcinoma | ACH-000794", - "Head and Neck Squamous Cell Carcinoma | ACH-000832", - "Head and Neck Squamous Cell Carcinoma | ACH-000836", - "Head and Neck Squamous Cell Carcinoma | ACH-000846", - "Head and Neck Squamous Cell Carcinoma | ACH-001228", - "Head and Neck Squamous Cell Carcinoma | ACH-001229", - "Head and Neck Squamous Cell Carcinoma | ACH-001331", - "Head and Neck Squamous Cell Carcinoma | ACH-001332", - "Head and Neck Squamous Cell Carcinoma | ACH-001346", - "Head and Neck Squamous Cell Carcinoma | ACH-001347", - "Head and Neck Squamous Cell Carcinoma | ACH-001385", - "Head and Neck Squamous Cell Carcinoma | ACH-001509", - "Head and Neck Squamous Cell Carcinoma | ACH-001510", - "Head and Neck Squamous Cell Carcinoma | ACH-001511", - "Head and Neck Squamous Cell Carcinoma | ACH-001542", - "Head and Neck Squamous Cell Carcinoma | ACH-001543", - "Head and Neck Squamous Cell Carcinoma | ACH-001625", - "Head and Neck Squamous Cell Carcinoma | ACH-001626", - "Head and Neck Squamous Cell Carcinoma | ACH-001641", - "Head and Neck Squamous Cell Carcinoma | ACH-001675", - "Head and Neck Squamous Cell Carcinoma | ACH-001690", - "Head and Neck Squamous Cell Carcinoma | ACH-001691", - "Head and Neck Squamous Cell Carcinoma | ACH-001692", - "Head and Neck Squamous Cell Carcinoma | ACH-001694", - "Head and Neck Squamous Cell Carcinoma | ACH-001695", - "Head and Neck Squamous Cell Carcinoma | ACH-001696", - "Head and Neck Squamous Cell Carcinoma | ACH-001698", - "Head and Neck Squamous Cell Carcinoma | ACH-001699", - "Head and Neck Squamous Cell Carcinoma | ACH-001701", - "Head and Neck Squamous Cell Carcinoma | ACH-002029", - "Head and Neck Squamous Cell Carcinoma | ACH-002030", - "Head and Neck Squamous Cell Carcinoma | ACH-002042", - "Head and Neck Squamous Cell Carcinoma | ACH-002043", - "Head and Neck Squamous Cell Carcinoma | ACH-002044", - "Head and Neck Squamous Cell Carcinoma | ACH-002045", - "Head and Neck Squamous Cell Carcinoma | ACH-002212", - "Head and Neck Squamous Cell Carcinoma | ACH-002249", - "Head and Neck Squamous Cell Carcinoma | ACH-002250", - "Head and Neck Squamous Cell Carcinoma | ACH-002251", - "Head and Neck Squamous Cell Carcinoma | ACH-002265", - "Head and Neck Squamous Cell Carcinoma | ACH-002294", - "Head and Neck Squamous Cell Carcinoma | ACH-002295", - "Head and Neck Squamous Cell Carcinoma | ACH-002296", - "Head and Neck Squamous Cell Carcinoma | ACH-002297", - "Head and Neck Squamous Cell Carcinoma | ACH-002298", - "Head and Neck Squamous Cell Carcinoma | ACH-002305" - ], - "type": "scattergl", - "x": { - "bdata": "mLj3vCVhAD9shwY/If81wFR4OcCFr4k+5Sw0wBL8ub4npKm9J+A2wBrpgj87xF4/62jDvpY+Ij8OjGQ/flTLP4fUfT91JzE/GMtwP6LhwT533Lk+p8vlPuowlT7iVjLA6C7WvtCPQj/nddI/OZUfPzFEpz83F6m+w5xHP4SEM8AqADjAXdIQP7HdFz9S5/I/fyMDvnS+Dj/GnY6+EneuP6FcCD9m9SG/m7I6v6K2M8CIfwE/EBZzP5qSRDs5ba8/maNcP0zeJD9JBxE/FswKP4zV3D+mnF4/tqnCP/iAjj/B//m+EItPPxyp/T+stk0/2pw2wBrpgT8Cyf0+jAs8Pz+sNMA/yzk/oO03vUfxxj8VkII/Xf+cP4JjM8A=", - "dtype": "f4" - }, - "y": { - "bdata": "d3hAP2S10j1u6oE+Nv04v7KLBL81Tvo+buhVv2uBaD/YRFg/vk4mv9w6hb62SYe9xlZbP3JSZj6EzYW9L4k8v8ZPSr4/bKE+PPMavriHqj6I2d8+s+2YPkDCBT/AlGi/+mp4P3UxmrzNph6/SS/KPNbrYb6XOo4/9bHdPXgKVL8OPhi/a+X4PXJoTj5eVm6/kOtaP6CP+D53fHc/eyo1v6bnRz5Y+pE/b/KhP8/eU7/VnZQ+/vhEvpgqgz/Sna2+HroDvpbSoz11q4M+VE4oPhzFO7+WLby7+T4ov5X7cr6PiIE/9sEovjhOi78ooxa+1Ac2vyFTh73S2bU+2yXoPbkHOb/+cD09NFc3Py2qEL9caCS+t+Wxvok0Qr8=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000174", - "ACH-000191", - "ACH-001306", - "ACH-001307", - "ACH-001356", - "ACH-001443", - "ACH-002041" - ], - "hoverinfo": "text", - "marker": { - "color": "#FC6955", - "size": 7 - }, - "mode": "markers", - "name": "Anaplastic Thyroid Cancer", - "text": [ - "Anaplastic Thyroid Cancer | ACH-000174", - "Anaplastic Thyroid Cancer | ACH-000191", - "Anaplastic Thyroid Cancer | ACH-001306", - "Anaplastic Thyroid Cancer | ACH-001307", - "Anaplastic Thyroid Cancer | ACH-001356", - "Anaplastic Thyroid Cancer | ACH-001443", - "Anaplastic Thyroid Cancer | ACH-002041" - ], - "type": "scattergl", - "x": { - "bdata": "lJeCPmle0j5yIm++pZYkvzOQir9QapY93yx1vQ==", - "dtype": "f4" - }, - "y": { - "bdata": "6zIaP/PbSz6CgZQ/qry2PzWAwD/Qnzk/PPqKPw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000182", - "ACH-000377", - "ACH-001862", - "ACH-002023" - ], - "hoverinfo": "text", - "marker": { - "color": "#E48F72", - "size": 7 - }, - "mode": "markers", - "name": "Ampullary Carcinoma", - "text": [ - "Ampullary Carcinoma | ACH-000182", - "Ampullary Carcinoma | ACH-000377", - "Ampullary Carcinoma | ACH-001862", - "Ampullary Carcinoma | ACH-002023" - ], - "type": "scattergl", - "x": { - "bdata": "Tog0wNMTNcAYF4G+U+kxPw==", - "dtype": "f4" - }, - "y": { - "bdata": "RolKv+WfSL/Cvio/tRZVvg==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000187", - "ACH-000257", - "ACH-000290", - "ACH-000292", - "ACH-000355", - "ACH-000431", - "ACH-000514", - "ACH-000515", - "ACH-000525", - "ACH-000559", - "ACH-000639", - "ACH-000695", - "ACH-000698", - "ACH-000749", - "ACH-000767", - "ACH-000775", - "ACH-000790", - "ACH-000800", - "ACH-000866", - "ACH-000871", - "ACH-000890", - "ACH-000912", - "ACH-001386", - "ACH-001549", - "ACH-002051", - "ACH-002052", - "ACH-002077" - ], - "hoverinfo": "text", - "marker": { - "color": "#2E91E5", - "size": 7 - }, - "mode": "markers", - "name": "Lung Neuroendocrine Tumor", - "text": [ - "Lung Neuroendocrine Tumor | ACH-000187", - "Lung Neuroendocrine Tumor | ACH-000257", - "Lung Neuroendocrine Tumor | ACH-000290", - "Lung Neuroendocrine Tumor | ACH-000292", - "Lung Neuroendocrine Tumor | ACH-000355", - "Lung Neuroendocrine Tumor | ACH-000431", - "Lung Neuroendocrine Tumor | ACH-000514", - "Lung Neuroendocrine Tumor | ACH-000515", - "Lung Neuroendocrine Tumor | ACH-000525", - "Lung Neuroendocrine Tumor | ACH-000559", - "Lung Neuroendocrine Tumor | ACH-000639", - "Lung Neuroendocrine Tumor | ACH-000695", - "Lung Neuroendocrine Tumor | ACH-000698", - "Lung Neuroendocrine Tumor | ACH-000749", - "Lung Neuroendocrine Tumor | ACH-000767", - "Lung Neuroendocrine Tumor | ACH-000775", - "Lung Neuroendocrine Tumor | ACH-000790", - "Lung Neuroendocrine Tumor | ACH-000800", - "Lung Neuroendocrine Tumor | ACH-000866", - "Lung Neuroendocrine Tumor | ACH-000871", - "Lung Neuroendocrine Tumor | ACH-000890", - "Lung Neuroendocrine Tumor | ACH-000912", - "Lung Neuroendocrine Tumor | ACH-001386", - "Lung Neuroendocrine Tumor | ACH-001549", - "Lung Neuroendocrine Tumor | ACH-002051", - "Lung Neuroendocrine Tumor | ACH-002052", - "Lung Neuroendocrine Tumor | ACH-002077" - ], - "type": "scattergl", - "x": { - "bdata": "3m1kP4zVBj6sLEI/fS/AP2PatT/JI6g+q9CtvTreUD9fDzQ/in4mvhq+wj9VFl++CkmMPyB9Zj8Q/KO8w25RP4C3hj+sexY/RULEP2nWtT+g6la+a95YPw0usT4dwec+5TEDv7SulD1U/qa+", - "dtype": "f4" - }, - "y": { - "bdata": "DZuUvVxOKz/C8pe9cvQdv4j1NL+oEgE/Q7pHP/2UXL7UV668RrEpP+6yfL9pV2w//lQEv1iEHr6kjVQ/0w5WvmdsOr7vonA+eb5Pv8YnGL87pWs/CZ26vc0AnD5/DLw+RFSlP0p1ND+a8n4/", - "dtype": "f4" - } - }, - { - "customdata": [ - 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"Endometrial Carcinoma | ACH-000941", - "Endometrial Carcinoma | ACH-000946", - "Endometrial Carcinoma | ACH-000961", - "Endometrial Carcinoma | ACH-000965", - "Endometrial Carcinoma | ACH-000972", - "Endometrial Carcinoma | ACH-000974", - "Endometrial Carcinoma | ACH-000978", - "Endometrial Carcinoma | ACH-000984", - "Endometrial Carcinoma | ACH-000988", - "Endometrial Carcinoma | ACH-000993", - "Endometrial Carcinoma | ACH-000994", - "Endometrial Carcinoma | ACH-000996", - "Endometrial Carcinoma | ACH-001495", - "Endometrial Carcinoma | ACH-001517", - "Endometrial Carcinoma | ACH-001518", - "Endometrial Carcinoma | ACH-002026", - "Endometrial Carcinoma | ACH-002027", - "Endometrial Carcinoma | ACH-002046" - ], - "type": "scattergl", - "x": { - "bdata": "cZ9Yvyr4Ub/BCrI8bRaavUkyCz4LzWq+KC4xwBdZVz9w9Zc/Nx2TPzhpEL9AdmY/UAhgP5bI2T8D7jjARYqNP36mLz4JTd6+p3EIPY367z1uRTPADhwCPfRctr6uIIy/dJA9wDk8kT+qNws/YpqqvQ==", - "dtype": "f4" - }, - "y": { - "bdata": 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ACH-001857", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001858", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001863", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001864", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001959", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001960", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001997", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-002647" - ], - "type": "scattergl", - "x": { - "bdata": "U1Q3wLMgOMCBbzPAnjI3PAuiPj5MGIQ+xQ2XPhBjqD+QXznAHoszwNrONsA9eTzA04g2wLWMMsAwmYW9HYc2wOTsM8DqzTPAcy00wG36rD/h/NM+/sUlP416HT9aiDrAPE6aPoBB4z9EmDQ/Xao3wMigIT8=", - "dtype": "f4" - }, - "y": { - "bdata": "1OMjvwzWEb/Dsk+/VqEQP75c6D6azvw+7UD6PonjNL/Dyg6/6lxTv/oANL/tkLy+eeQsv9+HbL+f8lg/Ipsvv84HVr8/ele/y+RIv37HGL+odoc+MQwHPmNVMb4mSwO/toywPZmofr+JoEs+fTckv6tlUj4=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000217", - "ACH-000221", - "ACH-000316", - "ACH-000361", - 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Carcinoma | ACH-000493", - "Hepatocellular Carcinoma | ACH-000537", - "Hepatocellular Carcinoma | ACH-000577", - "Hepatocellular Carcinoma | ACH-000620", - "Hepatocellular Carcinoma | ACH-000734", - "Hepatocellular Carcinoma | ACH-000848", - "Hepatocellular Carcinoma | ACH-001318", - "Hepatocellular Carcinoma | ACH-002523" - ], - "type": "scattergl", - "x": { - "bdata": "1flGP2aUzT8A3D0+QYqePnKVfr+S/N2+2iASP708kLxdxlw/JmSSvoa0v74M6og/hF/1vhMvmj24PgI/0JmOv/GlIT/TUa0/aiOoP0Q2PD8Wcfc+", - "dtype": "f4" - }, - "y": { - "bdata": "5fBDvdbs/75YxEk/5K8BP0+P6T8joJQ/phWDPhXoHj/lpgq9bwBuP6Cnfz8yhFe+esWQP+rvOT+Vz8o9vDzgP1KS2r3powW/Vf4Jv8nBhT1xP+E+", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000305", - "ACH-000318", - "ACH-000408", - "ACH-000452", - "ACH-000488", - "ACH-000544", - "ACH-000561", - "ACH-000605", - "ACH-000637", - "ACH-000647", - "ACH-000693", - "ACH-000694", - "ACH-000717", - "ACH-000777", - "ACH-000784", - "ACH-000809", - "ACH-000823", - "ACH-000824", - "ACH-000855", - "ACH-000865", - "ACH-000873", - "ACH-000917", - "ACH-002243", - "ACH-002263" - ], - "hoverinfo": "text", - "marker": { - "color": "#222A2A", - "size": 7 - }, - "mode": "markers", - "name": "Esophageal Squamous Cell Carcinoma", - "text": [ - "Esophageal Squamous Cell Carcinoma | ACH-000305", - "Esophageal Squamous Cell Carcinoma | ACH-000318", - "Esophageal Squamous Cell Carcinoma | ACH-000408", - "Esophageal Squamous Cell Carcinoma | ACH-000452", - "Esophageal Squamous Cell Carcinoma | ACH-000488", - "Esophageal Squamous Cell Carcinoma | ACH-000544", - "Esophageal Squamous Cell Carcinoma | ACH-000561", - "Esophageal Squamous Cell Carcinoma | ACH-000605", - "Esophageal Squamous Cell Carcinoma | ACH-000637", - "Esophageal Squamous Cell Carcinoma | ACH-000647", - "Esophageal Squamous Cell Carcinoma | ACH-000693", - "Esophageal Squamous Cell Carcinoma | ACH-000694", - "Esophageal Squamous Cell Carcinoma | ACH-000717", - "Esophageal Squamous Cell Carcinoma | ACH-000777", - "Esophageal 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"size": 7 - }, - "mode": "markers", - "name": "Poorly Differentiated Thyroid Cancer", - "text": [ - "Poorly Differentiated Thyroid Cancer | ACH-000456" - ], - "type": "scattergl", - "x": { - "bdata": "MEOfPw==", - "dtype": "f4" - }, - "y": { - "bdata": "/0ajvg==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000487" - ], - "hoverinfo": "text", - "marker": { - "color": "#750D86", - "size": 7 - }, - "mode": "markers", - "name": "Myelodysplastic Syndromes", - "text": [ - "Myelodysplastic Syndromes | ACH-000487" - ], - "type": "scattergl", - "x": { - "bdata": "cKv3Pw==", - "dtype": "f4" - }, - "y": { - "bdata": "DYOcvw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000490", - "ACH-000556", - "ACH-001333", - "ACH-001334", - "ACH-001335", - "ACH-001336", - "ACH-001360", - "ACH-001402", - "ACH-001451", - "ACH-001515", - "ACH-001651", - "ACH-001652", - "ACH-002020" - ], - "hoverinfo": "text", - "marker": { - "color": "#EB663B", - "size": 7 - }, - "mode": "markers", - "name": "Cervical Squamous Cell Carcinoma", - "text": [ - "Cervical Squamous Cell Carcinoma | ACH-000490", - "Cervical Squamous Cell Carcinoma | ACH-000556", - "Cervical Squamous Cell Carcinoma | ACH-001333", - "Cervical Squamous Cell Carcinoma | ACH-001334", - "Cervical Squamous Cell Carcinoma | ACH-001335", - "Cervical Squamous Cell Carcinoma | ACH-001336", - "Cervical Squamous Cell Carcinoma | ACH-001360", - "Cervical Squamous Cell Carcinoma | ACH-001402", - "Cervical Squamous Cell Carcinoma | ACH-001451", - "Cervical Squamous Cell Carcinoma | ACH-001515", - "Cervical Squamous Cell Carcinoma | ACH-001651", - "Cervical Squamous Cell Carcinoma | ACH-001652", - "Cervical Squamous Cell Carcinoma | ACH-002020" - ], - "type": "scattergl", - "x": { - "bdata": "Ty0rPxIomj6HkXQ/+/HPPzAVUT9fqwM/eGjOv1oqsz/tTTjAXfVePuvXrb/gReo+8WgGPA==", - "dtype": "f4" - }, - "y": { - "bdata": "KFORPjjf1j6WjKq9/UNSv1GltTymq44+kygWQK7Y3b46hiK/kz8XP1j7AkBUyqc+qdcWPw==", - "dtype": "f4" - } - }, - { - 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7 - }, - "mode": "markers", - "name": "Hepatoblastoma", - "text": [ - "Hepatoblastoma | ACH-000671", - "Hepatoblastoma | ACH-000739" - ], - "type": "scattergl", - "x": { - "bdata": "R96vP/gruz4=", - "dtype": "f4" - }, - "y": { - "bdata": "UHgBvwhVpj4=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000702", - "ACH-000754", - "ACH-001685" - ], - "hoverinfo": "text", - "marker": { - "color": "#FC0080", - "size": 7 - }, - "mode": "markers", - "name": "Hodgkin Lymphoma", - "text": [ - "Hodgkin Lymphoma | ACH-000702", - "Hodgkin Lymphoma | ACH-000754", - "Hodgkin Lymphoma | ACH-001685" - ], - "type": "scattergl", - "x": { - "bdata": "ArigPoiJHD+My4a7", - "dtype": "f4" - }, - "y": { - "bdata": "7FBdPiHBDj4pHxE/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000716", - "ACH-000903", - "ACH-001528" - ], - "hoverinfo": "text", - "marker": { - "color": "#B2828D", - "size": 7 - }, - "mode": "markers", - "name": "Well-Differentiated Thyroid Cancer", - "text": [ - 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ACH-000005", - "Acute Myeloid Leukemia | ACH-000045", - "Acute Myeloid Leukemia | ACH-000113", - "Acute Myeloid Leukemia | ACH-000146", - "Acute Myeloid Leukemia | ACH-000168", - "Acute Myeloid Leukemia | ACH-000190", - "Acute Myeloid Leukemia | ACH-000195", - "Acute Myeloid Leukemia | ACH-000263", - "Acute Myeloid Leukemia | ACH-000294", - "Acute Myeloid Leukemia | ACH-000336", - "Acute Myeloid Leukemia | ACH-000362", - "Acute Myeloid Leukemia | ACH-000387", - "Acute Myeloid Leukemia | ACH-000406", - "Acute Myeloid Leukemia | ACH-000498", - "Acute Myeloid Leukemia | ACH-000557", - "Acute Myeloid Leukemia | ACH-000602", - "Acute Myeloid Leukemia | ACH-000770", - "Acute Myeloid Leukemia | ACH-001036", - "Acute Myeloid Leukemia | ACH-001129", - "Acute Myeloid Leukemia | ACH-001574", - "Acute Myeloid Leukemia | ACH-001577", - "Acute Myeloid Leukemia | ACH-001613", - "Acute Myeloid Leukemia | ACH-001618", - "Acute Myeloid Leukemia | ACH-001647", - "Acute Myeloid Leukemia | ACH-001656" - ], 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ACH-000963", - "Colorectal Adenocarcinoma | ACH-000969", - "Colorectal Adenocarcinoma | ACH-000970", - "Colorectal Adenocarcinoma | ACH-000971", - "Colorectal Adenocarcinoma | ACH-000985", - "Colorectal Adenocarcinoma | ACH-000986", - "Colorectal Adenocarcinoma | ACH-000991", - "Colorectal Adenocarcinoma | ACH-000997", - "Colorectal Adenocarcinoma | ACH-001039", - "Colorectal Adenocarcinoma | ACH-001061", - "Colorectal Adenocarcinoma | ACH-001081", - "Colorectal Adenocarcinoma | ACH-001345", - "Colorectal Adenocarcinoma | ACH-001399", - "Colorectal Adenocarcinoma | ACH-001454", - "Colorectal Adenocarcinoma | ACH-001458", - "Colorectal Adenocarcinoma | ACH-001459", - "Colorectal Adenocarcinoma | ACH-001460", - "Colorectal Adenocarcinoma | ACH-001461", - "Colorectal Adenocarcinoma | ACH-001786", - "Colorectal Adenocarcinoma | ACH-002024", - "Colorectal Adenocarcinoma | ACH-002025", - "Colorectal Adenocarcinoma | ACH-002233", - "Colorectal Adenocarcinoma | ACH-002535", - "Colorectal 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ACH-000896", - "Bladder Urothelial Carcinoma | ACH-000905", - "Bladder Urothelial Carcinoma | ACH-001183", - "Bladder Urothelial Carcinoma | ACH-001407", - "Bladder Urothelial Carcinoma | ACH-001409", - "Bladder Urothelial Carcinoma | ACH-001412", - "Bladder Urothelial Carcinoma | ACH-001413", - "Bladder Urothelial Carcinoma | ACH-001414", - "Bladder Urothelial Carcinoma | ACH-001415", - "Bladder Urothelial Carcinoma | ACH-001416" - ], - "type": "scattergl", - "x": { - "bdata": "0rv5PzG3yj+vyNg/FhtpQDqeCUAYkt4/6UXbvcBk9cADpklACDL1wFdV9cDAIwVApjTgP3fmAkBPV3O/cGzOP4y1VEBUPlBA7EJTQAGJ9cC0txFATzMbQLZZ9cAoOPXA90b1wNRY9cBkMvXAuFn1wD6N9cAQW/XA", - "dtype": "f4" - }, - "y": { - "bdata": "hcSLP9+nzD+pwsA9NZ2gu0SA2T4BWpo+kxOOP+H0br6XAgU/ZhR0vo+Jbb7meFQ/aJesP52y6T+q1KQ/bMNAPjR9IT99XYw/u/U1Pwu8Wb5bMjM/M4kPP5r9Xb4GpW++gyhovq9/bL5X74C+jlddvs4RZb6kAHO+", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000012", - "ACH-000015", - "ACH-000021", - "ACH-000029", - "ACH-000030", - "ACH-000035", - 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"ACH-000853", - "ACH-000858", - "ACH-000860", - "ACH-000861", - "ACH-000867", - "ACH-000869", - "ACH-000872", - "ACH-000878", - "ACH-000886", - "ACH-000888", - "ACH-000894", - "ACH-000900", - "ACH-000901", - "ACH-000916", - "ACH-000921", - "ACH-000924", - "ACH-000929", - "ACH-000945", - "ACH-000975", - "ACH-000980", - "ACH-001075", - "ACH-001137", - "ACH-001233", - "ACH-002035", - "ACH-002156", - "ACH-002522", - "ACH-002526", - "ACH-002531", - "ACH-002650", - "ACH-003012" - ], - "hoverinfo": "text", - "marker": { - "color": "#FFA15A", - "size": 7 - }, - "mode": "markers", - "name": "Non-Small Cell Lung Cancer", - "text": [ - "Non-Small Cell Lung Cancer | ACH-000012", - "Non-Small Cell Lung Cancer | ACH-000015", - "Non-Small Cell Lung Cancer | ACH-000021", - "Non-Small Cell Lung Cancer | ACH-000029", - "Non-Small Cell Lung Cancer | ACH-000030", - "Non-Small Cell Lung Cancer | ACH-000035", - "Non-Small Cell Lung Cancer | ACH-000143", - "Non-Small Cell Lung Cancer | ACH-000161", - "Non-Small Cell Lung Cancer | ACH-000176", - "Non-Small Cell Lung Cancer | ACH-000251", - "Non-Small Cell Lung Cancer | ACH-000261", - "Non-Small Cell Lung Cancer | ACH-000264", - "Non-Small Cell Lung Cancer | ACH-000311", - "Non-Small Cell Lung Cancer | ACH-000337", - "Non-Small Cell Lung Cancer | ACH-000339", - "Non-Small Cell Lung Cancer | ACH-000343", - "Non-Small Cell Lung Cancer | ACH-000378", - "Non-Small Cell Lung Cancer | ACH-000390", - "Non-Small Cell Lung Cancer | ACH-000395", - "Non-Small Cell Lung Cancer | ACH-000414", - "Non-Small Cell Lung Cancer | ACH-000416", - "Non-Small Cell Lung Cancer | ACH-000434", - "Non-Small Cell Lung Cancer | ACH-000438", - "Non-Small Cell Lung Cancer | ACH-000442", - "Non-Small Cell Lung Cancer | ACH-000444", - "Non-Small Cell Lung Cancer | ACH-000448", - "Non-Small Cell Lung Cancer | ACH-000454", - "Non-Small Cell Lung Cancer | ACH-000463", - "Non-Small Cell Lung Cancer | ACH-000481", - "Non-Small Cell Lung Cancer | ACH-000496", - "Non-Small Cell Lung Cancer | ACH-000510", - "Non-Small Cell Lung Cancer | ACH-000511", - "Non-Small Cell Lung Cancer | ACH-000521", - "Non-Small Cell Lung Cancer | ACH-000528", - "Non-Small Cell Lung Cancer | ACH-000562", - "Non-Small Cell Lung Cancer | ACH-000563", - "Non-Small Cell Lung Cancer | ACH-000585", - "Non-Small Cell Lung Cancer | ACH-000587", - "Non-Small Cell Lung Cancer | ACH-000589", - "Non-Small Cell Lung Cancer | ACH-000596", - "Non-Small Cell Lung Cancer | ACH-000627", - "Non-Small Cell Lung Cancer | ACH-000638", - "Non-Small Cell Lung Cancer | ACH-000662", - "Non-Small Cell Lung Cancer | ACH-000665", - "Non-Small Cell Lung Cancer | ACH-000666", - "Non-Small Cell Lung Cancer | ACH-000667", - "Non-Small Cell Lung Cancer | ACH-000672", - "Non-Small Cell Lung Cancer | ACH-000677", - "Non-Small Cell Lung Cancer | ACH-000681", - "Non-Small Cell Lung Cancer | ACH-000700", - "Non-Small Cell Lung Cancer | ACH-000706", - "Non-Small Cell Lung Cancer | ACH-000718", - "Non-Small Cell Lung Cancer | ACH-000747", - "Non-Small Cell Lung Cancer | ACH-000757", - "Non-Small Cell Lung Cancer | ACH-000766", - "Non-Small Cell Lung Cancer | ACH-000769", - "Non-Small Cell Lung Cancer | ACH-000774", - "Non-Small Cell Lung Cancer | ACH-000781", - "Non-Small Cell Lung Cancer | ACH-000785", - "Non-Small Cell Lung Cancer | ACH-000787", - "Non-Small Cell Lung Cancer | ACH-000791", - "Non-Small Cell Lung Cancer | ACH-000826", - "Non-Small Cell Lung Cancer | ACH-000837", - "Non-Small Cell Lung Cancer | ACH-000840", - "Non-Small Cell Lung Cancer | ACH-000841", - "Non-Small Cell Lung Cancer | ACH-000843", - "Non-Small Cell Lung Cancer | ACH-000845", - "Non-Small Cell Lung Cancer | ACH-000851", - "Non-Small Cell Lung Cancer | ACH-000853", - "Non-Small Cell Lung Cancer | ACH-000858", - "Non-Small Cell Lung Cancer | ACH-000860", - "Non-Small Cell Lung Cancer | ACH-000861", - "Non-Small Cell Lung Cancer | ACH-000867", - "Non-Small Cell Lung Cancer | ACH-000869", - "Non-Small Cell Lung Cancer | ACH-000872", - "Non-Small Cell Lung Cancer | ACH-000878", - "Non-Small Cell Lung Cancer | ACH-000886", - "Non-Small Cell Lung Cancer | ACH-000888", - "Non-Small Cell Lung Cancer | ACH-000894", - "Non-Small Cell Lung Cancer | ACH-000900", - "Non-Small Cell Lung Cancer | ACH-000901", - "Non-Small Cell Lung Cancer | ACH-000916", - "Non-Small Cell Lung Cancer | ACH-000921", - "Non-Small Cell Lung Cancer | ACH-000924", - "Non-Small Cell Lung Cancer | ACH-000929", - "Non-Small Cell Lung Cancer | ACH-000945", - "Non-Small Cell Lung Cancer | ACH-000975", - "Non-Small Cell Lung Cancer | ACH-000980", - "Non-Small Cell Lung Cancer | ACH-001075", - "Non-Small Cell Lung Cancer | ACH-001137", - "Non-Small Cell Lung Cancer | ACH-001233", - "Non-Small Cell Lung Cancer | ACH-002035", - "Non-Small Cell Lung Cancer | ACH-002156", - "Non-Small Cell Lung Cancer | ACH-002522", - "Non-Small Cell Lung Cancer | ACH-002526", - "Non-Small Cell Lung Cancer | ACH-002531", - "Non-Small Cell Lung Cancer | ACH-002650", - "Non-Small Cell Lung Cancer | ACH-003012" - ], - "type": "scattergl", - "x": { - "bdata": "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", - "dtype": "f4" - }, - "y": { - "bdata": 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"ACH-000827", - "ACH-000881", - "ACH-000882", - "ACH-000884", - "ACH-000899", - "ACH-000915", - "ACH-000968", - "ACH-001041", - "ACH-001190", - "ACH-001239", - "ACH-001522", - "ACH-001563", - "ACH-001566", - "ACH-001567", - "ACH-001568", - "ACH-001570", - "ACH-001645", - "ACH-001970", - "ACH-001972", - "ACH-001973", - "ACH-001975", - "ACH-001982", - "ACH-001986", - "ACH-001990", - "ACH-002001", - "ACH-002002", - "ACH-002003", - "ACH-002004", - "ACH-002005", - "ACH-002084", - "ACH-002143", - "ACH-002458", - "ACH-002460", - "ACH-002461", - "ACH-002508", - "ACH-002510", - "ACH-002511", - "ACH-002512", - "ACH-002847", - "ACH-002928" - ], - "hoverinfo": "text", - "marker": { - "color": "#19D3F3", - "size": 7 - }, - "mode": "markers", - "name": "Melanoma", - "text": [ - "Melanoma | ACH-000014", - "Melanoma | ACH-000219", - "Melanoma | ACH-000274", - "Melanoma | ACH-000304", - "Melanoma | ACH-000322", - "Melanoma | ACH-000348", - "Melanoma | ACH-000401", - "Melanoma | ACH-000404", - "Melanoma | ACH-000425", - "Melanoma | ACH-000441", - "Melanoma | ACH-000450", - "Melanoma | ACH-000458", - "Melanoma | ACH-000477", - "Melanoma | ACH-000550", - "Melanoma | ACH-000579", - "Melanoma | ACH-000580", - "Melanoma | ACH-000614", - "Melanoma | ACH-000632", - "Melanoma | ACH-000661", - "Melanoma | ACH-000765", - "Melanoma | ACH-000788", - "Melanoma | ACH-000799", - "Melanoma | ACH-000801", - "Melanoma | ACH-000805", - "Melanoma | ACH-000810", - "Melanoma | ACH-000822", - "Melanoma | ACH-000827", - "Melanoma | ACH-000881", - "Melanoma | ACH-000882", - "Melanoma | ACH-000884", - "Melanoma | ACH-000899", - "Melanoma | ACH-000915", - "Melanoma | ACH-000968", - "Melanoma | ACH-001041", - "Melanoma | ACH-001190", - "Melanoma | ACH-001239", - "Melanoma | ACH-001522", - "Melanoma | ACH-001563", - "Melanoma | ACH-001566", - "Melanoma | ACH-001567", - "Melanoma | ACH-001568", - "Melanoma | ACH-001570", - "Melanoma | ACH-001645", - "Melanoma | ACH-001970", - "Melanoma | ACH-001972", - "Melanoma | ACH-001973", - "Melanoma | ACH-001975", - "Melanoma | ACH-001982", - "Melanoma | ACH-001986", - "Melanoma | ACH-001990", - "Melanoma | ACH-002001", - "Melanoma | ACH-002002", - "Melanoma | ACH-002003", - "Melanoma | ACH-002004", - "Melanoma | ACH-002005", - "Melanoma | ACH-002084", - "Melanoma | ACH-002143", - "Melanoma | ACH-002458", - "Melanoma | ACH-002460", - "Melanoma | ACH-002461", - "Melanoma | ACH-002508", - "Melanoma | ACH-002510", - "Melanoma | ACH-002511", - "Melanoma | ACH-002512", - "Melanoma | ACH-002847", - "Melanoma | ACH-002928" - ], - "type": "scattergl", - "x": { - "bdata": "RBoeQKmUpEBPvdC/Ne4KP3NkUkDyuRK/3akpQL1E9cCkbvXAlydcQDpV9cCcRfXAgTMlP8WRL7+OXfXAMmmqPmSkPEC0nyNAvmD1wJ4I4T8lkMU/5uURP7Z29cAIQc8/ouplP0KT1r8UMOo/WnVEQMDDakCWWjhAgkj1wIHxPkD0mi1AWfzrP5jKqrzmHDdAv7XuP9FI9cDfavXAgHL1wHZe9cDEVfXAjir1PPkzF0BTJvXA4Fn1wHxo9cD5ogVANGdCQCr6W0B9b2JA2LGPQHwAFEBYPfXA1utYQLMNPzuR2AvAKUcqQJo1GkCGwDE/KKZtPhI9OEBV5gTAySquP/zkrD7i4P2/", - "dtype": "f4" - }, - "y": { - "bdata": 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"ACH-001393", - "ACH-001394", - "ACH-001396", - "ACH-001419", - "ACH-001662", - "ACH-001683", - "ACH-001819", - "ACH-002179", - "ACH-002399", - "ACH-002401" - ], - "hoverinfo": "text", - "marker": { - "color": "#FF6692", - "size": 7 - }, - "mode": "markers", - "name": "Invasive Breast Carcinoma", - "text": [ - "Invasive Breast Carcinoma | ACH-000017", - "Invasive Breast Carcinoma | ACH-000019", - "Invasive Breast Carcinoma | ACH-000028", - "Invasive Breast Carcinoma | ACH-000097", - "Invasive Breast Carcinoma | ACH-000111", - "Invasive Breast Carcinoma | ACH-000147", - "Invasive Breast Carcinoma | ACH-000148", - "Invasive Breast Carcinoma | ACH-000212", - "Invasive Breast Carcinoma | ACH-000223", - "Invasive Breast Carcinoma | ACH-000248", - "Invasive Breast Carcinoma | ACH-000258", - "Invasive Breast Carcinoma | ACH-000276", - "Invasive Breast Carcinoma | ACH-000277", - "Invasive Breast Carcinoma | ACH-000288", - "Invasive Breast Carcinoma | ACH-000330", - "Invasive Breast Carcinoma | ACH-000352", - "Invasive Breast Carcinoma | ACH-000374", - "Invasive Breast Carcinoma | ACH-000554", - "Invasive Breast Carcinoma | ACH-000573", - "Invasive Breast Carcinoma | ACH-000621", - "Invasive Breast Carcinoma | ACH-000668", - "Invasive Breast Carcinoma | ACH-000699", - "Invasive Breast Carcinoma | ACH-000711", - "Invasive Breast Carcinoma | ACH-000721", - "Invasive Breast Carcinoma | ACH-000768", - "Invasive Breast Carcinoma | ACH-000783", - "Invasive Breast Carcinoma | ACH-000849", - "Invasive Breast Carcinoma | ACH-000856", - "Invasive Breast Carcinoma | ACH-000876", - "Invasive Breast Carcinoma | ACH-000910", - "Invasive Breast Carcinoma | ACH-000934", - "Invasive Breast Carcinoma | ACH-001065", - "Invasive Breast Carcinoma | ACH-001388", - "Invasive Breast Carcinoma | ACH-001389", - "Invasive Breast Carcinoma | ACH-001390", - "Invasive Breast Carcinoma | ACH-001391", - "Invasive Breast Carcinoma | ACH-001392", - "Invasive Breast Carcinoma | ACH-001393", - "Invasive Breast Carcinoma | ACH-001394", - "Invasive Breast Carcinoma | ACH-001396", - "Invasive Breast Carcinoma | ACH-001419", - "Invasive Breast Carcinoma | ACH-001662", - "Invasive Breast Carcinoma | ACH-001683", - "Invasive Breast Carcinoma | ACH-001819", - "Invasive Breast Carcinoma | ACH-002179", - "Invasive Breast Carcinoma | ACH-002399", - "Invasive Breast Carcinoma | ACH-002401" - ], - "type": "scattergl", - "x": { - "bdata": "hOtRPmIYlT8ZFEJA/CokP62K0T9n0/c/fZToPpTtwD/IHnS/hZaxP3A4P75uMuK9sjkuvjxB1D8x9Rk/8wMDPwPIxT9ykDbAUauiP/vWGsDh95K+/ajHv/y+AUDQuj1AjB3NP3DHEMB6zShAtN+SQAUJ9r9tMfU/sjqAwJQDdUC2glm/2Vf1wHw1B0AiRLa/4V71wHBa9cDuY/XAb4b1wCUeYD8cOXu+v1QZu2/stL84zZE/jMOoP8j+J0A=", - "dtype": "f4" - }, - "y": { - "bdata": "bx9mv6Y817962tO/YaGSv3qEBsDlEMO/Jy6SP1WVCD9/Yyy/JaW8v27Bdr42n0k+U5B1v0OtEEAICoW/Fke1vww4P79nMA3APro9PmqgCD5PYqi/rEjaPvOTKr9xixO/XppvPEoxrr9cYwm/45ckPkjs7r/E4RrAZoL6vxMd1r8O5K48JuBivhgkMT+RPiM+aYJovo9YbL5xWG6+CeVpvl395b6JHiC/H750v3OXdr+PSibA33rjvs3rVL0=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000022", - "ACH-000023", - "ACH-000042", - "ACH-000060", - "ACH-000085", - "ACH-000093", - "ACH-000094", - "ACH-000114", - "ACH-000118", - "ACH-000138", - "ACH-000139", - "ACH-000155", - "ACH-000164", - "ACH-000178", - "ACH-000213", - "ACH-000222", - "ACH-000235", - "ACH-000243", - "ACH-000265", - "ACH-000266", - "ACH-000281", - "ACH-000307", - "ACH-000320", - "ACH-000332", - "ACH-000354", - "ACH-000417", - "ACH-000468", - "ACH-000502", - "ACH-000517", - "ACH-000535", - "ACH-000599", - "ACH-000601", - "ACH-000652", - "ACH-001098", - "ACH-001107", - "ACH-001353", - "ACH-001375", - "ACH-001377", - "ACH-001379", - "ACH-001380", - "ACH-001382", - "ACH-001999", - "ACH-002039", - "ACH-002186", - "ACH-002672" - ], - "hoverinfo": "text", - "marker": { - "color": "#B6E880", - "size": 7 - }, - "mode": "markers", - "name": "Pancreatic Adenocarcinoma", - "text": [ - "Pancreatic Adenocarcinoma | ACH-000022", - "Pancreatic Adenocarcinoma | ACH-000023", - "Pancreatic Adenocarcinoma | ACH-000042", - "Pancreatic Adenocarcinoma | ACH-000060", - "Pancreatic Adenocarcinoma | ACH-000085", - "Pancreatic Adenocarcinoma | ACH-000093", - "Pancreatic Adenocarcinoma | ACH-000094", - "Pancreatic Adenocarcinoma | ACH-000114", - "Pancreatic Adenocarcinoma | ACH-000118", - "Pancreatic Adenocarcinoma | ACH-000138", - "Pancreatic Adenocarcinoma | ACH-000139", - "Pancreatic Adenocarcinoma | ACH-000155", - "Pancreatic Adenocarcinoma | ACH-000164", - "Pancreatic Adenocarcinoma | ACH-000178", - "Pancreatic Adenocarcinoma | ACH-000213", - "Pancreatic Adenocarcinoma | ACH-000222", - "Pancreatic Adenocarcinoma | ACH-000235", - "Pancreatic Adenocarcinoma | ACH-000243", - "Pancreatic Adenocarcinoma | ACH-000265", - "Pancreatic Adenocarcinoma | ACH-000266", - "Pancreatic Adenocarcinoma | ACH-000281", - "Pancreatic Adenocarcinoma | ACH-000307", - "Pancreatic Adenocarcinoma | ACH-000320", - "Pancreatic Adenocarcinoma | ACH-000332", - "Pancreatic Adenocarcinoma | ACH-000354", - "Pancreatic Adenocarcinoma | ACH-000417", - "Pancreatic Adenocarcinoma | ACH-000468", - "Pancreatic Adenocarcinoma | ACH-000502", - "Pancreatic Adenocarcinoma | ACH-000517", - "Pancreatic Adenocarcinoma | ACH-000535", - "Pancreatic Adenocarcinoma | ACH-000599", - "Pancreatic Adenocarcinoma | ACH-000601", - "Pancreatic Adenocarcinoma | ACH-000652", - "Pancreatic Adenocarcinoma | ACH-001098", - "Pancreatic Adenocarcinoma | ACH-001107", - "Pancreatic Adenocarcinoma | ACH-001353", - "Pancreatic Adenocarcinoma | ACH-001375", - "Pancreatic Adenocarcinoma | ACH-001377", - "Pancreatic Adenocarcinoma | ACH-001379", - "Pancreatic Adenocarcinoma | ACH-001380", - "Pancreatic Adenocarcinoma | ACH-001382", - "Pancreatic Adenocarcinoma | ACH-001999", - "Pancreatic Adenocarcinoma | ACH-002039", - "Pancreatic Adenocarcinoma | ACH-002186", - "Pancreatic Adenocarcinoma | ACH-002672" - ], - "type": "scattergl", - "x": { - "bdata": 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"ACH-000660", - "ACH-000697", - "ACH-000714", - "ACH-000763", - "ACH-000817", - "ACH-000821", - "ACH-000829", - "ACH-000838", - "ACH-000889", - "ACH-000914", - "ACH-000944", - "ACH-001450", - "ACH-001498", - "ACH-001533", - "ACH-001539", - "ACH-001616", - "ACH-001634", - "ACH-001639", - "ACH-001677", - "ACH-001707", - "ACH-001709", - "ACH-002055", - "ACH-002062", - "ACH-002214", - "ACH-002215", - "ACH-002478", - "ACH-002485", - "ACH-002500", - "ACH-002677", - "ACH-002678" - ], - "hoverinfo": "text", - "marker": { - "color": "#FF97FF", - "size": 7 - }, - "mode": "markers", - "name": "Mature B-Cell Neoplasms", - "text": [ - "Mature B-Cell Neoplasms | ACH-000024", - "Mature B-Cell Neoplasms | ACH-000106", - "Mature B-Cell Neoplasms | ACH-000124", - "Mature B-Cell Neoplasms | ACH-000167", - "Mature B-Cell Neoplasms | ACH-000183", - "Mature B-Cell Neoplasms | ACH-000204", - "Mature B-Cell Neoplasms | ACH-000271", - "Mature B-Cell Neoplasms | ACH-000315", - "Mature B-Cell Neoplasms | ACH-000334", - "Mature B-Cell Neoplasms | ACH-000346", - "Mature B-Cell Neoplasms | ACH-000363", - "Mature B-Cell Neoplasms | ACH-000365", - "Mature B-Cell Neoplasms | ACH-000371", - "Mature B-Cell Neoplasms | ACH-000398", - "Mature B-Cell Neoplasms | ACH-000402", - "Mature B-Cell Neoplasms | ACH-000405", - "Mature B-Cell Neoplasms | ACH-000426", - "Mature B-Cell Neoplasms | ACH-000436", - "Mature B-Cell Neoplasms | ACH-000512", - "Mature B-Cell Neoplasms | ACH-000541", - "Mature B-Cell Neoplasms | ACH-000567", - "Mature B-Cell Neoplasms | ACH-000576", - "Mature B-Cell Neoplasms | ACH-000588", - "Mature B-Cell Neoplasms | ACH-000653", - "Mature B-Cell Neoplasms | ACH-000654", - "Mature B-Cell Neoplasms | ACH-000656", - "Mature B-Cell Neoplasms | ACH-000660", - "Mature B-Cell Neoplasms | ACH-000697", - "Mature B-Cell Neoplasms | ACH-000714", - "Mature B-Cell Neoplasms | ACH-000763", - "Mature B-Cell Neoplasms | ACH-000817", - "Mature B-Cell Neoplasms | ACH-000821", - "Mature B-Cell Neoplasms | ACH-000829", - "Mature B-Cell Neoplasms | ACH-000838", - "Mature B-Cell Neoplasms | ACH-000889", - "Mature B-Cell Neoplasms | ACH-000914", - "Mature B-Cell Neoplasms | ACH-000944", - "Mature B-Cell Neoplasms | ACH-001450", - "Mature B-Cell Neoplasms | ACH-001498", - "Mature B-Cell Neoplasms | ACH-001533", - "Mature B-Cell Neoplasms | ACH-001539", - "Mature B-Cell Neoplasms | ACH-001616", - "Mature B-Cell Neoplasms | ACH-001634", - "Mature B-Cell Neoplasms | ACH-001639", - "Mature B-Cell Neoplasms | ACH-001677", - "Mature B-Cell Neoplasms | ACH-001707", - "Mature B-Cell Neoplasms | ACH-001709", - "Mature B-Cell Neoplasms | ACH-002055", - "Mature B-Cell Neoplasms | ACH-002062", - "Mature B-Cell Neoplasms | ACH-002214", - "Mature B-Cell Neoplasms | ACH-002215", - "Mature B-Cell Neoplasms | ACH-002478", - "Mature B-Cell Neoplasms | ACH-002485", - "Mature B-Cell Neoplasms | ACH-002500", - "Mature B-Cell Neoplasms | ACH-002677", - "Mature B-Cell Neoplasms | ACH-002678" - ], - 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ACH-001067", - "Meningothelial Tumor | ACH-002070" - ], - "type": "scattergl", - "x": { - "bdata": "yABNQNop9cD6YO4/", - "dtype": "f4" - }, - "y": { - "bdata": "7jABQMvIc749eaQ/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000036", - "ACH-000040", - "ACH-000067", - "ACH-000075", - "ACH-000098", - "ACH-000128", - "ACH-000137", - "ACH-000152", - "ACH-000200", - "ACH-000208", - "ACH-000215", - "ACH-000231", - "ACH-000232", - "ACH-000244", - "ACH-000269", - "ACH-000273", - "ACH-000323", - "ACH-000329", - "ACH-000368", - "ACH-000370", - "ACH-000376", - "ACH-000389", - "ACH-000437", - "ACH-000445", - "ACH-000455", - "ACH-000464", - "ACH-000469", - "ACH-000479", - "ACH-000504", - "ACH-000558", - "ACH-000570", - "ACH-000571", - "ACH-000591", - "ACH-000592", - "ACH-000595", - "ACH-000609", - "ACH-000622", - "ACH-000623", - "ACH-000631", - "ACH-000634", - "ACH-000655", - "ACH-000673", - "ACH-000676", - "ACH-000738", - "ACH-000756", - "ACH-000760", - "ACH-000807", - "ACH-000819", - "ACH-000863", - "ACH-000887", - "ACH-001016", - "ACH-001126", - "ACH-001172", - "ACH-001329", - "ACH-001605", - "ACH-001606", - "ACH-001608", - "ACH-001609", - "ACH-001610", - "ACH-001611", - "ACH-001622", - "ACH-001623", - "ACH-001624", - "ACH-002228", - "ACH-002229", - "ACH-002230", - "ACH-002257", - "ACH-002269", - "ACH-002304", - "ACH-002680" - ], - "hoverinfo": "text", - "marker": { - "color": "#FD3216", - "size": 7 - }, - "mode": "markers", - "name": "Diffuse Glioma", - "text": [ - "Diffuse Glioma | ACH-000036", - "Diffuse Glioma | ACH-000040", - "Diffuse Glioma | ACH-000067", - "Diffuse Glioma | ACH-000075", - "Diffuse Glioma | ACH-000098", - "Diffuse Glioma | ACH-000128", - "Diffuse Glioma | ACH-000137", - "Diffuse Glioma | ACH-000152", - "Diffuse Glioma | ACH-000200", - "Diffuse Glioma | ACH-000208", - "Diffuse Glioma | ACH-000215", - "Diffuse Glioma | ACH-000231", - "Diffuse Glioma | ACH-000232", - "Diffuse Glioma | ACH-000244", - "Diffuse Glioma | ACH-000269", - "Diffuse Glioma | ACH-000273", - "Diffuse Glioma | ACH-000323", - "Diffuse Glioma | ACH-000329", - "Diffuse Glioma | ACH-000368", - "Diffuse Glioma | ACH-000370", - "Diffuse Glioma | ACH-000376", - "Diffuse Glioma | ACH-000389", - "Diffuse Glioma | ACH-000437", - "Diffuse Glioma | ACH-000445", - "Diffuse Glioma | ACH-000455", - "Diffuse Glioma | ACH-000464", - "Diffuse Glioma | ACH-000469", - "Diffuse Glioma | ACH-000479", - "Diffuse Glioma | ACH-000504", - "Diffuse Glioma | ACH-000558", - "Diffuse Glioma | ACH-000570", - "Diffuse Glioma | ACH-000571", - "Diffuse Glioma | ACH-000591", - "Diffuse Glioma | ACH-000592", - "Diffuse Glioma | ACH-000595", - "Diffuse Glioma | ACH-000609", - "Diffuse Glioma | ACH-000622", - "Diffuse Glioma | ACH-000623", - "Diffuse Glioma | ACH-000631", - "Diffuse Glioma | ACH-000634", - "Diffuse Glioma | ACH-000655", - "Diffuse Glioma | ACH-000673", - "Diffuse Glioma | ACH-000676", - "Diffuse Glioma | ACH-000738", - "Diffuse Glioma | ACH-000756", - "Diffuse Glioma | ACH-000760", - "Diffuse Glioma | ACH-000807", - "Diffuse Glioma | ACH-000819", - "Diffuse Glioma | ACH-000863", - "Diffuse Glioma | ACH-000887", - "Diffuse Glioma | ACH-001016", - "Diffuse Glioma | ACH-001126", - "Diffuse Glioma | ACH-001172", - "Diffuse Glioma | ACH-001329", - "Diffuse Glioma | ACH-001605", - "Diffuse Glioma | ACH-001606", - "Diffuse Glioma | ACH-001608", - "Diffuse Glioma | ACH-001609", - "Diffuse Glioma | ACH-001610", - "Diffuse Glioma | ACH-001611", - "Diffuse Glioma | ACH-001622", - "Diffuse Glioma | ACH-001623", - "Diffuse Glioma | ACH-001624", - "Diffuse Glioma | ACH-002228", - "Diffuse Glioma | ACH-002229", - "Diffuse Glioma | ACH-002230", - "Diffuse Glioma | ACH-002257", - "Diffuse Glioma | ACH-002269", - "Diffuse Glioma | ACH-002304", - "Diffuse Glioma | ACH-002680" - ], - "type": "scattergl", - "x": { - "bdata": 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[ - "Sarcoma, NOS | ACH-000037" - ], - "type": "scattergl", - "x": { - "bdata": "LiYbvw==", - "dtype": "f4" - }, - "y": { - "bdata": "atrvPw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000039", - "ACH-000041", - "ACH-000052", - "ACH-000087", - "ACH-000210", - "ACH-000279", - "ACH-000391", - "ACH-000424", - "ACH-000499", - "ACH-001029", - "ACH-001038", - "ACH-001192", - "ACH-001193", - "ACH-001205", - "ACH-001283", - "ACH-001430", - "ACH-001431", - "ACH-002105", - "ACH-002106", - "ACH-002109", - "ACH-002110", - "ACH-002114", - "ACH-002116", - "ACH-002119", - "ACH-002160" - ], - "hoverinfo": "text", - "marker": { - "color": "#6A76FC", - "size": 7 - }, - "mode": "markers", - "name": "Ewing Sarcoma", - "text": [ - "Ewing Sarcoma | ACH-000039", - "Ewing Sarcoma | ACH-000041", - "Ewing Sarcoma | ACH-000052", - "Ewing Sarcoma | ACH-000087", - "Ewing Sarcoma | ACH-000210", - "Ewing Sarcoma | ACH-000279", - "Ewing Sarcoma | ACH-000391", - "Ewing Sarcoma | ACH-000424", - "Ewing Sarcoma | ACH-000499", - "Ewing Sarcoma | ACH-001029", - "Ewing Sarcoma | ACH-001038", - "Ewing Sarcoma | ACH-001192", - "Ewing Sarcoma | ACH-001193", - "Ewing Sarcoma | ACH-001205", - "Ewing Sarcoma | ACH-001283", - "Ewing Sarcoma | ACH-001430", - "Ewing Sarcoma | ACH-001431", - "Ewing Sarcoma | ACH-002105", - "Ewing Sarcoma | ACH-002106", - "Ewing Sarcoma | ACH-002109", - "Ewing Sarcoma | ACH-002110", - "Ewing Sarcoma | ACH-002114", - "Ewing Sarcoma | ACH-002116", - "Ewing Sarcoma | ACH-002119", - "Ewing Sarcoma | ACH-002160" - ], - "type": "scattergl", - "x": { - "bdata": "DIWCPlcphD4KdZ8/thsdQLIjlz9V7UpAk0tyQCU3j0DyikRAMshnQJhb6z9/vPg/VwPoPxxY7j+fkARAc8PTPwXXBkDiogBAl7lOQGySBUBVWphA7U/1wHBz9cDmIoNAD2t4QA==", - "dtype": "f4" - }, - "y": { - "bdata": "F6ncPh4t474dvcY/3PfOvmmndb5xT/a+RMSRP8TFaj8rhCI/O74qP5zz0L+ynJA+tmSQP2iMAj5lVgw+P1gIPxWHhr4laBJA7r+tvyxFxT6QGBk+5lJqvktxY76d8gc/iJ/7vQ==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000047", - "ACH-000144", - "ACH-000216", - "ACH-000239", - "ACH-000247", - "ACH-000255", - "ACH-000303", - "ACH-000325", - "ACH-000344", - "ACH-000356", - "ACH-000383", - "ACH-000427", - "ACH-000466", - "ACH-000485", - "ACH-000507", - "ACH-000581", - "ACH-000616", - "ACH-000633", - "ACH-000736", - "ACH-000746", - "ACH-000758", - "ACH-000764", - "ACH-000793", - "ACH-000847", - "ACH-000880", - "ACH-000898", - "ACH-000911", - "ACH-000919", - "ACH-000932", - "ACH-000948", - "ACH-001368", - "ACH-001496", - "ACH-001497", - "ACH-001500", - "ACH-001544", - "ACH-001653", - "ACH-001654", - "ACH-001664", - "ACH-002141", - "ACH-002161", - "ACH-002202", - "ACH-002446", - "ACH-002705", - "ACH-002706" - ], - "hoverinfo": "text", - "marker": { - "color": "#FED4C4", - "size": 7 - }, - "mode": "markers", - "name": "Esophagogastric Adenocarcinoma", - "text": [ - "Esophagogastric Adenocarcinoma | ACH-000047", - "Esophagogastric Adenocarcinoma | ACH-000144", - "Esophagogastric Adenocarcinoma | ACH-000216", - "Esophagogastric Adenocarcinoma | ACH-000239", - "Esophagogastric Adenocarcinoma | ACH-000247", - "Esophagogastric Adenocarcinoma | ACH-000255", - "Esophagogastric Adenocarcinoma | ACH-000303", - "Esophagogastric Adenocarcinoma | ACH-000325", - "Esophagogastric Adenocarcinoma | ACH-000344", - "Esophagogastric Adenocarcinoma | ACH-000356", - "Esophagogastric Adenocarcinoma | ACH-000383", - "Esophagogastric Adenocarcinoma | ACH-000427", - "Esophagogastric Adenocarcinoma | ACH-000466", - "Esophagogastric Adenocarcinoma | ACH-000485", - "Esophagogastric Adenocarcinoma | ACH-000507", - "Esophagogastric Adenocarcinoma | ACH-000581", - "Esophagogastric Adenocarcinoma | ACH-000616", - "Esophagogastric Adenocarcinoma | ACH-000633", - "Esophagogastric Adenocarcinoma | ACH-000736", - "Esophagogastric Adenocarcinoma | ACH-000746", - "Esophagogastric Adenocarcinoma | ACH-000758", - "Esophagogastric Adenocarcinoma | ACH-000764", - "Esophagogastric Adenocarcinoma | ACH-000793", - "Esophagogastric Adenocarcinoma | ACH-000847", - "Esophagogastric Adenocarcinoma | ACH-000880", - "Esophagogastric Adenocarcinoma | ACH-000898", - "Esophagogastric Adenocarcinoma | ACH-000911", - "Esophagogastric Adenocarcinoma | ACH-000919", - "Esophagogastric Adenocarcinoma | ACH-000932", - "Esophagogastric Adenocarcinoma | ACH-000948", - "Esophagogastric Adenocarcinoma | ACH-001368", - "Esophagogastric Adenocarcinoma | ACH-001496", - "Esophagogastric Adenocarcinoma | ACH-001497", - "Esophagogastric Adenocarcinoma | ACH-001500", - "Esophagogastric Adenocarcinoma | ACH-001544", - "Esophagogastric Adenocarcinoma | ACH-001653", - "Esophagogastric Adenocarcinoma | ACH-001654", - "Esophagogastric Adenocarcinoma | ACH-001664", - "Esophagogastric Adenocarcinoma | ACH-002141", - "Esophagogastric Adenocarcinoma | ACH-002161", - "Esophagogastric Adenocarcinoma | ACH-002202", - "Esophagogastric Adenocarcinoma | ACH-002446", - "Esophagogastric Adenocarcinoma | ACH-002705", - "Esophagogastric Adenocarcinoma | ACH-002706" - ], - "type": "scattergl", - "x": { - "bdata": "WLhTQBshJ8BPCxlA/opNPxZrKUDoZe8/mdIJQBIuGEDqf6A/D0DcP/GbFz9yYvXANyF2P71lHEBmrlJA1IbnP/HTND8AgbA/gPlJQEMCvD6f5yJAcmj1wAK8GUDtHvXADD94QC1qAT/jeltA3evlP8X1OkD3PztAGjzPP0oDPT+4rqQ/L7ckQHpu5z2xfQZAF3spQL34WkCcO4BA5+X/P74GPUCVxhZAVLciQPEjWUA=", - "dtype": "f4" - }, - "y": { - "bdata": "FveQv2c2Vb80eC0/JatOPQWBvb8B1NU/YR4vv4vSHMAQkEI/LCf6vn7Rw7/Z7nS+9qzlP3D2q79F+5K/aITvvyP+yj/qi66/zAK/v8HLGMCoro+/2tVgvna4AcDOBoG+UqaQvsv8+L8SlUm/08L7vhRX3r+THXm/2dDjv2Sn9r8Uj6W/HFdhPwkX0L8FWIe/JzPHPwM1DcDJQ8u/DgE+v82cOr5IofW+Em3Uvv7Cyb4=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000053", - "ACH-000101", - "ACH-000226", - "ACH-000233", - "ACH-000338", - "ACH-000664", - "ACH-000773", - "ACH-001111", - "ACH-001119", - "ACH-001737" - ], - "hoverinfo": "text", - "marker": { - "color": "#FE00CE", - "size": 7 - }, - "mode": "markers", - "name": "Mature T and NK Neoplasms", - "text": [ - "Mature T and NK Neoplasms | ACH-000053", - "Mature T and NK Neoplasms | ACH-000101", - "Mature T and NK Neoplasms | ACH-000226", - "Mature T and NK Neoplasms | ACH-000233", - "Mature T and NK Neoplasms | ACH-000338", - "Mature T and NK Neoplasms | ACH-000664", - "Mature T and NK Neoplasms | ACH-000773", - "Mature T and NK Neoplasms | ACH-001111", - "Mature T and NK Neoplasms | ACH-001119", - "Mature T and NK Neoplasms | ACH-001737" - ], - "type": "scattergl", - "x": { - "bdata": "EWe6P5C9Z0BdeE5AwjM9QJPJvD+sbItATXoLQPlr7j/09zG/8jMfQA==", - "dtype": "f4" - }, - "y": { - "bdata": "7uwIwIumIcDK5v+/HiW7v8fczL6mmhXAb47Xv85/hb9OAzW/aUcuPg==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000054" - ], - "hoverinfo": "text", - "marker": { - "color": "#0DF9FF", - "size": 7 - }, - "mode": "markers", - "name": "Fibrosarcoma", - "text": [ - "Fibrosarcoma | ACH-000054" - ], - "type": "scattergl", - "x": { - "bdata": "DTuBPw==", - "dtype": "f4" - }, - "y": { - "bdata": "fpSPPw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000055", - "ACH-000095", - "ACH-000160", - "ACH-000211", - "ACH-000776", - "ACH-001020", - "ACH-001028", - "ACH-001031", - "ACH-001033", - "ACH-001053", - "ACH-001054", - "ACH-001232", - "ACH-001289", - "ACH-001670", - "ACH-001711" - ], - "hoverinfo": "text", - "marker": { - "color": "#F6F926", - "size": 7 - }, - "mode": "markers", - "name": "Embryonal Tumor", - "text": [ - "Embryonal Tumor | ACH-000055", - "Embryonal Tumor | ACH-000095", - "Embryonal Tumor | ACH-000160", - "Embryonal Tumor | ACH-000211", - "Embryonal Tumor | ACH-000776", - "Embryonal Tumor | ACH-001020", - "Embryonal Tumor | ACH-001028", - "Embryonal Tumor | ACH-001031", - "Embryonal Tumor | ACH-001033", - "Embryonal Tumor | ACH-001053", - "Embryonal Tumor | ACH-001054", - "Embryonal Tumor | ACH-001232", - "Embryonal Tumor | ACH-001289", - "Embryonal Tumor | ACH-001670", - "Embryonal Tumor | ACH-001711" - ], - "type": "scattergl", - "x": { - "bdata": "/esoQHAd9z9/anFAHl5zP3E6BECd5QJA1vFTQCNMY0C6Mdg/3HTSPygGWkDQKFA/TeugPwsmOkBiSA9A", - "dtype": "f4" - }, - "y": { - "bdata": "Q8R1v+p5Lb8gP/Y+C+LtP/W6Qz/CeHU/IU+kvpUT8D6yS+M+6LWbviaXi78FYC5AOGz2vu+Q5T7U2sc+", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000070", - "ACH-000151", - "ACH-000782", - "ACH-000922", - "ACH-000938", - "ACH-000960", - "ACH-001484", - "ACH-001520", - "ACH-001669", - "ACH-001735", - "ACH-001736", - "ACH-001993", - "ACH-002059" - ], - "hoverinfo": "text", - "marker": { - "color": "#FF9616", - "size": 7 - }, - "mode": "markers", - "name": "B-Lymphoblastic Leukemia/Lymphoma", - "text": [ - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000070", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000151", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000782", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000922", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000938", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-000960", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001484", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001520", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001669", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001735", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001736", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-001993", - "B-Lymphoblastic Leukemia/Lymphoma | ACH-002059" - ], - "type": "scattergl", - "x": { - "bdata": "DitMQDjJqz/1ZDtAUVFtQEOATUBzyEpA6Xo1QDW7VUBJHm5AC3EhQGJAeUDe6dA/KUE+QA==", - "dtype": "f4" - }, - "y": { - "bdata": "+i4gwBykJcBwwirAq+ZBwC5PWsC1HDPAq8YAwAIsCsDFainAeBA5wOYvRcDGSwrAlaf5vw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000074", - "ACH-000076", - "ACH-000198", - "ACH-000295", - "ACH-000326", - "ACH-000551", - "ACH-000604", - "ACH-000920", - "ACH-000983", - "ACH-002061" - ], - "hoverinfo": "text", - "marker": { - "color": "#479B55", - "size": 7 - }, - "mode": "markers", - "name": "Myeloproliferative Neoplasms", - "text": [ - "Myeloproliferative Neoplasms | ACH-000074", - "Myeloproliferative Neoplasms | ACH-000076", - "Myeloproliferative Neoplasms | ACH-000198", - "Myeloproliferative Neoplasms | ACH-000295", - "Myeloproliferative Neoplasms | ACH-000326", - "Myeloproliferative Neoplasms | ACH-000551", - "Myeloproliferative Neoplasms | ACH-000604", - "Myeloproliferative Neoplasms | ACH-000920", - "Myeloproliferative Neoplasms | ACH-000983", - "Myeloproliferative Neoplasms | ACH-002061" - ], - "type": "scattergl", - "x": { - "bdata": "u1n9P1XPSkA1Y4xAHpSaP8A6X0CWkB1A6Gb9P1Obzj8DFGlADDJEQA==", - "dtype": "f4" - }, - "y": { - "bdata": "WHsbwGzt4L8QWjTAZlPLv25QBcDHQx7AuYDgv8ilFL++ByLAo6L8vw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000077", - "ACH-000583", - "ACH-001197", - "ACH-001642" - ], - "hoverinfo": "text", - "marker": { - "color": "#EEA6FB", - "size": 7 - }, - "mode": "markers", - "name": "Non-Hodgkin Lymphoma", - "text": [ - "Non-Hodgkin Lymphoma | ACH-000077", - "Non-Hodgkin Lymphoma | ACH-000583", - "Non-Hodgkin Lymphoma | ACH-001197", - "Non-Hodgkin Lymphoma | ACH-001642" - ], - "type": "scattergl", - "x": { - "bdata": "k+NUQEUn9cAoSSJABGnVPw==", - "dtype": "f4" - }, - "y": { - "bdata": "vr1nvz1chL4rKPq/i8u3vw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000078", - "ACH-000099", - "ACH-000120", - "ACH-000149", - "ACH-000203", - "ACH-000227", - "ACH-000259", - "ACH-000260", - "ACH-000310", - "ACH-000312", - "ACH-000341", - "ACH-000366", - "ACH-000804", - "ACH-001188", - "ACH-001300", - "ACH-001301", - "ACH-001302", - "ACH-001303", - "ACH-001338", - "ACH-001344", - "ACH-001354", - "ACH-001366", - "ACH-001367", - "ACH-001481", - "ACH-001548", - "ACH-001603", - "ACH-001674", - "ACH-002080", - "ACH-002083", - "ACH-002261", - "ACH-002278", - "ACH-002280", - "ACH-002282", - "ACH-002283", - "ACH-002284", - "ACH-002285", - "ACH-002922" - ], - "hoverinfo": "text", - "marker": { - "color": "#DC587D", - "size": 7 - }, - "mode": "markers", - "name": "Neuroblastoma", - "text": [ - "Neuroblastoma | ACH-000078", - "Neuroblastoma | ACH-000099", - "Neuroblastoma | ACH-000120", - "Neuroblastoma | ACH-000149", - "Neuroblastoma | ACH-000203", - "Neuroblastoma | ACH-000227", - "Neuroblastoma | ACH-000259", - "Neuroblastoma | ACH-000260", - "Neuroblastoma | ACH-000310", - "Neuroblastoma | ACH-000312", - "Neuroblastoma | ACH-000341", - "Neuroblastoma | ACH-000366", - "Neuroblastoma | ACH-000804", - "Neuroblastoma | ACH-001188", - "Neuroblastoma | ACH-001300", - "Neuroblastoma | ACH-001301", - "Neuroblastoma | ACH-001302", - "Neuroblastoma | ACH-001303", - "Neuroblastoma | ACH-001338", - "Neuroblastoma | ACH-001344", - "Neuroblastoma | ACH-001354", - "Neuroblastoma | ACH-001366", - "Neuroblastoma | ACH-001367", - "Neuroblastoma | ACH-001481", - "Neuroblastoma | ACH-001548", - "Neuroblastoma | ACH-001603", - "Neuroblastoma | ACH-001674", - "Neuroblastoma | ACH-002080", - "Neuroblastoma | ACH-002083", - "Neuroblastoma | ACH-002261", - "Neuroblastoma | ACH-002278", - "Neuroblastoma | ACH-002280", - "Neuroblastoma | ACH-002282", - "Neuroblastoma | ACH-002283", - "Neuroblastoma | ACH-002284", - "Neuroblastoma | ACH-002285", - "Neuroblastoma | ACH-002922" - ], - "type": "scattergl", - "x": { - "bdata": "Xm9AP+mTHkDgf30/cRkuQBOtET9j7e+/VONSQHdECUAyo8W/zXc0P92s5b4Xe7E/J3ZVQN/AC0AIbixAewHfvG/VWj/d9lA+YhUnQF9Gij/zJLo/P03zPxpGHkAPO0o/qGo3PwaYoj967c8/ein1wFK5ckBl20JANbMzQCeQIUD1RA9AHxwQQFlI9cDNS6dATmspQA==", - "dtype": "f4" - }, - "y": { - "bdata": "Tdwyv8WvWL9jkEw/xtSfPux4yT46Dmu/iU95vxjGez/qCR2/DuuQv3KPlD5dFsm+9i20vs9z0z7FtJa+UDXmPiHBr743CFy+62XRv5SOnj8rH2i9zNAov8DHGr91irE/LjTvPrNHKb8QadS/BTF8vhITvT9jMm6/qDoOv2V8Rb/C9wK/MsopPzncab5VWSY/+c1Cvw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000082", - "ACH-000359", - "ACH-000364", - "ACH-000410", - "ACH-000748", - "ACH-001001", - "ACH-001526", - "ACH-001715", - "ACH-001814", - "ACH-002067", - "ACH-002069", - "ACH-002471", - "ACH-002834" - ], - "hoverinfo": "text", - "marker": { - "color": "#D626FF", - "size": 7 - }, - "mode": "markers", - "name": "Osteosarcoma", - "text": [ - "Osteosarcoma | ACH-000082", - "Osteosarcoma | ACH-000359", - "Osteosarcoma | ACH-000364", - "Osteosarcoma | ACH-000410", - "Osteosarcoma | ACH-000748", - "Osteosarcoma | ACH-001001", - "Osteosarcoma | ACH-001526", - "Osteosarcoma | ACH-001715", - "Osteosarcoma | ACH-001814", - "Osteosarcoma | ACH-002067", - "Osteosarcoma | ACH-002069", - "Osteosarcoma | ACH-002471", - "Osteosarcoma | ACH-002834" - ], - "type": "scattergl", - "x": { - "bdata": "tqkRwK0axL/2lQdA5suAPzL9DUBoBWFAiAibvjQj+b5AbcS+TBajP6qLgj9bGTQ/qo71wA==", - "dtype": "f4" - }, - "y": { - "bdata": "DXmcP+yRpz++IwNANiqXPz8gN0CgQ6y+UTChP3jguT+JYBZAHyIOP7UaIkBKmbw/SeJavg==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000086", - "ACH-000092", - "ACH-000153", - "ACH-000319", - "ACH-000331", - "ACH-000335", - "ACH-000367", - "ACH-000569", - "ACH-000645", - "ACH-000648", - "ACH-001547", - "ACH-001555", - "ACH-001556", - "ACH-001557", - "ACH-001558", - "ACH-001559", - "ACH-001560", - "ACH-001562", - "ACH-001977", - "ACH-001992", - "ACH-002033" - ], - "hoverinfo": "text", - "marker": { - "color": "#6E899C", - "size": 7 - }, - "mode": "markers", - "name": "Pleural Mesothelioma", - "text": [ - "Pleural Mesothelioma | ACH-000086", - "Pleural Mesothelioma | ACH-000092", - "Pleural Mesothelioma | ACH-000153", - "Pleural Mesothelioma | ACH-000319", - "Pleural Mesothelioma | ACH-000331", - "Pleural Mesothelioma | ACH-000335", - "Pleural Mesothelioma | ACH-000367", - "Pleural Mesothelioma | ACH-000569", - "Pleural Mesothelioma | ACH-000645", - "Pleural Mesothelioma | ACH-000648", - "Pleural Mesothelioma | ACH-001547", - "Pleural Mesothelioma | ACH-001555", - "Pleural Mesothelioma | ACH-001556", - "Pleural Mesothelioma | ACH-001557", - "Pleural Mesothelioma | ACH-001558", - "Pleural Mesothelioma | ACH-001559", - "Pleural Mesothelioma | ACH-001560", - "Pleural Mesothelioma | ACH-001562", - "Pleural Mesothelioma | ACH-001977", - "Pleural Mesothelioma | ACH-001992", - "Pleural Mesothelioma | ACH-002033" - ], - "type": "scattergl", - "x": { - "bdata": "2ScXQOObKr9EWAI97RhwPWrLlj+bpiJAO0r1wCyKjD/Vv1a/VSLXP2qhZj/GUKU/KGH4PwQKrT8UZPXACjr1wF1Z9cCEMPXAL2lJQKNGN0AXSP+/", - "dtype": "f4" - }, - "y": { - "bdata": "iK3GP9RAzz+GvQFA5HQVQF7T3j+CjLE+xWFsvs6ECT9X1Ng/Mkm/P8kNJEDVm/A/c7dRP0VMBUCxDmK+m15xvsy9bL6Ll2u+Eqv/vWZojT8f2Gs+", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000090", - "ACH-000115", - "ACH-000956", - "ACH-000977", - "ACH-000979", - "ACH-001422", - "ACH-001627", - "ACH-001648", - "ACH-001649" - ], - "hoverinfo": "text", - "marker": { - "color": "#00B5F7", - "size": 7 - }, - "mode": "markers", - "name": "Prostate Adenocarcinoma", - "text": [ - "Prostate Adenocarcinoma | ACH-000090", - "Prostate Adenocarcinoma | ACH-000115", - "Prostate Adenocarcinoma | ACH-000956", - "Prostate Adenocarcinoma | ACH-000977", - "Prostate Adenocarcinoma | ACH-000979", - "Prostate Adenocarcinoma | ACH-001422", - "Prostate Adenocarcinoma | ACH-001627", - "Prostate Adenocarcinoma | ACH-001648", - "Prostate Adenocarcinoma | ACH-001649" - ], - 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"Non-Cancerous", - "text": [ - "Non-Cancerous | ACH-000133", - "Non-Cancerous | ACH-001310", - "Non-Cancerous | ACH-001453", - "Non-Cancerous | ACH-002210", - "Non-Cancerous | ACH-002247", - "Non-Cancerous | ACH-002462", - "Non-Cancerous | ACH-002463", - "Non-Cancerous | ACH-002464", - "Non-Cancerous | ACH-002465", - "Non-Cancerous | ACH-002467" - ], - "type": "scattergl", - "x": { - "bdata": "inBOP8U49cBENfg/ORyPQFk79cBSfPXAZVn1wIes9cA3ZfXAyFT1wA==", - "dtype": "f4" - }, - "y": { - "bdata": "WREnQHe2db7Lvq8/INL9v0cbdr7rFmG+UjtjvsLDWb63JGy+lztsvg==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000141", - "ACH-001607", - "ACH-001619", - "ACH-001850", - "ACH-001861", - "ACH-001961" - ], - "hoverinfo": "text", - "marker": { - "color": "#E3EE9E", - "size": 7 - }, - "mode": "markers", - "name": "Intracholecystic Papillary Neoplasm", - "text": [ - "Intracholecystic Papillary Neoplasm | ACH-000141", - "Intracholecystic Papillary Neoplasm | ACH-001607", - "Intracholecystic Papillary Neoplasm | ACH-001619", - "Intracholecystic Papillary Neoplasm | ACH-001850", - "Intracholecystic Papillary Neoplasm | ACH-001861", - "Intracholecystic Papillary Neoplasm | ACH-001961" - ], - "type": "scattergl", - "x": { - "bdata": "ho31wPBPLkBRPsK+qDdCQGd09cDhdyVA", - "dtype": "f4" - }, - "y": { - "bdata": "CmZTvgIhHb9T5aU/vgpHPrcRZr5dMpi+", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000145", - "ACH-000505", - "ACH-002785" - ], - "hoverinfo": "text", - "marker": { - "color": "#86CE00", - "size": 7 - }, - "mode": "markers", - "name": "Leiomyosarcoma", - "text": [ - "Leiomyosarcoma | ACH-000145", - "Leiomyosarcoma | ACH-000505", - "Leiomyosarcoma | ACH-002785" - ], - "type": "scattergl", - "x": { - "bdata": "mskwv9vcwb+ghI+/", - "dtype": "f4" - }, - "y": { - "bdata": "a0XnP4YXxz+YzK4+", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000159", - "ACH-000189", - "ACH-000234", - "ACH-000246", - "ACH-000250", - "ACH-000262", - "ACH-000272", - "ACH-000313", - "ACH-000317", - "ACH-000375", - "ACH-000385", - "ACH-000411", - "ACH-000433", - "ACH-000459", - "ACH-000484", - "ACH-000495", - "ACH-000649", - "ACH-000684", - "ACH-000709", - "ACH-000792", - "ACH-000907", - "ACH-001163", - "ACH-001194", - "ACH-001398", - "ACH-001687", - "ACH-001688", - "ACH-002150", - "ACH-002189", - "ACH-002533" - ], - "hoverinfo": "text", - "marker": { - "color": "#BC7196", - "size": 7 - }, - "mode": "markers", - "name": "Renal Cell Carcinoma", - "text": [ - "Renal Cell Carcinoma | ACH-000159", - "Renal Cell Carcinoma | ACH-000189", - "Renal Cell Carcinoma | ACH-000234", - "Renal Cell Carcinoma | ACH-000246", - "Renal Cell Carcinoma | ACH-000250", - "Renal Cell Carcinoma | ACH-000262", - "Renal Cell Carcinoma | ACH-000272", - "Renal Cell Carcinoma | ACH-000313", - "Renal Cell Carcinoma | ACH-000317", - "Renal Cell Carcinoma | ACH-000375", - "Renal Cell Carcinoma | ACH-000385", - "Renal Cell Carcinoma | ACH-000411", - "Renal Cell Carcinoma | ACH-000433", - "Renal Cell Carcinoma | ACH-000459", - "Renal Cell Carcinoma | ACH-000484", - "Renal Cell Carcinoma | ACH-000495", - "Renal Cell Carcinoma | ACH-000649", - "Renal Cell Carcinoma | ACH-000684", - "Renal Cell Carcinoma | ACH-000709", - "Renal Cell Carcinoma | ACH-000792", - "Renal Cell Carcinoma | ACH-000907", - "Renal Cell Carcinoma | ACH-001163", - "Renal Cell Carcinoma | ACH-001194", - "Renal Cell Carcinoma | ACH-001398", - "Renal Cell Carcinoma | ACH-001687", - "Renal Cell Carcinoma | ACH-001688", - "Renal Cell Carcinoma | ACH-002150", - "Renal Cell Carcinoma | ACH-002189", - "Renal Cell Carcinoma | ACH-002533" - ], - "type": "scattergl", - "x": { - "bdata": "SJ0vv4Bo9cDFbNi+iVf1wGxD9cCKVfXA04b1wGoBmr9Oe/XAl+ZOQPRrnT+1NQRAL9r9PSSwlsBzjPXA4JUSPgVOG0BVBV4/x9B8vwLmyD9RTfS/W3OBPxKX9cD6TCy+Azv1wGeS9cBgSfXAhvkXwCjzVUA=", - "dtype": "f4" - }, - "y": { - "bdata": "EfAeP/DXVr7SkvU/Z5tivtGtZL4hmFe+1p5cviFWsj/q1GO+UMW9PNC9vT8zRtc/chD2P+D62b6EeGO+5J/sPz6o8z9FDBRAjsmxP5beRUADrABA1CWcv7bySL5WTu8+VcVovui+Z74FjWy+VZFzPzt0nrs=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000163", - "ACH-000181", - "ACH-000188", - "ACH-000207", - "ACH-000228", - "ACH-000238", - "ACH-000415", - "ACH-000472", - "ACH-000500", - "ACH-000503", - "ACH-000518", - "ACH-000546", - "ACH-000548", - "ACH-000549", - "ACH-000606", - "ACH-000618", - "ACH-000619", - "ACH-000630", - "ACH-000682", - "ACH-000732", - "ACH-000735", - "ACH-000740", - "ACH-000762", - "ACH-000771", - "ACH-000778", - "ACH-000794", - "ACH-000832", - "ACH-000836", - "ACH-000846", - "ACH-001228", - "ACH-001229", - "ACH-001331", - "ACH-001332", - "ACH-001346", - "ACH-001347", - "ACH-001385", - "ACH-001509", - "ACH-001510", - "ACH-001511", - "ACH-001542", - "ACH-001543", - "ACH-001625", - "ACH-001626", - "ACH-001641", - "ACH-001675", - "ACH-001690", - "ACH-001691", - "ACH-001692", - "ACH-001694", - "ACH-001695", - "ACH-001696", - "ACH-001698", - "ACH-001699", - "ACH-001701", - "ACH-002029", - "ACH-002030", - "ACH-002042", - "ACH-002043", - "ACH-002044", - "ACH-002045", - "ACH-002212", - "ACH-002249", - "ACH-002250", - "ACH-002251", - "ACH-002265", - "ACH-002294", - "ACH-002295", - "ACH-002296", - "ACH-002297", - "ACH-002298", - "ACH-002305" - ], - "hoverinfo": "text", - "marker": { - "color": "#7E7DCD", - "size": 7 - }, - "mode": "markers", - "name": "Head and Neck Squamous Cell Carcinoma", - "text": [ - "Head and Neck Squamous Cell Carcinoma | ACH-000163", - "Head and Neck Squamous Cell Carcinoma | ACH-000181", - "Head and Neck Squamous Cell Carcinoma | ACH-000188", - "Head and Neck Squamous Cell Carcinoma | ACH-000207", - "Head and Neck Squamous Cell Carcinoma | ACH-000228", - "Head and Neck Squamous Cell Carcinoma | ACH-000238", - "Head and Neck Squamous Cell Carcinoma | ACH-000415", - "Head and Neck Squamous Cell Carcinoma | ACH-000472", - "Head and Neck Squamous Cell Carcinoma | ACH-000500", - "Head and Neck Squamous Cell Carcinoma | ACH-000503", - "Head and Neck Squamous Cell Carcinoma | ACH-000518", - "Head and Neck Squamous Cell Carcinoma | ACH-000546", - "Head and Neck Squamous Cell Carcinoma | ACH-000548", - "Head and Neck Squamous Cell Carcinoma | ACH-000549", - "Head and Neck Squamous Cell Carcinoma | ACH-000606", - "Head and Neck Squamous Cell Carcinoma | ACH-000618", - "Head and Neck Squamous Cell Carcinoma | ACH-000619", - "Head and Neck Squamous Cell Carcinoma | ACH-000630", - "Head and Neck Squamous Cell Carcinoma | ACH-000682", - "Head and Neck Squamous Cell Carcinoma | ACH-000732", - "Head and Neck Squamous Cell Carcinoma | ACH-000735", - "Head and Neck Squamous Cell Carcinoma | ACH-000740", - "Head and Neck Squamous Cell Carcinoma | ACH-000762", - "Head and Neck Squamous Cell Carcinoma | ACH-000771", - "Head and Neck Squamous Cell Carcinoma | ACH-000778", - "Head and Neck Squamous Cell Carcinoma | ACH-000794", - "Head and Neck Squamous Cell Carcinoma | ACH-000832", - "Head and Neck Squamous Cell Carcinoma | ACH-000836", - "Head and Neck Squamous Cell Carcinoma | ACH-000846", - "Head and Neck Squamous Cell Carcinoma | ACH-001228", - "Head and Neck Squamous Cell Carcinoma | ACH-001229", - "Head and Neck Squamous Cell Carcinoma | ACH-001331", - "Head and Neck Squamous Cell Carcinoma | ACH-001332", - "Head and Neck Squamous Cell Carcinoma | ACH-001346", - "Head and Neck Squamous Cell Carcinoma | ACH-001347", - "Head and Neck Squamous Cell Carcinoma | ACH-001385", - "Head and Neck Squamous Cell Carcinoma | ACH-001509", - "Head and Neck Squamous Cell Carcinoma | ACH-001510", - "Head and Neck Squamous Cell Carcinoma | ACH-001511", - "Head and Neck Squamous Cell Carcinoma | ACH-001542", - "Head and Neck Squamous Cell Carcinoma | ACH-001543", - "Head and Neck Squamous Cell Carcinoma | ACH-001625", - "Head and Neck Squamous Cell Carcinoma | ACH-001626", - "Head and Neck Squamous Cell Carcinoma | ACH-001641", - "Head and Neck Squamous Cell Carcinoma | ACH-001675", - "Head and Neck Squamous Cell Carcinoma | ACH-001690", - "Head and Neck Squamous Cell Carcinoma | ACH-001691", - "Head and Neck Squamous Cell Carcinoma | ACH-001692", - "Head and Neck Squamous Cell Carcinoma | ACH-001694", - "Head and Neck Squamous Cell Carcinoma | ACH-001695", - "Head and Neck Squamous Cell Carcinoma | ACH-001696", - "Head and Neck Squamous Cell Carcinoma | ACH-001698", - "Head and Neck Squamous Cell Carcinoma | ACH-001699", - "Head and Neck Squamous Cell Carcinoma | ACH-001701", - "Head and Neck Squamous Cell Carcinoma | ACH-002029", - "Head and Neck Squamous Cell Carcinoma | ACH-002030", - "Head and Neck Squamous Cell Carcinoma | ACH-002042", - "Head and Neck Squamous Cell Carcinoma | ACH-002043", - "Head and Neck Squamous Cell Carcinoma | ACH-002044", - "Head and Neck Squamous Cell Carcinoma | ACH-002045", - "Head and Neck Squamous Cell Carcinoma | ACH-002212", - "Head and Neck Squamous Cell Carcinoma | ACH-002249", - "Head and Neck Squamous Cell Carcinoma | ACH-002250", - "Head and Neck Squamous Cell Carcinoma | ACH-002251", - "Head and Neck Squamous Cell Carcinoma | ACH-002265", - "Head and Neck Squamous Cell Carcinoma | ACH-002294", - "Head and Neck Squamous Cell Carcinoma | ACH-002295", - "Head and Neck Squamous Cell Carcinoma | ACH-002296", - "Head and Neck Squamous Cell Carcinoma | ACH-002297", - "Head and Neck Squamous Cell Carcinoma | ACH-002298", - "Head and Neck Squamous Cell Carcinoma | ACH-002305" - ], - "type": "scattergl", - "x": { - "bdata": "3LxePzs2AkDYNBZA+lL1wDlf9cD9IN0/uG/1wIUzjT5zSDg/zm/1wL7VY0Bg30tARd3qPgmFCkBcXyJA88tuQKq4XEAk+RFAveJBQNyb6T9wpwBA/t6/P7cR9j+HYvXAZ4AkvXngOUC5l5NA6XwbQASrbEAaAlG+RkHePzp19cCMePXAoyITQPDxGkDiWlxAw2eWP7UjFEDbZjU+QUqDQNjSD0Ao7yq/znubv61T9cA99f4/NslPQCzQXD+MwU9Ac0suQCLqD0AM+B1AHW8AQAuZcEA0uCVACkCAQN/ELkDscoa+Y5AjQGycc0AV2DJAuGb1wJABd0BCc4Q/ScVMQAlF9cA/rSpAiuNbP9ygjEDtAGFAF3x6QD1l9cA=", - "dtype": "f4" - }, - "y": { - "bdata": "IIstQK87yz6Cv3c/f7Nyvo6XaL5Eu+4/PpplvkNzlj8x+3M/xiFjvnB9hj/jT4E+zqRhP6GAoj4ythM/1uabvlZ9Qz+jHUhAamCrPnNhVj9Q5Jo/fvXePg67gj/vBW++COBrPwzgTz9kn0k/P5xNP9n2yryd9Pc+HwcovsHMZ757O2C+Spm8P4bKhD96w3y//TrSP1Gs/j8HzKE/J2ERP0hnmD9VAj8/aqyFPgxzbb4IZ+o/KwcvP3NoU0ArFg4/qrdPP+O/jD6PQLw/bb+5P4PYwb6IKoo+2CjJPuvg6T7avIE/COgbPokN1L/VE+M713lvvq8Zmj93MLy+OU20P7Z+e76hNpk+kjGqP2NItT4PBjI/U9/kuzeKa74=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000174", - "ACH-000191", - "ACH-001306", - "ACH-001307", - "ACH-001356", - "ACH-001443", - "ACH-002041" - ], - "hoverinfo": "text", - "marker": { - "color": "#FC6955", - "size": 7 - }, - "mode": "markers", - "name": "Anaplastic Thyroid Cancer", - "text": [ - "Anaplastic Thyroid Cancer | ACH-000174", - "Anaplastic Thyroid Cancer | ACH-000191", - "Anaplastic Thyroid Cancer | ACH-001306", - "Anaplastic Thyroid Cancer | ACH-001307", - "Anaplastic Thyroid Cancer | ACH-001356", - "Anaplastic Thyroid Cancer | ACH-001443", - "Anaplastic Thyroid Cancer | ACH-002041" - ], - "type": "scattergl", - "x": { - "bdata": "QZrQPzuE8j/0Zco+ti6Sv8VlCcC1eo4/Ds4YPw==", - "dtype": "f4" - }, - "y": { - "bdata": "vw3SP5GYyT/AZSZAp5hOP/nwk72qnaA/hGEbQA==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000182", - "ACH-000377", - "ACH-001862", - "ACH-002023" - ], - "hoverinfo": "text", - "marker": { - "color": "#E48F72", - "size": 7 - }, - "mode": "markers", - "name": "Ampullary Carcinoma", - "text": [ - "Ampullary Carcinoma | ACH-000182", - "Ampullary Carcinoma | ACH-000377", - "Ampullary Carcinoma | ACH-001862", - "Ampullary Carcinoma | ACH-002023" - ], - "type": "scattergl", - "x": { - "bdata": "okP1wF9K9cCtYQK/I6ggQA==", - "dtype": "f4" - }, - "y": { - "bdata": "+rB/vp1Rbb5jYXg+ulJgvw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000187", - "ACH-000257", - "ACH-000290", - "ACH-000292", - "ACH-000355", - "ACH-000431", - "ACH-000514", - "ACH-000515", - "ACH-000525", - "ACH-000559", - "ACH-000639", - "ACH-000695", - "ACH-000698", - "ACH-000749", - "ACH-000767", - "ACH-000775", - "ACH-000790", - "ACH-000800", - "ACH-000866", - "ACH-000871", - "ACH-000890", - "ACH-000912", - "ACH-001386", - "ACH-001549", - "ACH-002051", - "ACH-002052", - "ACH-002077" - ], - "hoverinfo": "text", - "marker": { - "color": "#2E91E5", - "size": 7 - }, - "mode": "markers", - "name": "Lung Neuroendocrine Tumor", - "text": [ - "Lung Neuroendocrine Tumor | ACH-000187", - "Lung Neuroendocrine Tumor | ACH-000257", - "Lung Neuroendocrine Tumor | ACH-000290", - "Lung Neuroendocrine Tumor | ACH-000292", - "Lung Neuroendocrine Tumor | ACH-000355", - "Lung Neuroendocrine Tumor | ACH-000431", - "Lung Neuroendocrine Tumor | ACH-000514", - "Lung Neuroendocrine Tumor | ACH-000515", - "Lung Neuroendocrine Tumor | ACH-000525", - "Lung Neuroendocrine Tumor | ACH-000559", - "Lung Neuroendocrine Tumor | ACH-000639", - "Lung Neuroendocrine Tumor | ACH-000695", - "Lung Neuroendocrine Tumor | ACH-000698", - "Lung Neuroendocrine Tumor | ACH-000749", - "Lung Neuroendocrine Tumor | ACH-000767", - "Lung Neuroendocrine Tumor | ACH-000775", - "Lung Neuroendocrine Tumor | ACH-000790", - "Lung Neuroendocrine Tumor | ACH-000800", - "Lung Neuroendocrine Tumor | ACH-000866", - "Lung Neuroendocrine Tumor | ACH-000871", - "Lung Neuroendocrine Tumor | ACH-000890", - "Lung Neuroendocrine Tumor | ACH-000912", - "Lung Neuroendocrine Tumor | ACH-001386", - "Lung Neuroendocrine Tumor | ACH-001549", - "Lung Neuroendocrine Tumor | ACH-002051", - "Lung Neuroendocrine Tumor | ACH-002052", - "Lung Neuroendocrine Tumor | ACH-002077" - ], - "type": "scattergl", - "x": { - "bdata": "v60WP1hRub4G5NQ+k1ZWQNpHVECeBZE7p+yev4/PDEBR15w/uLiAvw4kOUDpLlG/k4riPxzn6j+RSKG/inv7P39cE0BmUQBAeypAQADJOkA8Olk/LC0pQMQi3704ydE+Cgvzv96bf7/PwYa/", - "dtype": "f4" - }, - "y": { - "bdata": "iZ8pwNhWvr840gXA1OmiPhRzBr8wiW+/pfLav5u6X7/r2bG/AGiuv1SXDsDVg36/g6UewLpKa77t1/m/Ljf4vrkQoL9JjFA/cnazv12ynr8uywdAcY8HP391w79Adau/u/jKv+rm6L+rpWS/", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000192", - "ACH-000293", - "ACH-000302", - "ACH-000397", - "ACH-000407", - "ACH-000435", - "ACH-000831", - "ACH-000864", - "ACH-000879", - "ACH-000928", - "ACH-000941", - "ACH-000946", - "ACH-000961", - "ACH-000965", - "ACH-000972", - "ACH-000974", - "ACH-000978", - "ACH-000984", - "ACH-000988", - "ACH-000993", - "ACH-000994", - "ACH-000996", - "ACH-001495", - "ACH-001517", - "ACH-001518", - "ACH-002026", - "ACH-002027", - "ACH-002046" - ], - "hoverinfo": "text", - "marker": { - "color": "#E15F99", - "size": 7 - }, - "mode": "markers", - "name": "Endometrial Carcinoma", - "text": [ - "Endometrial Carcinoma | ACH-000192", - "Endometrial Carcinoma | ACH-000293", - "Endometrial Carcinoma | ACH-000302", - "Endometrial Carcinoma | ACH-000397", - "Endometrial Carcinoma | ACH-000407", - "Endometrial Carcinoma | ACH-000435", - "Endometrial Carcinoma | ACH-000831", - "Endometrial Carcinoma | ACH-000864", - "Endometrial Carcinoma | ACH-000879", - "Endometrial Carcinoma | ACH-000928", - "Endometrial Carcinoma | ACH-000941", - "Endometrial Carcinoma | ACH-000946", - "Endometrial Carcinoma | ACH-000961", - "Endometrial Carcinoma | ACH-000965", - "Endometrial Carcinoma | ACH-000972", - "Endometrial Carcinoma | ACH-000974", - "Endometrial Carcinoma | ACH-000978", - "Endometrial Carcinoma | ACH-000984", - "Endometrial Carcinoma | ACH-000988", - "Endometrial Carcinoma | ACH-000993", - "Endometrial Carcinoma | ACH-000994", - "Endometrial Carcinoma | ACH-000996", - "Endometrial Carcinoma | ACH-001495", - "Endometrial Carcinoma | ACH-001517", - "Endometrial Carcinoma | ACH-001518", - "Endometrial Carcinoma | ACH-002026", - "Endometrial Carcinoma | ACH-002027", - "Endometrial Carcinoma | ACH-002046" - ], - "type": "scattergl", - "x": { - "bdata": "Y1IewEPDAsDLISE+GpczP8fQiD82IAs+x1b1wP/pdD/V/CJAhF9KQDL5jb/V0QtAfgs4QD2jcEDKcPXAPfMxQJVcbj+yhW2/S9tOP6vEhz+CZ/XAZF3RPp0kHL8FHSjAQqf1wLxyKkD09co/oaoSPw==", - "dtype": "f4" - }, - "y": { - "bdata": 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ACH-001538", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001673", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001834", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001835", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001836", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001838", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001839", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001841", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001842", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001843", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001844", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001848", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001849", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001852", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001856", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001857", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001858", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001863", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001864", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001959", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001960", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-001997", - "Intraductal Papillary Neoplasm of the Bile Duct | ACH-002647" - ], - "type": "scattergl", - "x": { - "bdata": "8Fv1wOZT9cCSKvXAEcSSP1aw3D95UMU/N0IMQHi1RUDXfPXAu4j1wNqF9cB3e/XAl2L1wOtV9cCy9Xc/gWb1wA5o9cAmb/XAkyL1wIbubUC1DbM/IVLcP4v9E0A3jPXArScqP2TZcUAPKiNAMVT1wA5JG0A=", - "dtype": "f4" - }, - "y": { - "bdata": "vAhrvoXAYb7Oe3G+GCm8PqQLHz87R+I//cvuP3889b/jRk++TsBfvm80W77v4ma+DRdnvlkdar6qXrY/9ANkvi+Tcb4HHVy+Jv1+voETWT7hS6I/Lqy+vR57kj60gF6+zyPuvhYE1rvh3LU/Wixnvlx9gj8=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000217", - "ACH-000221", - "ACH-000316", - "ACH-000361", - 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Carcinoma | ACH-000493", - "Hepatocellular Carcinoma | ACH-000537", - "Hepatocellular Carcinoma | ACH-000577", - "Hepatocellular Carcinoma | ACH-000620", - "Hepatocellular Carcinoma | ACH-000734", - "Hepatocellular Carcinoma | ACH-000848", - "Hepatocellular Carcinoma | ACH-001318", - "Hepatocellular Carcinoma | ACH-002523" - ], - "type": "scattergl", - "x": { - "bdata": "JCnUP9pFVUBKWcw/YsavP26grL+hdeG+UjkPQJvqnj851AxAj1wSv9meQT71JyxARB9tvyHdUT+m37c//D3zv0Tloj9Z/jxA7DtEQKam9T+iDPQ/", - "dtype": "f4" - }, - "y": { - "bdata": "4f8QPtPO377vozxAypmIP/Hf6z8NK+o/y7Y+QGxPDEC7JC09weWlPgX8/D9Ey4A/KxLrP4hbDECtX8Y/uH+mP25HgL6yqTS/Bpc6vxlLVD5iA0BA", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000305", - "ACH-000318", - "ACH-000408", - "ACH-000452", - "ACH-000488", - "ACH-000544", - "ACH-000561", - "ACH-000605", - "ACH-000637", - "ACH-000647", - "ACH-000693", - "ACH-000694", - "ACH-000717", - "ACH-000777", - "ACH-000784", - "ACH-000809", - "ACH-000823", - "ACH-000824", - "ACH-000855", - "ACH-000865", - "ACH-000873", - "ACH-000917", - "ACH-002243", - "ACH-002263" - ], - "hoverinfo": "text", - "marker": { - "color": "#222A2A", - "size": 7 - }, - "mode": "markers", - "name": "Esophageal Squamous Cell Carcinoma", - "text": [ - "Esophageal Squamous Cell Carcinoma | ACH-000305", - "Esophageal Squamous Cell Carcinoma | ACH-000318", - "Esophageal Squamous Cell Carcinoma | ACH-000408", - "Esophageal Squamous Cell Carcinoma | ACH-000452", - "Esophageal Squamous Cell Carcinoma | ACH-000488", - "Esophageal Squamous Cell Carcinoma | ACH-000544", - "Esophageal Squamous Cell Carcinoma | ACH-000561", - "Esophageal Squamous Cell Carcinoma | ACH-000605", - "Esophageal Squamous Cell Carcinoma | ACH-000637", - "Esophageal Squamous Cell Carcinoma | ACH-000647", - "Esophageal Squamous Cell Carcinoma | ACH-000693", - "Esophageal Squamous Cell Carcinoma | ACH-000694", - "Esophageal Squamous Cell Carcinoma | ACH-000717", - "Esophageal Squamous Cell Carcinoma | ACH-000777", - "Esophageal 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"size": 7 - }, - "mode": "markers", - "name": "Poorly Differentiated Thyroid Cancer", - "text": [ - "Poorly Differentiated Thyroid Cancer | ACH-000456" - ], - "type": "scattergl", - "x": { - "bdata": "++dhQA==", - "dtype": "f4" - }, - "y": { - "bdata": "XXuuPw==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000487" - ], - "hoverinfo": "text", - "marker": { - "color": "#750D86", - "size": 7 - }, - "mode": "markers", - "name": "Myelodysplastic Syndromes", - "text": [ - "Myelodysplastic Syndromes | ACH-000487" - ], - "type": "scattergl", - "x": { - "bdata": "oFBoQA==", - "dtype": "f4" - }, - "y": { - "bdata": "NjIdwA==", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000490", - "ACH-000556", - "ACH-001333", - "ACH-001334", - "ACH-001335", - "ACH-001336", - "ACH-001360", - "ACH-001402", - "ACH-001451", - "ACH-001515", - "ACH-001651", - "ACH-001652", - "ACH-002020" - ], - "hoverinfo": "text", - "marker": { - "color": "#EB663B", - "size": 7 - }, - "mode": "markers", - "name": "Cervical Squamous Cell Carcinoma", - "text": [ - "Cervical Squamous Cell Carcinoma | ACH-000490", - "Cervical Squamous Cell Carcinoma | ACH-000556", - "Cervical Squamous Cell Carcinoma | ACH-001333", - "Cervical Squamous Cell Carcinoma | ACH-001334", - "Cervical Squamous Cell Carcinoma | ACH-001335", - "Cervical Squamous Cell Carcinoma | ACH-001336", - "Cervical Squamous Cell Carcinoma | ACH-001360", - "Cervical Squamous Cell Carcinoma | ACH-001402", - "Cervical Squamous Cell Carcinoma | ACH-001451", - "Cervical Squamous Cell Carcinoma | ACH-001515", - "Cervical Squamous Cell Carcinoma | ACH-001651", - "Cervical Squamous Cell Carcinoma | ACH-001652", - "Cervical Squamous Cell Carcinoma | ACH-002020" - ], - "type": "scattergl", - "x": { - "bdata": "G9QeQO3R+D4D+RpAjDFwQMwapz8gqPo/Hf14wG4wIkD+bvXAvSkaP7yMVcCMQNo/9ojwvQ==", - "dtype": "f4" - }, - "y": { - "bdata": "b62tPwI3WL9zPY8+E9FRv8p06L13UyM/mPuWv/W7j78jTnq+rBEyv0PYqr+WbX8/q8zevg==", - "dtype": "f4" - } - }, - { - 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7 - }, - "mode": "markers", - "name": "Hepatoblastoma", - "text": [ - "Hepatoblastoma | ACH-000671", - "Hepatoblastoma | ACH-000739" - ], - "type": "scattergl", - "x": { - "bdata": "J7BDQKbEJD8=", - "dtype": "f4" - }, - "y": { - "bdata": "IFlMP7wu7b4=", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000702", - "ACH-000754", - "ACH-001685" - ], - "hoverinfo": "text", - "marker": { - "color": "#FC0080", - "size": 7 - }, - "mode": "markers", - "name": "Hodgkin Lymphoma", - "text": [ - "Hodgkin Lymphoma | ACH-000702", - "Hodgkin Lymphoma | ACH-000754", - "Hodgkin Lymphoma | ACH-001685" - ], - "type": "scattergl", - "x": { - "bdata": "1m7rPl8GVT/0Uni/", - "dtype": "f4" - }, - "y": { - "bdata": "zE29vwlED8D3vgnA", - "dtype": "f4" - } - }, - { - "customdata": [ - "ACH-000716", - "ACH-000903", - "ACH-001528" - ], - "hoverinfo": "text", - "marker": { - "color": "#B2828D", - "size": 7 - }, - "mode": "markers", - "name": "Well-Differentiated Thyroid Cancer", - "text": [ - 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"lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "#6A76FC" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - } - ], - "visible": [ - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - 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"lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "#FED4C4" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - } - ], - "visible": [ - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true - ] - }, - { - "title": "PCA Highlighted: Extra Gonadal Germ Cell Tumor" - } - ], - "label": "Extra Gonadal Germ Cell Tumor", - "method": "update" - }, - { - "args": [ - { - "marker": [ - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": 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"lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "#FE00CE" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - } - ], - "visible": [ - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true - ] - }, - { - "title": "PCA Highlighted: Chordoma" - } - ], - "label": "Chordoma", - "method": "update" - }, - { - "args": [ - { - "marker": [ - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "#0DF9FF" - }, - { - "color": "lightgrey" - } - ], - "visible": [ - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true - ] - }, - { - "title": "PCA Highlighted: Head and Neck Carcinoma, Other" - } - ], - "label": "Head and Neck Carcinoma, Other", - "method": "update" - }, - { - "args": [ - { - "marker": [ - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "lightgrey" - }, - { - "color": "#F6F926" - } - ], - "visible": [ - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true, - true - ] - }, - { - "title": "PCA Highlighted: Salivary Carcinoma" - } - ], - "label": "Salivary Carcinoma", - "method": "update" - } - ], - "direction": "down", - "showactive": true, - "x": 1.15, - "xanchor": "left", - "y": 1.15, - "yanchor": "top" - } - ], - "width": 1500, - "xaxis": { - "title": { - "text": "PCA1" - } - }, - "yaxis": { - "title": { - "text": "PCA2" - } - } - } - } - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "92e3889c12d5473f886a52d78b22ca39", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Output()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Assuming combined_df is your full dataset\n", - "reactome_fig, reactome_out = make_dropdown_pca_with_selection(\n", - " reactome_matrix, \"PCA: Reactome Subset\"\n", - ")\n", - "corum_fig, corum_out = make_dropdown_pca_with_selection(\n", - " corum_matrix, \"PCA: CORUM Subset\"\n", - ")\n", - "drug_fig, drug_out = make_dropdown_pca_with_selection(drug_matrix, \"PCA: Drug Subset\")\n", - "\n", - "# Show plots\n", - "reactome_fig.show()\n", - "display(reactome_out)\n", - "\n", - "corum_fig.show()\n", - "display(corum_out)\n", - "\n", - "drug_fig.show()\n", - "display(drug_out)\n", - "\n", - "# Save HTMLs\n", - "reactome_fig.write_html(\"pca_reactome.html\")\n", - "corum_fig.write_html(\"pca_corum.html\")\n", - "drug_fig.write_html(\"pca_drug.html\")" - ] - }, - { - "cell_type": "markdown", - "id": "d65a9394", - "metadata": {}, - "source": [ - "## spider plots" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "529ca84c", - "metadata": {}, - "outputs": [], - "source": [ - "import textwrap\n", - "\n", - "import matplotlib.pyplot as plt\n", - "import numpy as np\n", - "import pandas as pd" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "id": "3a41344d", - "metadata": {}, - "outputs": [], - "source": [ - "model_ids = [\"ACH-000323\", \"ACH-002083\", \"ACH-002228\", \"ACH-000001\"]\n", - "files = {\n", - " \"Reactome Pathways\": \"../5.drug-dependency/results/all_reactome_results.parquet\",\n", - " \"CORUM Complexes\": \"../5.drug-dependency/results/all_corum_results.parquet\",\n", - " \"Drug Responses\": \"../5.drug-dependency/results/all_drug_results.parquet\",\n", - "}\n", - "# Adjust these if your column names differ\n", - "feature_colnames = {\n", - " \"Reactome Pathways\": \"reactome_pathway\",\n", - " \"CORUM Complexes\": \"reactome_pathway\",\n", - " \"Drug Responses\": \"name\",\n", - "}\n", - "score_col = \"pathway_score\"\n", - "\n", - "model_colors = {\n", - " \"ACH-000323\": \"#00FFFF\", # cyan\n", - " \"ACH-002083\": \"#FF69B4\", # pink\n", - " \"ACH-002228\": \"#800080\", # purple\n", - " \"ACH-000001\": \"#FFA500\", # orange\n", - "}" - ] - }, - { - "cell_type": "code", - "execution_count": 42, - "id": "aa291f2e", - "metadata": {}, - "outputs": [], - "source": [ - "def clean_label(x: str) -> str:\n", - " \"\"\"\n", - " Clean or override specific long labels before truncation.\n", - " \"\"\"\n", - " # Polymerase switching\n", - " if \"Polymerase Switching\" in x:\n", - " return \"Polymerase Switching\"\n", - "\n", - " # Negative MET regulation\n", - " if \"Negative Regulation Of MET\" in x or \"Negative Regulation of MET\" in x:\n", - " return \"Negative MET Regulation\"\n", - "\n", - " return truncate_label(x)\n", - "\n", - "\n", - "def truncate_label(\n", - " label: str,\n", - " max_chars_per_line: int = 22,\n", - " max_total_words: int = 4,\n", - " max_lines: int = 2,\n", - ") -> str:\n", - " \"\"\"\n", - " Truncate a label according to character and line limits.\n", - " \"\"\"\n", - " words = label.split()\n", - " short = \" \".join(words[:max_total_words])\n", - "\n", - " # Wrap\n", - " lines = textwrap.wrap(short, width=max_chars_per_line)\n", - "\n", - " # clamp to max lines\n", - " if len(lines) > max_lines:\n", - " lines = lines[:max_lines]\n", - "\n", - " wrapped = \"\\n\".join(lines)\n", - "\n", - " # Determine if truncated\n", - " if len(words) > max_total_words or (\n", - " len(lines) >= max_lines\n", - " and len(lines) < len(textwrap.wrap(short, width=max_chars_per_line))\n", - " ):\n", - " wrapped += \"...\"\n", - "\n", - " return wrapped\n", - "\n", - "\n", - "def place_labels_polar(ax, angles, labels, radius: float) -> None:\n", - " \"\"\"\n", - " Place labels around a polar plot at a given radius.\n", - " \"\"\"\n", - " for angle, label in zip(angles[:-1], labels):\n", - " r = radius\n", - "\n", - " # left / right alignment\n", - " if 0 <= angle <= np.pi / 2 or 3 * np.pi / 2 <= angle <= 2 * np.pi:\n", - " ha = \"left\"\n", - " else:\n", - " ha = \"right\"\n", - "\n", - " ax.text(\n", - " angle, r, label, fontsize=9, color=\"black\", ha=ha, va=\"center\", wrap=True\n", - " )\n", - "\n", - " return None\n", - "\n", - "\n", - "def make_radar(\n", - " ax,\n", - " df: pd.DataFrame,\n", - " feature_col: str,\n", - " title: str,\n", - " global_max: float,\n", - " score_col: str = \"pathway_score\",\n", - " model_ids: list = [\"ACH-000323\", \"ACH-002083\", \"ACH-002228\"],\n", - " num_circles: int = 5,\n", - ") -> None:\n", - " \"\"\"\n", - " Draw a radar plot on an existing polar matplotlib axis.\n", - " \"\"\"\n", - " if model_ids == [\"ACH-000323\", \"ACH-002083\", \"ACH-002228\"]:\n", - " model_colors = {\n", - " \"ACH-000323\": \"#00FFFF\", # cyan\n", - " \"ACH-002083\": \"#FF69B4\", # pink\n", - " \"ACH-002228\": \"#800080\", # purple\n", - " }\n", - " else:\n", - " model_colors = generate_model_color_map(model_ids, seed=12)\n", - "\n", - " # Top 5 per model, union of all\n", - " top_by_model = (\n", - " df.groupby(\"ModelID\", group_keys=False)\n", - " .apply(lambda x: x.nlargest(5, score_col))\n", - " .reset_index(drop=True)\n", - " )\n", - " top_features = top_by_model[feature_col].drop_duplicates().tolist()\n", - " n_vars = len(top_features)\n", - " labels = [clean_label(x) for x in top_features]\n", - "\n", - " # Angles\n", - " angles = np.linspace(0, 2 * np.pi, n_vars, endpoint=False).tolist()\n", - " angles += [angles[0]]\n", - "\n", - " # Reference circles\n", - " circle_levels = np.linspace(0, global_max, num_circles + 1)[1:]\n", - " for r in circle_levels:\n", - " circle_vals = [r] * (n_vars + 1)\n", - " ax.plot(\n", - " angles, circle_vals, color=\"grey\", linestyle=\"--\", linewidth=1, zorder=0\n", - " )\n", - " # Plot each model\n", - " for mid in model_ids:\n", - " subset = df[df[\"ModelID\"] == mid]\n", - "\n", - " merged = pd.DataFrame({feature_col: top_features}).merge(\n", - " subset[[feature_col, score_col]], on=feature_col, how=\"left\"\n", - " )\n", - "\n", - " values = merged[score_col].fillna(0).tolist()\n", - " values += [values[0]]\n", - "\n", - " ax.plot(angles, values, color=model_colors[mid], linewidth=3, label=mid)\n", - " ax.scatter(\n", - " angles, values, color=model_colors[mid], s=30, edgecolor=\"black\", zorder=5\n", - " )\n", - "\n", - " # Axis styling\n", - " ax.set_ylim(0, global_max * 1.25)\n", - " ax.set_xticks([])\n", - " ax.set_yticks([])\n", - " ax.set_aspect(\"equal\")\n", - "\n", - " # Labels\n", - " label_radius = global_max * 1.4\n", - " place_labels_polar(ax, angles, labels, label_radius)\n", - "\n", - " # Title\n", - " ax.set_title(title, fontsize=18, pad=30, fontweight=\"bold\", y=1)\n", - "\n", - " return None\n", - "\n", - "\n", - "def generate_model_color_map(model_ids, seed=12):\n", - " colors = generate_random_palette(len(model_ids), seed)\n", - " return {model_id: color for model_id, color in zip(model_ids, colors)}" - ] - }, - { - "cell_type": "code", - "execution_count": 43, - "id": "dd6645ac", - "metadata": {}, - "outputs": [], - "source": [ - "global_max = 0\n", - "dfs = {}\n", - "for name, file in files.items():\n", - " df = pd.read_parquet(file)\n", - " dfs[name] = df\n", - " if df[score_col].max() > global_max:\n", - " global_max = df[score_col].max()" - ] - }, - { - "cell_type": "code", - "execution_count": 47, - "id": "36779957", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'name'" - ] - }, - "execution_count": 47, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "cols" - ] - }, - { - "cell_type": "code", - "execution_count": 46, - "id": "81e8b00c", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
    " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "max_processes = 3\n", - "# --- Create one combined figure ---\n", - "fig, axes = plt.subplots(3, 1, figsize=(18, 12), subplot_kw=dict(polar=True))\n", - "\n", - "for ax, (title, df) in zip(axes, dfs.items()):\n", - " df = df[df[\"ModelID\"].isin(model_ids)].copy()\n", - "\n", - " # Apply process limit if set\n", - " cols = feature_colnames[title]\n", - " # if max_processes is not None:\n", - " # cols = cols[:max_processes]\n", - "\n", - " make_radar(ax, df, cols, title, global_max, model_ids=model_ids)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d206f528", - "metadata": {}, - "outputs": [], - "source": [ - "# Shared legend (one for all)\n", - "handles, labels = axes[0].get_legend_handles_labels()\n", - "\n", - "fig.legend(\n", - " handles,\n", - " labels,\n", - " loc=\"lower center\",\n", - " ncol=3,\n", - " fontsize=12,\n", - " frameon=False,\n", - " bbox_to_anchor=(0.5, -0.05),\n", - ")\n", - "\n", - "plt.tight_layout(rect=[0, 0, 1, 0.95])\n", - "# plt.savefig(\"visualize/combined_radar_plots.png\", dpi=600,\n", - "# bbox_inches=\"tight\", transparent=True)\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "34752035", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "id": "8e416fd5", - "metadata": {}, - "source": [ - "## testing" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "1529353d", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[(0.25660503201582907, 0.9323619711728774, 0.8292577291672704),\n", - " (0.3484708479375381, 0.3074749658243011, 0.0645616837705435),\n", - " (0.6096646070080306, 0.9514553535026719, 0.4209623091794289)]" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model_colors = generate_random_palette(len(model_ids), seed=12)\n", - "model_colors" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "a0b3b2e7", - "metadata": {}, - "outputs": [ - { - "ename": "TypeError", - "evalue": "list indices must be integers or slices, not str", - "output_type": "error", - "traceback": [ - "\u001b[31m---------------------------------------------------------------------------\u001b[39m", - "\u001b[31mTypeError\u001b[39m Traceback (most recent call last)", - "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[4]\u001b[39m\u001b[32m, line 40\u001b[39m\n\u001b[32m 36\u001b[39m subplot_kw=dict(polar=\u001b[38;5;28;01mTrue\u001b[39;00m))\n\u001b[32m 37\u001b[39m \n\u001b[32m 38\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m ax, (title, df) \u001b[38;5;28;01min\u001b[39;00m zip(axes, dfs.items()):\n\u001b[32m 39\u001b[39m df = df[df[\u001b[33m\"ModelID\"\u001b[39m].isin(model_ids)].copy()\n\u001b[32m---> \u001b[39m\u001b[32m40\u001b[39m make_radar(ax, df, feature_colnames[title], title, global_max)\n\u001b[32m 41\u001b[39m \n\u001b[32m 42\u001b[39m \u001b[38;5;66;03m# Shared legend (one for all)\u001b[39;00m\n\u001b[32m 43\u001b[39m handles, labels = axes[\u001b[32m0\u001b[39m].get_legend_handles_labels()\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/gene-process-dependencies/9.webapp/app_utils.py:150\u001b[39m, in \u001b[36mmake_radar\u001b[39m\u001b[34m(ax, df, feature_col, title, global_max, score_col, model_ids, num_circles)\u001b[39m\n\u001b[32m 147\u001b[39m values = merged[score_col].fillna(\u001b[32m0\u001b[39m).tolist()\n\u001b[32m 148\u001b[39m values += [values[\u001b[32m0\u001b[39m]]\n\u001b[32m--> \u001b[39m\u001b[32m150\u001b[39m ax.plot(angles, values, color=\u001b[30;43mmodel_colors\u001b[39;49m\u001b[30;43m[\u001b[39;49m\u001b[30;43mmid\u001b[39;49m\u001b[30;43m]\u001b[39;49m,\n\u001b[32m 151\u001b[39m linewidth=\u001b[32m3\u001b[39m, label=mid)\n\u001b[32m 152\u001b[39m ax.scatter(angles, values, color=model_colors[mid],\n\u001b[32m 153\u001b[39m s=\u001b[32m30\u001b[39m, edgecolor=\u001b[33m\"\u001b[39m\u001b[33mblack\u001b[39m\u001b[33m\"\u001b[39m, zorder=\u001b[32m5\u001b[39m)\n\u001b[32m 155\u001b[39m \u001b[38;5;66;03m# Axis styling\u001b[39;00m\n", - "\u001b[31mTypeError\u001b[39m: list indices must be integers or slices, not str" - ] - }, - { - "data": { - "image/png": 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", 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    " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import textwrap\n", - "\n", - "import matplotlib.pyplot as plt\n", - "import numpy as np\n", - "import pandas as pd\n", - "from app_utils import (\n", - " clean_label,\n", - " generate_random_palette,\n", - " make_radar,\n", - " place_labels_polar,\n", - " truncate_label,\n", - ")\n", - "\n", - "model_ids = [\"ACH-000323\", \"ACH-002083\", \"ACH-002228\"]\n", - "files = {\n", - " \"Reactome Pathways\": \"../5.drug-dependency/results/all_reactome_results.parquet\",\n", - " \"CORUM Complexes\": \"../5.drug-dependency/results/all_corum_results.parquet\",\n", - " \"Drug Responses\": \"../5.drug-dependency/results/all_drug_results.parquet\",\n", - "}\n", - "# Adjust these if your column names differ\n", - "feature_colnames = {\n", - " \"Reactome Pathways\": \"reactome_pathway\",\n", - " \"CORUM Complexes\": \"reactome_pathway\",\n", - " \"Drug Responses\": \"name\",\n", - "}\n", - "score_col = \"pathway_score\"\n", - "\n", - "model_colors = {\n", - " \"ACH-000323\": \"#00FFFF\", # cyan\n", - " \"ACH-002083\": \"#FF69B4\", # pink\n", - " \"ACH-002228\": \"#800080\", # purple\n", - "}\n", - "\n", - "global_max = 0\n", - "dfs = {}\n", - "for name, file in files.items():\n", - " df = pd.read_parquet(file)\n", - " dfs[name] = df\n", - " if df[score_col].max() > global_max:\n", - " global_max = df[score_col].max()\n", - "\n", - "# --- Create one combined figure ---\n", - "fig, axes = plt.subplots(3, 1, figsize=(18, 12), subplot_kw=dict(polar=True))\n", - "\n", - "for ax, (title, df) in zip(axes, dfs.items()):\n", - " df = df[df[\"ModelID\"].isin(model_ids)].copy()\n", - " make_radar(ax, df, feature_colnames[title], title, global_max)\n", - "\n", - "# Shared legend (one for all)\n", - "handles, labels = axes[0].get_legend_handles_labels()\n", - "\n", - "fig.legend(\n", - " handles,\n", - " labels,\n", - " loc=\"lower center\",\n", - " ncol=3,\n", - " fontsize=12,\n", - " frameon=False,\n", - " bbox_to_anchor=(0.5, -0.05),\n", - ")\n", - "\n", - "plt.tight_layout(rect=[0, 0, 1, 0.95])\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "dfca7abf", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
    \n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
    Primary DiseaseModelID
    0Acute Myeloid LeukemiaACH-000004
    1Acute Myeloid LeukemiaACH-000005
    2Acute Myeloid LeukemiaACH-000045
    3Acute Myeloid LeukemiaACH-000113
    4Acute Myeloid LeukemiaACH-000146
    .........
    1145Uterine Sarcoma/MesenchymalACH-000939
    1146Uterine Sarcoma/MesenchymalACH-001655
    1147Well-Differentiated Thyroid CancerACH-000716
    1148Well-Differentiated Thyroid CancerACH-000903
    1149Well-Differentiated Thyroid CancerACH-001528
    \n", - "

    1150 rows × 2 columns

    \n", - "
    " - ], - "text/plain": [ - " Primary Disease ModelID\n", - "0 Acute Myeloid Leukemia ACH-000004\n", - "1 Acute Myeloid Leukemia ACH-000005\n", - "2 Acute Myeloid Leukemia ACH-000045\n", - "3 Acute Myeloid Leukemia ACH-000113\n", - "4 Acute Myeloid Leukemia ACH-000146\n", - "... ... ...\n", - "1145 Uterine Sarcoma/Mesenchymal ACH-000939\n", - "1146 Uterine Sarcoma/Mesenchymal ACH-001655\n", - "1147 Well-Differentiated Thyroid Cancer ACH-000716\n", - "1148 Well-Differentiated Thyroid Cancer ACH-000903\n", - "1149 Well-Differentiated Thyroid Cancer ACH-001528\n", - "\n", - "[1150 rows x 2 columns]" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import pandas as pd\n", - "from app_utils import latent_load_data\n", - "\n", - "selected_diseases = [\n", - " \"Lung Adenocarcinoma\",\n", - " \"Lung Squamous Cell Carcinoma\",\n", - " \"Small Cell Lung Carcinoma\",\n", - " \"Colorectal Adenocarcinoma\",\n", - " \"Pancreatic Adenocarcinoma\",\n", - " \"Ovarian Serous Cystadenocarcinoma\",\n", - " \"Glioblastoma Multiforme\",\n", - " \"Skin Cutaneous Melanoma\",\n", - " \"Uterine Corpus Endometrial Carcinoma\",\n", - " \"Prostate Adenocarcinoma\",\n", - "]\n", - "reactome_matrix, corum_matrix, drug_matrix = latent_load_data()\n", - "full_df = reactome_matrix[\n", - " reactome_matrix[\"OncotreePrimaryDisease\"].isin(selected_diseases)\n", - "]\n", - "\n", - "# Build summary: one row per unique (OncotreeLineage, OncotreePrimaryDisease) pair\n", - "# adjust column names below to match whatever lineage/cancer-type column your data actually has\n", - "group_cols = [\"OncotreePrimaryDisease\", \"ModelID\"] # ← rename if needed\n", - "summary = (\n", - " reactome_matrix.groupby(group_cols, dropna=False)\n", - " .agg(n_models=(\"ModelID\", \"nunique\"))\n", - " .reset_index()\n", - " .sort_values(group_cols)\n", - " .rename(\n", - " columns={\n", - " \"OncotreeLineage\": \"Lineage / Cancer Type\",\n", - " \"OncotreePrimaryDisease\": \"Primary Disease\",\n", - " \"n_models\": \"Cell Lines\",\n", - " }\n", - " )\n", - " .drop(columns=[\"Cell Lines\"])\n", - " .drop_duplicates()\n", - ")\n", - "summary" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "810f449e", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": ".venv (3.13.1)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.13.1" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} From fa10bfa9b711d67150cd49010ae9837989f9af0b Mon Sep 17 00:00:00 2001 From: MikeLippincott <1michaell2017@gmail.com> Date: Mon, 8 Jun 2026 19:05:27 -0600 Subject: [PATCH 04/25] add new webapp --- .gitignore | 1 + 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+++++++++++++++++++++++++----------------------- 1 file changed, 75 insertions(+), 69 deletions(-) diff --git a/9.webapp/app.py b/9.webapp/app.py index 574024a..097f7d1 100644 --- a/9.webapp/app.py +++ b/9.webapp/app.py @@ -213,57 +213,59 @@ def model_id_controls(key_prefix: str) -> list[str]: st.markdown('
    ', unsafe_allow_html=True) selected_diseases_single = disease_controls("single") st.markdown("
    ", unsafe_allow_html=True) - - combined_df = single_load_data() - combined_df = combined_df[ - combined_df["OncotreePrimaryDisease"].isin(selected_diseases_single) - ] - - gene_cols = combined_df.columns.drop(["ModelID", "OncotreePrimaryDisease"]) - pca_input = combined_df[gene_cols].apply(pd.to_numeric, errors="coerce") - pca = PCA(n_components=2, random_state=0) - pca_embedding = pca.fit_transform(pca_input) - combined_df["PCA1"] = pca_embedding[:, 0] - combined_df["PCA2"] = pca_embedding[:, 1] - - cancer_types = combined_df["OncotreePrimaryDisease"].unique() - color_map = ( - px.colors.qualitative.Plotly - + px.colors.qualitative.Light24 - + px.colors.qualitative.Dark24 - ) - highlight_color_map = { - c: color_map[i % len(color_map)] for i, c in enumerate(cancer_types) - } - - traces = [] - for cancer in cancer_types: - df_sub = combined_df[combined_df["OncotreePrimaryDisease"] == cancer] - traces.append( - go.Scatter( - x=df_sub["PCA1"], - y=df_sub["PCA2"], - mode="markers", - name=cancer, - marker=dict(size=7, color=highlight_color_map[cancer]), - text=[f"{cancer} | {m}" for m in df_sub["ModelID"]], - hoverinfo="text", - ) + if len(selected_diseases_single) == 0: + st.warning("Please select at least one primary disease to display the plot.") + else: + combined_df = single_load_data() + combined_df = combined_df[ + combined_df["OncotreePrimaryDisease"].isin(selected_diseases_single) + ] + + gene_cols = combined_df.columns.drop(["ModelID", "OncotreePrimaryDisease"]) + pca_input = combined_df[gene_cols].apply(pd.to_numeric, errors="coerce") + pca = PCA(n_components=2, random_state=0) + pca_embedding = pca.fit_transform(pca_input) + combined_df["PCA1"] = pca_embedding[:, 0] + combined_df["PCA2"] = pca_embedding[:, 1] + + cancer_types = combined_df["OncotreePrimaryDisease"].unique() + color_map = ( + px.colors.qualitative.Plotly + + px.colors.qualitative.Light24 + + px.colors.qualitative.Dark24 ) + highlight_color_map = { + c: color_map[i % len(color_map)] for i, c in enumerate(cancer_types) + } + + traces = [] + for cancer in cancer_types: + df_sub = combined_df[combined_df["OncotreePrimaryDisease"] == cancer] + traces.append( + go.Scatter( + x=df_sub["PCA1"], + y=df_sub["PCA2"], + mode="markers", + name=cancer, + marker=dict(size=7, color=highlight_color_map[cancer]), + text=[f"{cancer} | {m}" for m in df_sub["ModelID"]], + hoverinfo="text", + ) + ) - fig_single = go.Figure(data=traces) - fig_single.update_layout( - paper_bgcolor="#0d1117", - plot_bgcolor="#0d1117", - font=dict(color="#e6edf3"), - xaxis=dict(gridcolor="#21262d"), - yaxis=dict(gridcolor="#21262d"), - legend=dict(bgcolor="#161b22", bordercolor="#30363d", borderwidth=1), - height=1200, - margin=dict(l=40, r=40, t=40, b=40), - width=800, - ) - st.plotly_chart(fig_single, use_container_width=True) + fig_single = go.Figure(data=traces) + fig_single.update_layout( + paper_bgcolor="#0d1117", + plot_bgcolor="#0d1117", + font=dict(color="#e6edf3"), + xaxis=dict(gridcolor="#21262d"), + yaxis=dict(gridcolor="#21262d"), + legend=dict(bgcolor="#161b22", bordercolor="#30363d", borderwidth=1), + height=1200, + margin=dict(l=40, r=40, t=40, b=40), + width=800, + ) + st.plotly_chart(fig_single, use_container_width=True) # ───────────────────────────────────────────────────────────────────────────── @@ -280,27 +282,31 @@ def model_id_controls(key_prefix: str) -> list[str]: st.markdown('
    ', unsafe_allow_html=True) selected_diseases_latent = disease_controls("latent") st.markdown("
    ", unsafe_allow_html=True) + if len(selected_diseases_single) == 0: + st.warning("Please select at least one primary disease to display the plot.") + else: + reactome_matrix, corum_matrix, drug_matrix = latent_load_data() + reactome_matrix = reactome_matrix[ + reactome_matrix["OncotreePrimaryDisease"].isin(selected_diseases_latent) + ] + corum_matrix = corum_matrix[ + corum_matrix["OncotreePrimaryDisease"].isin(selected_diseases_latent) + ] + drug_matrix = drug_matrix[ + drug_matrix["OncotreePrimaryDisease"].isin(selected_diseases_latent) + ] + + reactome_fig, _ = make_dropdown_pca_with_selection( + reactome_matrix, "PCA: Reactome Subset" + ) + corum_fig, _ = make_dropdown_pca_with_selection( + corum_matrix, "PCA: CORUM Subset" + ) + drug_fig, _ = make_dropdown_pca_with_selection(drug_matrix, "PCA: Drug Subset") - reactome_matrix, corum_matrix, drug_matrix = latent_load_data() - reactome_matrix = reactome_matrix[ - reactome_matrix["OncotreePrimaryDisease"].isin(selected_diseases_latent) - ] - corum_matrix = corum_matrix[ - corum_matrix["OncotreePrimaryDisease"].isin(selected_diseases_latent) - ] - drug_matrix = drug_matrix[ - drug_matrix["OncotreePrimaryDisease"].isin(selected_diseases_latent) - ] - - reactome_fig, _ = make_dropdown_pca_with_selection( - reactome_matrix, "PCA: Reactome Subset" - ) - corum_fig, _ = make_dropdown_pca_with_selection(corum_matrix, "PCA: CORUM Subset") - drug_fig, _ = make_dropdown_pca_with_selection(drug_matrix, "PCA: Drug Subset") - - st.plotly_chart(reactome_fig, use_container_width=True) - st.plotly_chart(corum_fig, use_container_width=True) - st.plotly_chart(drug_fig, use_container_width=True) + st.plotly_chart(reactome_fig, use_container_width=True) + st.plotly_chart(corum_fig, use_container_width=True) + st.plotly_chart(drug_fig, use_container_width=True) # ───────────────────────────────────────────────────────────────────────────── From df7e22ed8a2bacb565fb78af59d44ea72de2701b Mon Sep 17 00:00:00 2001 From: MikeLippincott <1michaell2017@gmail.com> Date: Mon, 8 Jun 2026 19:31:27 -0600 Subject: [PATCH 06/25] track file --- .gitattributes | 1 + .gitignore | 1 - 0.data-download/data/Model.parquet | Bin 192916 -> 0 bytes 0.data-download/download_data.sh | 7 +- 0.data-download/scripts/1.data_downloader.py | 61 +++++++++++++-- .../scripts/2.construct_gene_dictionary.py | 72 ++++++++---------- 9.webapp/app_utils.py | 10 +-- 9.webapp/data/CRISPRGeneEffect.parquet | 3 + 9.webapp/data/CRISPR_gene_dictionary.parquet | 3 + 9.webapp/data/Model.parquet | 3 + 10 files changed, 107 insertions(+), 54 deletions(-) create mode 100644 .gitattributes delete mode 100644 0.data-download/data/Model.parquet create mode 100644 9.webapp/data/CRISPRGeneEffect.parquet create mode 100644 9.webapp/data/CRISPR_gene_dictionary.parquet create mode 100644 9.webapp/data/Model.parquet diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 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Sparse dictionary learning recovers pleiotropy from human cell fitness screens. Cell Syst. 2022 Apr 20;13(4):286-303.e10. doi: 10.1016/j.cels.2021.12.005. Epub 2022 Jan 31. PMID: 35085500; PMCID: PMC9035054. +# +# >Tsherniak A, Vazquez F, Montgomery PG, Weir BA, Kryukov G, Cowley GS, Gill S, Harrington WF, Pantel S, Krill-Burger JM, Meyers RM, Ali L, Goodale A, Lee Y, Jiang G, Hsiao J, Gerath WFJ, Howell S, Merkel E, Ghandi M, Garraway LA, Root DE, Golub TR, Boehm JS, Hahn WC. Defining a Cancer Dependency Map. Cell. 2017 Jul 27;170(3):564-576. # In[1]: import pathlib import urllib.request +from pathlib import Path +import pandas as pd +import pyarrow as pa # In[2]: @@ -37,10 +40,11 @@ def download_dependency_data(figshare_id, figshare_url, output_file): figshare_url = "https://ndownloader.figshare.com/files/" download_dict = { - "40448549": "CRISPRGeneDependency.parquet", - "40448555": "CRISPRGeneEffect.parquet", - "40448834": "Model.parquet", - "29094531": "depmap_gene_meta.tsv", # Data from Pan et al. 2022 + "46489732": "Model.csv", + "46489063": "CRISPRGeneEffect_Uncorrected.csv", + "46489021": "CRISPRGeneDependency.csv", + "29094531": "depmap_gene_meta.tsv", + # DepMap, Broad (2024). DepMap 24Q2 Public. Figshare+. Dataset. https://doi.org/10.25452/figshare.plus.25880521.v1 } @@ -65,3 +69,44 @@ def download_dependency_data(figshare_id, figshare_url, output_file): figshare_id=figshare_id, figshare_url=figshare_url, output_file=output_file ) + +# In[6]: + + +# Column name correction for CRISPRGeneEffect +df = pd.read_csv("../0.data-download/data/CRISPRGeneEffect_Uncorrected.csv") +df = df.rename(columns={df.columns[0]: "ModelID"}) +filepath = Path("../0.data-download/data/CRISPRGeneEffect.csv") +filepath.parent.mkdir(parents=True, exist_ok=True) + +df.to_csv(filepath, index=False) + + +# In[7]: + + +# Convert to parquet +# List of CSV files + +data_directory = "../0.data-download/data/" +model_file = pathlib.Path(data_directory, "Model.csv").resolve() +effect_data_file = pathlib.Path(data_directory, "CRISPRGeneEffect.csv").resolve() +dependency_file = pathlib.Path(data_directory, "CRISPRGeneDependency.csv").resolve() +metadata_file = pathlib.Path(data_directory, "depmap_gene_meta.tsv").resolve() + +csv_files = [model_file, effect_data_file, dependency_file] + +# Convert each CSV to Parquet +for csv_file in csv_files: + # Read the CSV file + df = pd.read_csv(csv_file) + + # Define the output Parquet file name + parquet_file = csv_file.with_suffix(".parquet") + + # Save the DataFrame as a Parquet file + df.to_parquet(parquet_file, index=False) + +meta_df = pd.read_csv(metadata_file, sep="\t") +meta_parquet = metadata_file.with_suffix(".parquet") +meta_df.to_parquet(meta_parquet, index=False) diff --git a/0.data-download/scripts/2.construct_gene_dictionary.py b/0.data-download/scripts/2.construct_gene_dictionary.py index c3806d9..6fc7019 100644 --- a/0.data-download/scripts/2.construct_gene_dictionary.py +++ b/0.data-download/scripts/2.construct_gene_dictionary.py @@ -2,25 +2,25 @@ # coding: utf-8 # ## Construct gene dictionary -# +# # The column names of the gene dependency files are of the format "gene symbol (entrez id)". -# +# # Additionally, the `depmap_gene_meta.tsv` contains genes that passed an initial QC (see Pan et al. 2022). -# +# # This notebook will create a six column matrix that separates symbol from entrez id, retains the original column name, two columns of if the gene passed two different QC, and a QC summary column. -# +# # Example: -# +# # | entrez_id | symbol_id | dependency_column | qc_pass_pan | qc_pass_other | qc_pass | # | :-------: | :-------: | :---------------: | :---------: | :-----------: | :-----: | # | 1 | A1BG |A1BG (1)| True | True | True | # | 29974 | A1CF | A1CF (29974) | True | False | False | # | 2 | A2M | A2M (2) | False | True | False | -# +# # *Note, the example qc_pass column above is an example and may not reflect truth.* -# +# # ### Quality control columns -# +# # - `qc_pass_pan` refers to the genes QC'd by Pan et al. 2022 # - `qc_pass_other` refers to gene families filtered by saturated signals # - RPL - Ribosomal proteins (including mitochondrial) @@ -31,8 +31,8 @@ import pathlib -import pandas as pd +import pandas as pd # In[2]: @@ -42,14 +42,14 @@ dependency_file = pathlib.Path(f"{base_dir}/CRISPRGeneEffect.parquet") qc_gene_file = pathlib.Path(f"{base_dir}/depmap_gene_meta.tsv") -output_gene_dict_file = pathlib.Path(f"{base_dir}/CRISPR_gene_dictionary.tsv") +output_gene_dict_file = pathlib.Path(f"{base_dir}/CRISPR_gene_dictionary.parquet") # In[3]: # Load gene dependency data -dependency_df = pd.read_parquet(dependency_file, index_col=0) +dependency_df = pd.read_parquet(dependency_file) print(dependency_df.shape) dependency_df.head() @@ -59,7 +59,7 @@ # Load depmap metadata -gene_meta_df = pd.read_parquet(qc_gene_file, sep="\t") +gene_meta_df = pd.read_csv(qc_gene_file, sep="\t") gene_meta_df.entrezgene = gene_meta_df.entrezgene.astype(str) print(gene_meta_df.shape) @@ -67,26 +67,25 @@ # ## Obtain the intersection of the genes -# +# # Comparing the current DepMap release and the previous gene set qc (19Q2 depmap release) # In[5]: # Recode column names to entrez ids from dependency file -entrez_genes = [x[1].strip(")").strip() for x in dependency_df.iloc[:, 1:].columns.str.split("(")] +entrez_genes = [ + x[1].strip(")").strip() for x in dependency_df.iloc[:, 1:].columns.str.split("(") +] # Obtain intersection of entrez gene ids -entrez_intersection = list( - set(gene_meta_df.entrezgene).intersection(set(entrez_genes)) -) +entrez_intersection = list(set(gene_meta_df.entrezgene).intersection(set(entrez_genes))) print(f"The number of overlapping entrez gene ids: {len(entrez_intersection)}") # Subset the gene metadata file to only those in common, which are ones that passed qc gene_passed_qc_df = ( - gene_meta_df - .query("entrezgene in @entrez_intersection") + gene_meta_df.query("entrezgene in @entrez_intersection") .set_index("entrezgene") .reindex(entrez_intersection) .reset_index() @@ -97,7 +96,7 @@ # ## Convert the initial dependency map input file to three parts -# +# # 1. Entrez ID # 2. Symbol # 3. The full column name @@ -105,15 +104,13 @@ # In[6]: -entrez_genes = [x[1].strip(")").strip() for x in dependency_df.columns.str.split("(")] -symbol_genes = [x[0].strip() for x in dependency_df.columns.str.split("(")] +entrez_genes = [ + x[1].strip(")").strip() for x in dependency_df.iloc[:, 1:].columns.str.split("(") +] +symbol_genes = [x[0].strip() for x in dependency_df.iloc[:, 1:].columns.str.split("(")] gene_dictionary_df = pd.DataFrame( - [ - entrez_genes, - symbol_genes, - dependency_df.columns.tolist() - ] + [entrez_genes, symbol_genes, dependency_df.iloc[:, 1:].columns.tolist()] ).transpose() gene_dictionary_df.columns = ["entrez_id", "symbol_id", "dependency_column"] @@ -140,7 +137,7 @@ gene_passed_qc_df, left_on="entrez_id", right_on="entrezgene", - how="left" # Note the left merge, to retain all genes from gene_dictionary_df + how="left", # Note the left merge, to retain all genes from gene_dictionary_df ) # Select only certain columns .loc[:, ["entrez_id", "symbol_id", "dependency_column", "entrezgene"]] @@ -151,27 +148,24 @@ ) # Convert genes with entrez entries to those that indicate QC pass -gene_dictionary_qc_df.loc[gene_dictionary_qc_df.qc_pass_pan != False, "qc_pass_pan"] = True +gene_dictionary_qc_df.loc[gene_dictionary_qc_df.qc_pass_pan != False, "qc_pass_pan"] = ( + True +) # Create the qc_pass_other column -gene_dictionary_qc_df = ( - gene_dictionary_qc_df.assign( - qc_pass_other=~gene_dictionary_qc_df.symbol_id.str.contains(qc_fail_other_genes) - ) +gene_dictionary_qc_df = gene_dictionary_qc_df.assign( + qc_pass_other=~gene_dictionary_qc_df.symbol_id.str.contains(qc_fail_other_genes) ) # Create qc_pass summary column -gene_dictionary_qc_df = ( - gene_dictionary_qc_df.assign( - qc_pass=(gene_dictionary_qc_df.qc_pass_pan & gene_dictionary_qc_df.qc_pass_other) - ) +gene_dictionary_qc_df = gene_dictionary_qc_df.assign( + qc_pass=(gene_dictionary_qc_df.qc_pass_pan & gene_dictionary_qc_df.qc_pass_other) ) # Output file -gene_dictionary_qc_df.to_parquet(output_gene_dict_file, index=False, sep="\t") +gene_dictionary_qc_df.to_parquet(output_gene_dict_file, index=False) print(gene_dictionary_qc_df.qc_pass.value_counts()) print(gene_dictionary_qc_df.shape) gene_dictionary_qc_df.head(3) - diff --git a/9.webapp/app_utils.py b/9.webapp/app_utils.py index 106630a..1c1e7a2 100644 --- a/9.webapp/app_utils.py +++ b/9.webapp/app_utils.py @@ -16,7 +16,7 @@ # ── Load & filter data ──────────────────────────────────────────────────────── def load_data(): # Load dependency data - data_directory = pathlib.Path("../0.data-download/data").resolve() + data_directory = pathlib.Path("./data").resolve() dependency_file = pathlib.Path( f"{data_directory}/CRISPRGeneEffect.parquet" ).resolve() @@ -25,13 +25,13 @@ def load_data(): ).resolve() dependency_df, gene_dict_df = load_model_data(dependency_file, gene_dict_file) dependency_df = dependency_df.set_index("ModelID") - cancer_type_input_file = pathlib.Path("../0.data-download/data/Model.parquet") + cancer_type_input_file = pathlib.Path("./data/Model.parquet") cancer_type_df = pd.read_parquet(cancer_type_input_file) def latent_load_data(): # latent space data - cancer_type_input_file = pathlib.Path("../0.data-download/data/Model.parquet") + cancer_type_input_file = pathlib.Path("./data/Model.parquet") cancer_type_df = pd.read_parquet(cancer_type_input_file) reactome_dims = pathlib.Path( @@ -93,7 +93,7 @@ def latent_load_data(): def single_load_data(): # Load dependency data - data_directory = pathlib.Path("../0.data-download/data").resolve() + data_directory = pathlib.Path("./data").resolve() dependency_file = pathlib.Path( f"{data_directory}/CRISPRGeneEffect.parquet" ).resolve() @@ -102,7 +102,7 @@ def single_load_data(): ).resolve() dependency_df, gene_dict_df = load_model_data(dependency_file, gene_dict_file) dependency_df = dependency_df.set_index("ModelID") - cancer_type_input_file = pathlib.Path("../0.data-download/data/Model.parquet") + cancer_type_input_file = pathlib.Path("./data/Model.parquet") cancer_type_df = pd.read_parquet(cancer_type_input_file) combined_df = dependency_df.merge( cancer_type_df[["ModelID", "OncotreePrimaryDisease"]], on="ModelID", how="left" diff --git a/9.webapp/data/CRISPRGeneEffect.parquet b/9.webapp/data/CRISPRGeneEffect.parquet new file mode 100644 index 0000000..e82ecea --- /dev/null +++ b/9.webapp/data/CRISPRGeneEffect.parquet @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7122ad47501a6bda0f8c98d0109e04a3c7aaa29d92624bad2ca38c6abed2f4d5 +size 203238901 diff --git a/9.webapp/data/CRISPR_gene_dictionary.parquet b/9.webapp/data/CRISPR_gene_dictionary.parquet new file mode 100644 index 0000000..7b1d06c --- /dev/null +++ b/9.webapp/data/CRISPR_gene_dictionary.parquet @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:00b08e507727b63a2eff033dc66de027005df63ca77a6ec1265ffa8440768207 +size 496959 diff --git a/9.webapp/data/Model.parquet b/9.webapp/data/Model.parquet new file mode 100644 index 0000000..f6ac944 --- /dev/null +++ b/9.webapp/data/Model.parquet @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e18aaaceb0f2b4d013cf6ed6da351a63cdc0ccba89967d8f146ce03793b7b0c0 +size 192916 From 17423382c455f6675253cb8d91e371dd5bac2f22 Mon Sep 17 00:00:00 2001 From: MikeLippincott <1michaell2017@gmail.com> Date: Mon, 8 Jun 2026 19:50:02 -0600 Subject: [PATCH 07/25] adding new --- 9.webapp/app.py | 5 +++++ 9.webapp/app_utils.py | 11 ++++++++--- 2 files changed, 13 insertions(+), 3 deletions(-) diff --git a/9.webapp/app.py b/9.webapp/app.py index 097f7d1..16ed3c6 100644 --- a/9.webapp/app.py +++ b/9.webapp/app.py @@ -2,6 +2,8 @@ Gene Process Dependency Explorer """ +import os +import pathlib import textwrap import matplotlib.pyplot as plt @@ -27,6 +29,9 @@ from sklearn.decomposition import PCA from sklearn.preprocessing import StandardScaler +BASE_DIR = pathlib.Path(os.path.dirname(os.path.abspath(__file__))).parent + + # ── Page config ─────────────────────────────────────────────────────────────── st.set_page_config( page_title="Gene Process Dependency Explorer", diff --git a/9.webapp/app_utils.py b/9.webapp/app_utils.py index 1c1e7a2..31889fd 100644 --- a/9.webapp/app_utils.py +++ b/9.webapp/app_utils.py @@ -1,4 +1,5 @@ import colorsys +import os import pathlib import random import textwrap @@ -12,6 +13,10 @@ from ipywidgets import widgets from sklearn.decomposition import PCA +# Go up one level to repo root, then into data/ +BASE_DIR = pathlib.Path(os.path.dirname(os.path.abspath(__file__))) +print(f"Base directory for data loading: {BASE_DIR}") + # ── Load & filter data ──────────────────────────────────────────────────────── def load_data(): @@ -25,13 +30,13 @@ def load_data(): ).resolve() dependency_df, gene_dict_df = load_model_data(dependency_file, gene_dict_file) dependency_df = dependency_df.set_index("ModelID") - cancer_type_input_file = pathlib.Path("./data/Model.parquet") + cancer_type_input_file = pathlib.Path(f"{BASE_DIR}/data/Model.parquet") cancer_type_df = pd.read_parquet(cancer_type_input_file) def latent_load_data(): # latent space data - cancer_type_input_file = pathlib.Path("./data/Model.parquet") + cancer_type_input_file = pathlib.Path(f"{BASE_DIR}/data/Model.parquet") cancer_type_df = pd.read_parquet(cancer_type_input_file) reactome_dims = pathlib.Path( @@ -102,7 +107,7 @@ def single_load_data(): ).resolve() dependency_df, gene_dict_df = load_model_data(dependency_file, gene_dict_file) dependency_df = dependency_df.set_index("ModelID") - cancer_type_input_file = pathlib.Path("./data/Model.parquet") + cancer_type_input_file = pathlib.Path(f"{BASE_DIR}/data/Model.parquet") cancer_type_df = pd.read_parquet(cancer_type_input_file) combined_df = dependency_df.merge( cancer_type_df[["ModelID", "OncotreePrimaryDisease"]], on="ModelID", how="left" From 4a32650425c78621c4547b792d6f4ba71d790c22 Mon Sep 17 00:00:00 2001 From: MikeLippincott <1michaell2017@gmail.com> Date: Mon, 8 Jun 2026 20:03:37 -0600 Subject: [PATCH 08/25] add new site --- 9.webapp/app_utils.py | 53 ++++++++++++++++++++++++------------------- 1 file changed, 30 insertions(+), 23 deletions(-) diff --git a/9.webapp/app_utils.py b/9.webapp/app_utils.py index 31889fd..95b2662 100644 --- a/9.webapp/app_utils.py +++ b/9.webapp/app_utils.py @@ -15,19 +15,18 @@ # Go up one level to repo root, then into data/ BASE_DIR = pathlib.Path(os.path.dirname(os.path.abspath(__file__))) -print(f"Base directory for data loading: {BASE_DIR}") +REPO_ROOT = BASE_DIR.parent # goes up from 9.webapp/ to repo root +print(f"Base directory: {BASE_DIR}") +print(f"Repo root: {REPO_ROOT}") # ── Load & filter data ──────────────────────────────────────────────────────── def load_data(): # Load dependency data - data_directory = pathlib.Path("./data").resolve() - dependency_file = pathlib.Path( - f"{data_directory}/CRISPRGeneEffect.parquet" - ).resolve() - gene_dict_file = pathlib.Path( - f"{data_directory}/CRISPR_gene_dictionary.parquet" - ).resolve() + data_directory = BASE_DIR / "data" + dependency_file = data_directory / "CRISPRGeneEffect.parquet" + gene_dict_file = data_directory / "CRISPR_gene_dictionary.parquet" + cancer_type_input_file = BASE_DIR / "data" / "Model.parquet" dependency_df, gene_dict_df = load_model_data(dependency_file, gene_dict_file) dependency_df = dependency_df.set_index("ModelID") cancer_type_input_file = pathlib.Path(f"{BASE_DIR}/data/Model.parquet") @@ -36,18 +35,20 @@ def load_data(): def latent_load_data(): # latent space data - cancer_type_input_file = pathlib.Path(f"{BASE_DIR}/data/Model.parquet") + cancer_type_input_file = BASE_DIR / "data" / "Model.parquet" cancer_type_df = pd.read_parquet(cancer_type_input_file) - reactome_dims = pathlib.Path( - "../5.drug-dependency/results/all_reactome_results.parquet" + reactome_dims = ( + REPO_ROOT / "5.drug-dependency" / "results" / "all_reactome_results.parquet" + ) + corum_dims = ( + REPO_ROOT / "5.drug-dependency" / "results" / "all_corum_results.parquet" ) + drug_dims = REPO_ROOT / "5.drug-dependency" / "results" / "all_drug_results.parquet" reactome_df = pd.read_parquet(reactome_dims) - corum_dims = pathlib.Path("../5.drug-dependency/results/all_corum_results.parquet") corum_df = pd.read_parquet(corum_dims) - drug_dims = pathlib.Path("../5.drug-dependency/results/all_drug_results.parquet") drug_df = pd.read_parquet(drug_dims) # Step 2: Subset based on matching keys subset_keys = ["model", "latent_dim_total", "init", "z"] @@ -98,13 +99,10 @@ def latent_load_data(): def single_load_data(): # Load dependency data - data_directory = pathlib.Path("./data").resolve() - dependency_file = pathlib.Path( - f"{data_directory}/CRISPRGeneEffect.parquet" - ).resolve() - gene_dict_file = pathlib.Path( - f"{data_directory}/CRISPR_gene_dictionary.parquet" - ).resolve() + data_directory = BASE_DIR / "data" + dependency_file = data_directory / "CRISPRGeneEffect.parquet" + gene_dict_file = data_directory / "CRISPR_gene_dictionary.parquet" + cancer_type_input_file = BASE_DIR / "data" / "Model.parquet" dependency_df, gene_dict_df = load_model_data(dependency_file, gene_dict_file) dependency_df = dependency_df.set_index("ModelID") cancer_type_input_file = pathlib.Path(f"{BASE_DIR}/data/Model.parquet") @@ -118,9 +116,18 @@ def single_load_data(): def spider_load_data(): # model_ids = ["ACH-000323", "ACH-002083", "ACH-002228"] files = { - "Reactome Pathways": "../5.drug-dependency/results/all_reactome_results.parquet", - "CORUM Complexes": "../5.drug-dependency/results/all_corum_results.parquet", - "Drug Responses": "../5.drug-dependency/results/all_drug_results.parquet", + "Reactome Pathways": REPO_ROOT + / "5.drug-dependency" + / "results" + / "all_reactome_results.parquet", + "CORUM Complexes": REPO_ROOT + / "5.drug-dependency" + / "results" + / "all_corum_results.parquet", + "Drug Responses": REPO_ROOT + / "5.drug-dependency" + / "results" + / "all_drug_results.parquet", } # Adjust these if your column names differ feature_colnames = { From 8c8cf60407aab7de23d742c92dd275bec24cc10f Mon Sep 17 00:00:00 2001 From: MikeLippincott <1michaell2017@gmail.com> Date: Tue, 9 Jun 2026 12:39:45 -0600 Subject: [PATCH 09/25] fix crashing by adding caching --- 9.webapp/app.py | 24 ++++++++++++------------ 9.webapp/app_utils.py | 22 ++++++++++++++++++++++ 2 files changed, 34 insertions(+), 12 deletions(-) diff --git a/9.webapp/app.py b/9.webapp/app.py index 16ed3c6..3906dbf 100644 --- a/9.webapp/app.py +++ b/9.webapp/app.py @@ -14,6 +14,7 @@ import streamlit as st from app_utils import ( clean_label, + compute_single_pca, generate_random_palette, latent_load_data, load_data, @@ -112,6 +113,15 @@ unsafe_allow_html=True, ) +# ── Load all data once at startup ───────────────────────────────────────────── +_base_reactome, _base_corum, _base_drug = latent_load_data() +ALL_DISEASES = sorted(_base_reactome["OncotreePrimaryDisease"].unique().tolist()) +ALL_MODEL_IDS = sorted(_base_reactome["ModelID"].unique().tolist()) + +# Then in each tab, unpack from the cached call — no reload happens: +# tab_latent, tab_scores, tab_table all call latent_load_data() again +# but with @st.cache_data it returns the cached result instantly + # ── Header ──────────────────────────────────────────────────────────────────── st.markdown("# Gene Process Dependency Explorer") st.markdown( @@ -221,17 +231,7 @@ def model_id_controls(key_prefix: str) -> list[str]: if len(selected_diseases_single) == 0: st.warning("Please select at least one primary disease to display the plot.") else: - combined_df = single_load_data() - combined_df = combined_df[ - combined_df["OncotreePrimaryDisease"].isin(selected_diseases_single) - ] - - gene_cols = combined_df.columns.drop(["ModelID", "OncotreePrimaryDisease"]) - pca_input = combined_df[gene_cols].apply(pd.to_numeric, errors="coerce") - pca = PCA(n_components=2, random_state=0) - pca_embedding = pca.fit_transform(pca_input) - combined_df["PCA1"] = pca_embedding[:, 0] - combined_df["PCA2"] = pca_embedding[:, 1] + combined_df = compute_single_pca(tuple(sorted(selected_diseases_single))) cancer_types = combined_df["OncotreePrimaryDisease"].unique() color_map = ( @@ -287,7 +287,7 @@ def model_id_controls(key_prefix: str) -> list[str]: st.markdown('
    ', unsafe_allow_html=True) selected_diseases_latent = disease_controls("latent") st.markdown("
    ", unsafe_allow_html=True) - if len(selected_diseases_single) == 0: + if len(selected_diseases_latent) == 0: st.warning("Please select at least one primary disease to display the plot.") else: reactome_matrix, corum_matrix, drug_matrix = latent_load_data() diff --git a/9.webapp/app_utils.py b/9.webapp/app_utils.py index 95b2662..f3621bd 100644 --- a/9.webapp/app_utils.py +++ b/9.webapp/app_utils.py @@ -10,6 +10,7 @@ import pandas as pd import plotly.express as px import plotly.graph_objs as go +import streamlit as st from ipywidgets import widgets from sklearn.decomposition import PCA @@ -21,6 +22,7 @@ # ── Load & filter data ──────────────────────────────────────────────────────── +@st.cache_data def load_data(): # Load dependency data data_directory = BASE_DIR / "data" @@ -33,6 +35,7 @@ def load_data(): cancer_type_df = pd.read_parquet(cancer_type_input_file) +@st.cache_data def latent_load_data(): # latent space data cancer_type_input_file = BASE_DIR / "data" / "Model.parquet" @@ -96,6 +99,7 @@ def latent_load_data(): return reactome_matrix, corum_matrix, drug_matrix +@st.cache_data def single_load_data(): # Load dependency data @@ -113,6 +117,7 @@ def single_load_data(): return combined_df +@st.cache_data def spider_load_data(): # model_ids = ["ACH-000323", "ACH-002083", "ACH-002228"] files = { @@ -410,6 +415,23 @@ def make_dropdown_pca_with_selection(df, title="PCA Interactive Plot"): return fig, out # Return both the figure and the output widget for selection +@st.cache_data +def compute_single_pca(selected_diseases: tuple) -> pd.DataFrame: + """Cache PCA result per disease selection.""" + combined_df = single_load_data() + combined_df = combined_df[ + combined_df["OncotreePrimaryDisease"].isin(selected_diseases) + ] + gene_cols = combined_df.columns.drop(["ModelID", "OncotreePrimaryDisease"]) + pca_input = combined_df[gene_cols].apply(pd.to_numeric, errors="coerce") + pca = PCA(n_components=2, random_state=0) + pca_embedding = pca.fit_transform(pca_input) + combined_df = combined_df.copy() + combined_df["PCA1"] = pca_embedding[:, 0] + combined_df["PCA2"] = pca_embedding[:, 1] + return combined_df + + def load_model_data(dependency_file, gene_dict_file): """ Load and preprocess gene dependency data and gene dictionary. From 905b43db85eb4369370852bf7143f392e6968cbe Mon Sep 17 00:00:00 2001 From: Gregory Way Date: Wed, 10 Jun 2026 13:38:37 -0600 Subject: [PATCH 10/25] fix app startup crash caused by loading large data at import time Replace heavy latent_load_data() call at startup with a lightweight read of Model.parquet (188 KB) for disease/model ID lists. Gate the 194 MB CRISPR load behind an explicit Compute PCA button. Trim cached PCA output to only the 4 needed columns instead of the full gene matrix. Co-Authored-By: Claude Sonnet 4.6 --- 9.webapp/app.py | 27 +++++++++++---------------- 9.webapp/app_utils.py | 2 +- 2 files changed, 12 insertions(+), 17 deletions(-) diff --git a/9.webapp/app.py b/9.webapp/app.py index 3906dbf..e30b51a 100644 --- a/9.webapp/app.py +++ b/9.webapp/app.py @@ -113,14 +113,11 @@ unsafe_allow_html=True, ) -# ── Load all data once at startup ───────────────────────────────────────────── -_base_reactome, _base_corum, _base_drug = latent_load_data() -ALL_DISEASES = sorted(_base_reactome["OncotreePrimaryDisease"].unique().tolist()) -ALL_MODEL_IDS = sorted(_base_reactome["ModelID"].unique().tolist()) - -# Then in each tab, unpack from the cached call — no reload happens: -# tab_latent, tab_scores, tab_table all call latent_load_data() again -# but with @st.cache_data it returns the cached result instantly +# ── Load only the tiny model metadata file at startup (188 KB) ──────────────── +_model_meta = pd.read_parquet(pathlib.Path(__file__).parent / "data" / "Model.parquet", columns=["ModelID", "OncotreePrimaryDisease"]) +ALL_DISEASES = sorted(_model_meta["OncotreePrimaryDisease"].dropna().unique().tolist()) +ALL_MODEL_IDS = sorted(_model_meta["ModelID"].dropna().unique().tolist()) +DEFAULT_MODEL_IDS = ["ACH-000323", "ACH-002083", "ACH-002228"] # ── Header ──────────────────────────────────────────────────────────────────── st.markdown("# Gene Process Dependency Explorer") @@ -129,12 +126,6 @@ unsafe_allow_html=True, ) -# ── Load base data once (cheap — just for disease list) ─────────────────────── -_base_reactome, _base_corum, _base_drug = latent_load_data() -ALL_DISEASES = sorted(_base_reactome["OncotreePrimaryDisease"].unique().tolist()) -ALL_MODEL_IDS = sorted(_base_reactome["ModelID"].unique().tolist()) -DEFAULT_MODEL_IDS = ["ACH-000323", "ACH-002083", "ACH-002228"] - # ── Tabs ────────────────────────────────────────────────────────────────────── ( tab_welcome, @@ -228,10 +219,14 @@ def model_id_controls(key_prefix: str) -> list[str]: st.markdown('
    ', unsafe_allow_html=True) selected_diseases_single = disease_controls("single") st.markdown("
    ", unsafe_allow_html=True) + if len(selected_diseases_single) == 0: st.warning("Please select at least one primary disease to display the plot.") - else: - combined_df = compute_single_pca(tuple(sorted(selected_diseases_single))) + elif st.button("Compute PCA", key="single_compute"): + st.session_state["single_run"] = tuple(sorted(selected_diseases_single)) + + if st.session_state.get("single_run"): + combined_df = compute_single_pca(st.session_state["single_run"]) cancer_types = combined_df["OncotreePrimaryDisease"].unique() color_map = ( diff --git a/9.webapp/app_utils.py b/9.webapp/app_utils.py index f3621bd..4696c1d 100644 --- a/9.webapp/app_utils.py +++ b/9.webapp/app_utils.py @@ -426,7 +426,7 @@ def compute_single_pca(selected_diseases: tuple) -> pd.DataFrame: pca_input = combined_df[gene_cols].apply(pd.to_numeric, errors="coerce") pca = PCA(n_components=2, random_state=0) pca_embedding = pca.fit_transform(pca_input) - combined_df = combined_df.copy() + combined_df = combined_df[["ModelID", "OncotreePrimaryDisease"]].copy() combined_df["PCA1"] = pca_embedding[:, 0] combined_df["PCA2"] = pca_embedding[:, 1] return combined_df From c06f75e687f97987813ff478791345a5c3c8aea1 Mon Sep 17 00:00:00 2001 From: MikeLippincott <1michaell2017@gmail.com> Date: Thu, 18 Jun 2026 07:51:51 -0600 Subject: [PATCH 11/25] adding webapp page fixes --- .pre-commit-config.yaml | 38 +- 9.webapp/app.py | 323 ++++++--- .../data/pca_embeddings_latent_corum.parquet | 3 + .../data/pca_embeddings_latent_drug.parquet | 3 + .../pca_embeddings_latent_reactome.parquet | 3 + ...pca_embeddings_single_dependencies.parquet | 3 + 9.webapp/preprocessing.ipynb | 634 ++++++++++++++++++ 7 files changed, 896 insertions(+), 111 deletions(-) create mode 100644 9.webapp/data/pca_embeddings_latent_corum.parquet create mode 100644 9.webapp/data/pca_embeddings_latent_drug.parquet create mode 100644 9.webapp/data/pca_embeddings_latent_reactome.parquet create mode 100644 9.webapp/data/pca_embeddings_single_dependencies.parquet create mode 100644 9.webapp/preprocessing.ipynb diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index b6f56df..af1066d 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -1,43 +1,43 @@ repos: - - repo: https://gitlab.com/vojko.pribudic.foss/pre-commit-update +- repo: https://gitlab.com/vojko.pribudic.foss/pre-commit-update rev: v0.9.0 # Insert the latest tag here hooks: - - id: pre-commit-update + - id: pre-commit-update args: [--exclude, black, --keep, isort] # Formats import order - - repo: https://github.com/pycqa/isort +- repo: https://github.com/pycqa/isort rev: 5.12.0 hooks: - - id: isort + - id: isort name: isort (python) args: ["--profile", "black", "--filter-files"] #Code formatter for both python files and jupyter notebooks - - repo: https://github.com/astral-sh/ruff-pre-commit +- repo: https://github.com/astral-sh/ruff-pre-commit # Ruff version. - rev: v0.15.16 + rev: v0.15.17 hooks: # Run the formatter. - - id: ruff-format + - id: ruff-format - - repo: https://github.com/nbQA-dev/nbQA +- repo: https://github.com/nbQA-dev/nbQA rev: 1.9.1 hooks: - - id: nbqa-isort + - id: nbqa-isort additional_dependencies: [isort==5.6.4] args: [--profile=black] - - repo: https://github.com/pre-commit/mirrors-prettier +- repo: https://github.com/pre-commit/mirrors-prettier rev: "v3.1.0" hooks: - - id: prettier + - id: prettier types_or: [markdown, yaml, json, html, css, python, r] - - repo: https://github.com/hadialqattan/pycln +- repo: https://github.com/hadialqattan/pycln rev: v2.6.0 hooks: - - id: pycln + - id: pycln args: [--config=pyproject.toml] exclude: | (?x)^( @@ -45,17 +45,17 @@ repos: 3\.cellprofiling/scripts/.*\.py$ )$ # additional hooks found with in the pre-commit lib - - repo: https://github.com/pre-commit/pre-commit-hooks +- repo: https://github.com/pre-commit/pre-commit-hooks rev: v6.0.0 hooks: - - id: trailing-whitespace # removes trailing white spaces - - id: mixed-line-ending # removes mixed end of line + - id: trailing-whitespace # removes trailing white spaces + - id: mixed-line-ending # removes mixed end of line args: - - --fix=lf + - --fix=lf - - repo: local +- repo: local hooks: - - id: shellcheck + - id: shellcheck name: shellcheck description: Test shell scripts with shellcheck entry: shellcheck diff --git a/9.webapp/app.py b/9.webapp/app.py index 3906dbf..8f3c715 100644 --- a/9.webapp/app.py +++ b/9.webapp/app.py @@ -30,8 +30,10 @@ from sklearn.decomposition import PCA from sklearn.preprocessing import StandardScaler -BASE_DIR = pathlib.Path(os.path.dirname(os.path.abspath(__file__))).parent - +BASE_DIR = pathlib.Path(os.path.dirname(os.path.abspath(__file__))) +REPO_DIR = BASE_DIR.parent +print(f"Base directory: {BASE_DIR}") +print(f"Repository directory: {REPO_DIR}") # ── Page config ─────────────────────────────────────────────────────────────── st.set_page_config( @@ -113,15 +115,6 @@ unsafe_allow_html=True, ) -# ── Load all data once at startup ───────────────────────────────────────────── -_base_reactome, _base_corum, _base_drug = latent_load_data() -ALL_DISEASES = sorted(_base_reactome["OncotreePrimaryDisease"].unique().tolist()) -ALL_MODEL_IDS = sorted(_base_reactome["ModelID"].unique().tolist()) - -# Then in each tab, unpack from the cached call — no reload happens: -# tab_latent, tab_scores, tab_table all call latent_load_data() again -# but with @st.cache_data it returns the cached result instantly - # ── Header ──────────────────────────────────────────────────────────────────── st.markdown("# Gene Process Dependency Explorer") st.markdown( @@ -134,6 +127,18 @@ ALL_DISEASES = sorted(_base_reactome["OncotreePrimaryDisease"].unique().tolist()) ALL_MODEL_IDS = sorted(_base_reactome["ModelID"].unique().tolist()) DEFAULT_MODEL_IDS = ["ACH-000323", "ACH-002083", "ACH-002228"] +single_gene_pca_df = pd.read_parquet( + BASE_DIR / "data" / "pca_embeddings_single_dependencies.parquet" +) +latent_reactome_pca_df = pd.read_parquet( + BASE_DIR / "data" / "pca_embeddings_latent_reactome.parquet" +) +latent_corum_pca_df = pd.read_parquet( + BASE_DIR / "data" / "pca_embeddings_latent_corum.parquet" +) +latent_drug_pca_df = pd.read_parquet( + BASE_DIR / "data" / "pca_embeddings_latent_drug.parquet" +) # ── Tabs ────────────────────────────────────────────────────────────────────── ( @@ -228,12 +233,80 @@ def model_id_controls(key_prefix: str) -> list[str]: st.markdown('
    ', unsafe_allow_html=True) selected_diseases_single = disease_controls("single") st.markdown("
    ", unsafe_allow_html=True) - if len(selected_diseases_single) == 0: - st.warning("Please select at least one primary disease to display the plot.") - else: - combined_df = compute_single_pca(tuple(sorted(selected_diseases_single))) - cancer_types = combined_df["OncotreePrimaryDisease"].unique() + cancer_types = single_gene_pca_df["OncotreePrimaryDisease"].unique() + color_map = ( + px.colors.qualitative.Plotly + + px.colors.qualitative.Light24 + + px.colors.qualitative.Dark24 + ) + highlight_color_map = { + c: color_map[i % len(color_map)] for i, c in enumerate(cancer_types) + } + + traces = [] + for cancer in cancer_types: + df_sub = single_gene_pca_df[ + single_gene_pca_df["OncotreePrimaryDisease"] == cancer + ] + is_selected = cancer in selected_diseases_single + traces.append( + go.Scatter( + x=df_sub["PCA1"], + y=df_sub["PCA2"], + mode="markers", + name=cancer, + marker=dict( + size=7, + color=highlight_color_map[cancer] if is_selected else "#3d444d", + opacity=1.0 if is_selected else 0.3, + ), + text=[f"{cancer} | {m}" for m in df_sub["ModelID"]], + hoverinfo="text" if is_selected else "skip", + showlegend=is_selected, + ) + ) + + # Render grayed traces behind colored ones + traces.sort(key=lambda t: t.name in selected_diseases_single, reverse=True) + + fig_single = go.Figure(data=traces) + fig_single.update_layout( + paper_bgcolor="#0d1117", + plot_bgcolor="#0d1117", + font=dict(color="#e6edf3"), + xaxis=dict(gridcolor="#21262d"), + yaxis=dict(gridcolor="#21262d"), + legend=dict(bgcolor="#161b22", bordercolor="#30363d", borderwidth=1), + height=1200, + margin=dict(l=40, r=40, t=40, b=40), + width=800, + ) + st.plotly_chart(fig_single, use_container_width=True) + +# ───────────────────────────────────────────────────────────────────────────── +# TAB 2 — Latent plots +# ───────────────────────────────────────────────────────────────────────────── +with tab_latent: + st.markdown("### Latent Space PCA Projections") + st.markdown( + "PCA projection of latent representations learned by the selected compression model. " + "Each point is a cancer cell line; clusters indicate similar gene dependency profiles." + ) + + with st.container(): + st.markdown('
    ', unsafe_allow_html=True) + selected_diseases_latent = disease_controls("latent") + st.markdown("
    ", unsafe_allow_html=True) + + for title, pca_df in [ + ("Reactome", latent_reactome_pca_df), + ("CORUM", latent_corum_pca_df), + ("Drug", latent_drug_pca_df), + ]: + st.markdown(f"#### PCA: {title} Subset") + + cancer_types = pca_df["OncotreePrimaryDisease"].unique() color_map = ( px.colors.qualitative.Plotly + px.colors.qualitative.Light24 @@ -245,73 +318,39 @@ def model_id_controls(key_prefix: str) -> list[str]: traces = [] for cancer in cancer_types: - df_sub = combined_df[combined_df["OncotreePrimaryDisease"] == cancer] + df_sub = pca_df[pca_df["OncotreePrimaryDisease"] == cancer] + is_selected = cancer in selected_diseases_latent traces.append( go.Scatter( x=df_sub["PCA1"], y=df_sub["PCA2"], mode="markers", name=cancer, - marker=dict(size=7, color=highlight_color_map[cancer]), + marker=dict( + size=7, + color=highlight_color_map[cancer] if is_selected else "#3d444d", + opacity=1.0 if is_selected else 0.3, + ), text=[f"{cancer} | {m}" for m in df_sub["ModelID"]], - hoverinfo="text", + hoverinfo="text" if is_selected else "skip", + showlegend=is_selected, ) ) - fig_single = go.Figure(data=traces) - fig_single.update_layout( + traces.sort(key=lambda t: t.name in selected_diseases_latent, reverse=True) + + fig = go.Figure(data=traces) + fig.update_layout( paper_bgcolor="#0d1117", plot_bgcolor="#0d1117", font=dict(color="#e6edf3"), xaxis=dict(gridcolor="#21262d"), yaxis=dict(gridcolor="#21262d"), legend=dict(bgcolor="#161b22", bordercolor="#30363d", borderwidth=1), - height=1200, + height=600, margin=dict(l=40, r=40, t=40, b=40), - width=800, ) - st.plotly_chart(fig_single, use_container_width=True) - - -# ───────────────────────────────────────────────────────────────────────────── -# TAB 2 — Latent plots -# ───────────────────────────────────────────────────────────────────────────── -with tab_latent: - st.markdown("### Latent Space PCA Projections") - st.markdown( - "PCA projection of latent representations learned by the selected compression model. " - "Each point is a cancer cell line; clusters indicate similar gene dependency profiles." - ) - - with st.container(): - st.markdown('
    ', unsafe_allow_html=True) - selected_diseases_latent = disease_controls("latent") - st.markdown("
    ", unsafe_allow_html=True) - if len(selected_diseases_latent) == 0: - st.warning("Please select at least one primary disease to display the plot.") - else: - reactome_matrix, corum_matrix, drug_matrix = latent_load_data() - reactome_matrix = reactome_matrix[ - reactome_matrix["OncotreePrimaryDisease"].isin(selected_diseases_latent) - ] - corum_matrix = corum_matrix[ - corum_matrix["OncotreePrimaryDisease"].isin(selected_diseases_latent) - ] - drug_matrix = drug_matrix[ - drug_matrix["OncotreePrimaryDisease"].isin(selected_diseases_latent) - ] - - reactome_fig, _ = make_dropdown_pca_with_selection( - reactome_matrix, "PCA: Reactome Subset" - ) - corum_fig, _ = make_dropdown_pca_with_selection( - corum_matrix, "PCA: CORUM Subset" - ) - drug_fig, _ = make_dropdown_pca_with_selection(drug_matrix, "PCA: Drug Subset") - - st.plotly_chart(reactome_fig, use_container_width=True) - st.plotly_chart(corum_fig, use_container_width=True) - st.plotly_chart(drug_fig, use_container_width=True) + st.plotly_chart(fig, use_container_width=True) # ───────────────────────────────────────────────────────────────────────────── @@ -326,10 +365,58 @@ def model_id_controls(key_prefix: str) -> list[str]: with st.container(): st.markdown('
    ', unsafe_allow_html=True) - sp_c1, sp_c2 = st.columns(2) + sp_c1, sp_c2, sp_c3 = st.columns(3) + with sp_c1: - model_ids_spider = model_id_controls("spider") + spider_filter_mode = st.radio( + "Filter by", + ["Model IDs", "Cancer Types"], + horizontal=True, + key="spider_filter_mode", + ) + with sp_c2: + if spider_filter_mode == "Model IDs": + st.markdown( + '
    Model IDs (max 10)
    ', + unsafe_allow_html=True, + ) + spider_model_ids = st.multiselect( + "Model IDs", + ALL_MODEL_IDS, + default=st.session_state.get("spider_model_ids", DEFAULT_MODEL_IDS), + max_selections=10, + label_visibility="collapsed", + key="spider_model_ids", + ) + else: + st.markdown( + '
    Cancer Types (max 5)
    ', + unsafe_allow_html=True, + ) + spider_cancer_types = st.multiselect( + "Cancer Types", + ALL_DISEASES, + default=st.session_state.get( + "spider_cancer_types", ALL_DISEASES[:2] + ), + max_selections=5, + label_visibility="collapsed", + key="spider_cancer_types", + ) + st.markdown( + '
    Aggregation
    ', + unsafe_allow_html=True, + ) + spider_agg = st.radio( + "Aggregation", + ["Mean", "Min", "Max"], + horizontal=True, + key="spider_agg", + label_visibility="collapsed", + ) + + with sp_c3: st.markdown( '
    Process limit
    ', unsafe_allow_html=True ) @@ -351,34 +438,86 @@ def model_id_controls(key_prefix: str) -> list[str]: st.markdown("
    ", unsafe_allow_html=True) dfs, global_max, feature_colnames = spider_load_data() - fig_spider, axes = plt.subplots(3, 1, figsize=(18, 12), subplot_kw=dict(polar=True)) - - for ax, (title, df) in zip(axes, dfs.items()): - df = df[df["ModelID"].isin(model_ids_spider)].copy() - cols = feature_colnames[title] - make_radar( - ax, - df, - cols, - title, - global_max, - model_ids=model_ids_spider, - max_processes=max_processes, + + if spider_filter_mode == "Model IDs": + selected_ids = spider_model_ids + id_col = "ModelID" + else: + selected_ids = ( + spider_cancer_types + if "spider_cancer_types" in st.session_state or True + else [] ) + id_col = "OncotreePrimaryDisease" + agg_func = {"Mean": "mean", "Min": "min", "Max": "max"}[spider_agg] - handles, labels = axes[0].get_legend_handles_labels() - fig_spider.legend( - handles, - labels, - loc="lower center", - ncol=3, - fontsize=12, - frameon=False, - bbox_to_anchor=(0.5, -0.05), - ) - plt.tight_layout(rect=[0, 0, 1, 0.95]) - st.pyplot(fig_spider) + if len(selected_ids) == 0: + st.warning( + "Please select at least one model ID or cancer type to display the plots." + ) + else: + fig_spider, axes = plt.subplots( + 3, 1, figsize=(18, 12), subplot_kw=dict(polar=True) + ) + + for ax, (title, df) in zip(axes, dfs.items()): + cols = feature_colnames[title] + if spider_filter_mode == "Cancer Types": + df_filtered = df[df["OncotreePrimaryDisease"].isin(selected_ids)].copy() + + # cols from feature_colnames[title] is the correct feature column list + feature_cols = list(cols) if not isinstance(cols, list) else cols + st.write("feature_colnames:", feature_colnames) + + df_agg = ( + df_filtered.groupby("OncotreePrimaryDisease")[feature_cols] + .agg(agg_func) + .reset_index() + .rename(columns={"OncotreePrimaryDisease": "ModelID"}) + ) + + # Melt to long format — use a fixed string for var_name + df_long = df_agg.melt( + id_vars="ModelID", + value_vars=feature_cols, + var_name="feature", # fixed string, not cols + value_name="agg_score", + ) + + make_radar( + ax, + df_long, + "feature", # must match var_name above + f"{title} ({spider_agg})", + global_max, + score_col="agg_score", + model_ids=selected_ids, + max_processes=max_processes, + ) + else: + df_filtered = df[df["ModelID"].isin(selected_ids)].copy() + make_radar( + ax, + df_filtered, + cols, + title, + global_max, + model_ids=selected_ids, + max_processes=max_processes, + ) + handles, labels = axes[0].get_legend_handles_labels() + fig_spider.legend( + handles, + labels, + loc="lower center", + ncol=3, + fontsize=12, + frameon=False, + bbox_to_anchor=(0.5, -0.05), + ) + plt.tight_layout(rect=[0, 0, 1, 0.95]) + st.pyplot(fig_spider) # ───────────────────────────────────────────────────────────────────────────── # TAB 4 — Top scores diff --git a/9.webapp/data/pca_embeddings_latent_corum.parquet b/9.webapp/data/pca_embeddings_latent_corum.parquet new file mode 100644 index 0000000..05f5a45 --- /dev/null +++ b/9.webapp/data/pca_embeddings_latent_corum.parquet @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ea55d89c2344f42b991c75b304e8c7979f5fc12614626c62b9e4da094c573d01 +size 27185 diff --git a/9.webapp/data/pca_embeddings_latent_drug.parquet b/9.webapp/data/pca_embeddings_latent_drug.parquet new file mode 100644 index 0000000..2f778cb --- /dev/null +++ b/9.webapp/data/pca_embeddings_latent_drug.parquet @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:743e0bd874634a435595a9a47a41e6287e640da12d43724a5fd9b5ad7500e980 +size 27185 diff --git a/9.webapp/data/pca_embeddings_latent_reactome.parquet b/9.webapp/data/pca_embeddings_latent_reactome.parquet new file mode 100644 index 0000000..87bb1d8 --- /dev/null +++ b/9.webapp/data/pca_embeddings_latent_reactome.parquet @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:578278837ff1802c869e8ab84c642d692004edaa8dce144d89d49a0ef99d66b8 +size 27185 diff --git a/9.webapp/data/pca_embeddings_single_dependencies.parquet b/9.webapp/data/pca_embeddings_single_dependencies.parquet new file mode 100644 index 0000000..9b51d05 --- /dev/null +++ b/9.webapp/data/pca_embeddings_single_dependencies.parquet @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:52f2a39dbbeb503163175267b61db8b64da0def08bc821b920382b90e16eb7a9 +size 34741 diff --git a/9.webapp/preprocessing.ipynb b/9.webapp/preprocessing.ipynb new file mode 100644 index 0000000..675b571 --- /dev/null +++ b/9.webapp/preprocessing.ipynb @@ -0,0 +1,634 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 2, + "id": "6c08a8f0", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-06-09 13:29:16.828 WARNING streamlit.runtime.caching.cache_data_api: No runtime found, using MemoryCacheStorageManager\n", + "2026-06-09 13:29:16.829 WARNING streamlit.runtime.caching.cache_data_api: No runtime found, using MemoryCacheStorageManager\n", + "2026-06-09 13:29:16.830 WARNING streamlit.runtime.caching.cache_data_api: No runtime found, using MemoryCacheStorageManager\n", + "2026-06-09 13:29:16.830 WARNING streamlit.runtime.caching.cache_data_api: No runtime found, using MemoryCacheStorageManager\n", + "2026-06-09 13:29:16.831 WARNING streamlit.runtime.caching.cache_data_api: No runtime found, using MemoryCacheStorageManager\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Base directory: /home/lippincm/gene-process-dependencies/9.webapp\n", + "Repo root: /home/lippincm/gene-process-dependencies\n" + ] + } + ], + "source": [ + "import os\n", + "import pathlib\n", + "\n", + "import numpy as np\n", + "import pandas as pd\n", + "import streamlit as st\n", + "from app_utils import latent_load_data, load_model_data, single_load_data\n", + "from sklearn.decomposition import PCA" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "328325ad", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-06-09 13:29:16.839 WARNING streamlit.runtime.caching.cache_data_api: No runtime found, using MemoryCacheStorageManager\n", + "2026-06-09 13:29:16.840 WARNING streamlit.runtime.scriptrunner_utils.script_run_context: Thread 'MainThread': missing ScriptRunContext! This warning can be ignored when running in bare mode.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Base directory: /home/lippincm/gene-process-dependencies/9.webapp\n", + "Repo root: /home/lippincm/gene-process-dependencies\n" + ] + } + ], + "source": [ + "_base_reactome, _base_corum, _base_drug = latent_load_data()\n", + "ALL_DISEASES = sorted(_base_reactome[\"OncotreePrimaryDisease\"].unique().tolist())\n", + "ALL_MODEL_IDS = sorted(_base_reactome[\"ModelID\"].unique().tolist())\n", + "# Go up one level to repo root, then into data/\n", + "BASE_DIR = pathlib.Path().resolve()\n", + "REPO_ROOT = BASE_DIR.parent\n", + "REPO_ROOT = BASE_DIR.parent # goes up from 9.webapp/ to repo root\n", + "print(f\"Base directory: {BASE_DIR}\")\n", + "print(f\"Repo root: {REPO_ROOT}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "id": "37924565", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(1150, 18444)\n" + ] + } + ], + "source": [ + "combined_df = single_load_data()\n", + "data_directory = BASE_DIR / \"data\"\n", + "dependency_file = data_directory / \"CRISPRGeneEffect.parquet\"\n", + "gene_dict_file = data_directory / \"CRISPR_gene_dictionary.parquet\"\n", + "cancer_type_input_file = BASE_DIR / \"data\" / \"Model.parquet\"\n", + "dependency_df, gene_dict_df = load_model_data(dependency_file, gene_dict_file)\n", + "dependency_df = dependency_df.set_index(\"ModelID\")\n", + "cancer_type_input_file = pathlib.Path(f\"{BASE_DIR}/data/Model.parquet\")\n", + "cancer_type_df = pd.read_parquet(cancer_type_input_file)\n", + "reactome_matrix, corum_matrix, drug_matrix = latent_load_data()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0ef7365a", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 63, + "id": "4f84dac0", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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    ModelIDOncotreePrimaryDiseaselatent_scoregsea_es_scorepathway_scorefeature
    0ACH-000001Ovarian Epithelial Tumor0.3928600.8243150.392860Inactivation, Recovery And Regulation Of Photo...
    1ACH-000001Ovarian Epithelial Tumor0.7636300.8801160.763630Elastic Fibre Formation R-HSA-1566948
    2ACH-000001Ovarian Epithelial Tumor0.4355310.8395060.435531Mismatch Repair (MMR) Directed By MSH2:MSH6 (M...
    3ACH-000001Ovarian Epithelial Tumor0.531491-0.7333750.531491Processive Synthesis On Lagging Strand R-HSA-6...
    4ACH-000001Ovarian Epithelial Tumor0.2677500.8642570.267750Mismatch Repair (MMR) Directed By MSH2:MSH3 (M...
    .....................
    169777ACH-003012Non-Small Cell Lung Cancer0.5052960.9382710.505296Kinase maturation complex 1 (human)
    169778ACH-003012Non-Small Cell Lung Cancer0.2826340.8082170.282634immunoproteasome (mouse)
    169779ACH-003012Non-Small Cell Lung Cancer0.0736970.7480240.073697ALL-1 supercomplex (human)
    169780ACH-003012Non-Small Cell Lung Cancer0.0329450.7396780.032945Emerin complex 32 (human)
    169781ACH-003012Non-Small Cell Lung Cancer0.2832630.8150850.283263Ikaros complex (mouse)
    \n", + "

    169782 rows × 6 columns

    \n", + "
    " + ], + "text/plain": [ + " ModelID OncotreePrimaryDisease latent_score gsea_es_score \\\n", + "0 ACH-000001 Ovarian Epithelial Tumor 0.392860 0.824315 \n", + "1 ACH-000001 Ovarian Epithelial Tumor 0.763630 0.880116 \n", + "2 ACH-000001 Ovarian Epithelial Tumor 0.435531 0.839506 \n", + "3 ACH-000001 Ovarian Epithelial Tumor 0.531491 -0.733375 \n", + "4 ACH-000001 Ovarian Epithelial Tumor 0.267750 0.864257 \n", + "... ... ... ... ... \n", + "169777 ACH-003012 Non-Small Cell Lung Cancer 0.505296 0.938271 \n", + "169778 ACH-003012 Non-Small Cell Lung Cancer 0.282634 0.808217 \n", + "169779 ACH-003012 Non-Small Cell Lung Cancer 0.073697 0.748024 \n", + "169780 ACH-003012 Non-Small Cell Lung Cancer 0.032945 0.739678 \n", + "169781 ACH-003012 Non-Small Cell Lung Cancer 0.283263 0.815085 \n", + "\n", + " pathway_score feature \n", + "0 0.392860 Inactivation, Recovery And Regulation Of Photo... \n", + "1 0.763630 Elastic Fibre Formation R-HSA-1566948 \n", + "2 0.435531 Mismatch Repair (MMR) Directed By MSH2:MSH6 (M... \n", + "3 0.531491 Processive Synthesis On Lagging Strand R-HSA-6... \n", + "4 0.267750 Mismatch Repair (MMR) Directed By MSH2:MSH3 (M... \n", + "... ... ... \n", + "169777 0.505296 Kinase maturation complex 1 (human) \n", + "169778 0.282634 immunoproteasome (mouse) \n", + "169779 0.073697 ALL-1 supercomplex (human) \n", + "169780 0.032945 Emerin complex 32 (human) \n", + "169781 0.283263 Ikaros complex (mouse) \n", + "\n", + "[169782 rows x 6 columns]" + ] + }, + "execution_count": 63, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "corum_matrix_path = (\n", + " REPO_ROOT / \"5.drug-dependency\" / \"results\" / \"all_corum_results.parquet\"\n", + ")\n", + "corum_matrix = pd.read_parquet(corum_matrix_path)\n", + "corum_matrix[\"feature\"] = corum_matrix[\"reactome_pathway\"]\n", + "corum_matrix = corum_matrix.drop(\n", + " columns=[\"model\", \"latent_dim_total\", \"init\", \"seed\", \"z\", \"reactome_pathway\"]\n", + ")\n", + "meta_cols = [\"ModelID\", \"OncotreePrimaryDisease\"]\n", + "\n", + "corum_meta = corum_matrix[meta_cols].drop_duplicates()\n", + "\n", + "# corum_matrix = corum_matrix.pivot(index=\"ModelID\", columns=\"feature\", values=\"latent_score\")\n", + "# corum_matrix = corum_matrix.merge(corum_meta, on=\"ModelID\", how=\"left\")\n", + "# print(corum_matrix.isna().sum().sum())\n", + "# corum_matrix.drop(columns=['gsea_es_score',\"pathway_score\",\"OncotreePrimaryDisease\"], inplace=True)\n", + "# corum_matrix.pivot(index=\"ModelID\", columns=\"feature\", values=\"latent_score\")\n", + "corum_matrix" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "id": "0f7fe22e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Inactivation, Recovery And Regulation Of Phototransduction Cascade R-HSA-2514859\n", + "Elastic Fibre Formation R-HSA-1566948\n", + "Mismatch Repair (MMR) Directed By MSH2:MSH6 (MutSalpha) R-HSA-5358565\n", + "Processive Synthesis On Lagging Strand R-HSA-69183\n", + "Mismatch Repair (MMR) Directed By MSH2:MSH3 (MutSbeta) R-HSA-5358606\n", + "Phototransduction Cascade R-HSA-2514856\n", + "RNA polymerase II complex, chromatin structure modifying (human)\n", + "Integrator-RNAPII complex (human)\n", + "Parvulin-associated pre-rRNP complex (mouse)\n", + "PCAF complex (human)\n", + "DNA synthesome complex (17 subunits) (human)\n", + "CTF18-cohesion-RFC-POLH complex (human)\n", + "FCP1-associated protein complex (human)\n", + "CF IIAm complex (Cleavage factor IIAm complex) (human)\n", + "BRM-SIN3A-HDAC complex (human)\n", + "TNF-alpha/NF-kappa B signaling complex 6 (human)\n", + "TNF-alpha/NF-kappa B signaling complex (CHUK, BTRC, NFKB2, PPP6C, REL, CUL1, IKBKE, SAPS2, SAPS1, ANKRD28, RELA, SKP1) (human)\n", + "E2F-6 complex (human)\n", + "BRD4 complex (human)\n", + "RC complex (Replication competent complex) (human)\n", + "PBAF complex (Polybromo- and BAF containing complex) (human)\n", + "Emerin complex 24 (human)\n", + "DSS1 complex (human)\n", + "TFIIH transcription factor complex (human)\n", + "Prefoldin complex (human)\n", + "Gata1-Fog1-MeCP1 complex (mouse)\n", + "URI complex (Unconventional prefoldin RPB5 Interactor) (human)\n", + "BRM-SIN3A complex (human)\n", + "RSmad complex (human)\n", + "MLL1-WDR5 complex (human)\n", + "12S U11 snRNP (human)\n", + "BRAFT complex (human)\n", + "FA complex (Fanconi anemia complex) (human)\n", + "SMN complex (human)\n", + "p400-associated complex (human)\n", + "GCN5-TRRAP histone acetyltransferase complex (human)\n", + "Anaphase-promoting complex (human)\n", + "BAF complex (human)\n", + "UTX-MLL2/3 complex (human)\n", + "Rnase/Mrp complex (human)\n", + "NCOR2 complex (human)\n", + "NUMAC complex (nucleosomal methylation activator complex) (human)\n", + "PA700 complex (human)\n", + "Cell cycle kinase complex CDC2 (human)\n", + "CDC5L core complex (human)\n", + "SRCAP-associated chromatin remodeling complex (human)\n", + "5S-DNA-TFIIIA-TFIIIC2-TFIIIB subcomplex (human)\n", + "Respiratory chain complex I, mitochondrial (mouse)\n", + "TRAP complex (human)\n", + "TNF-alpha/NF-kappa B signaling complex 5 (human)\n", + "HCF-1 complex (human)\n", + "SMN-PolII-RHA complex (human)\n", + "DAB complex (human)\n", + "mRNA decay complex (UPF1, UPF2, UPF3B, DCP2, XRN1, XRN2, EXOSC2, EXOSC4, EXOSC10, PARN) (human)\n", + "TFTC-type histone acetyl transferase complex (human)\n", + "BLM complex II (human)\n", + "ARC-L complex (human)\n", + "RNA polymerase II (RNAPII) (human)\n", + "PA28gamma-20S proteasome (human)\n", + "BRG1-SIN3A complex (human)\n", + "5S-DNA-TFIIIA-TFIIIC2 subcomplex (human)\n", + "LSm1-7 complex (human)\n", + "NCOR1 complex (human)\n", + "PA28-20S proteasome (human)\n", + "TFTC complex (TATA-binding protein-free TAF-II-containing complex) (human)\n", + "PC2 complex (human)\n", + "SNF2h-cohesin-NuRD complex (human)\n", + "Respiratory chain complex I (early intermediate NDUFAF1 assembly), mitochondrial (human)\n", + "RC complex during G2/M-phase of cell cycle (human)\n", + "Polycystin-1 multiprotein complex (ACTN1, CDH1, SRC, JUP, VCL, CTNNB1, PXN, BCAR1, PKD1, PTK2, TLN1) (human)\n", + "Anti-HDAC2 complex (human)\n", + "p300-CBP-p270-SWI/SNF complex (human)\n", + "Ubiquitin E3 ligase (CSN1, CSN8, HRT1, SKP1, SKP2, CUL1, CUL2, CUL3) (human)\n", + "TFIID complex (mouse)\n", + "TFIID complex (human)\n", + "TNF-alpha/NF-kappa B signaling complex (SEC16A, CHUK, IKBKB, NFKB2, REL, IKBKG, MAP3K14, RELA, FBXW7, USP2) (human)\n", + "NAT complex (human)\n", + "EBAFb complex (human)\n", + "Nop56p-associated pre-rRNA complex (human)\n", + "DA complex (human)\n", + "HDAC1-associated core complex cII (human)\n", + "BRCA1-RNA polymerase II complex (human)\n", + "p97/VCP-VIMP-DERL1-DERL2-HRD1-SEL1L complex (human)\n", + "INO80 chromatin remodeling complex (human)\n", + "ARC complex (human)\n", + "DRIP complex (human)\n", + "WINAC complex (human)\n", + "SIN3-ING1b complex II (human)\n", + "ING2 complex (human)\n", + "SIN3-SAP25 complex (human)\n", + "COP9 signalosome complex (human)\n", + "Integrator complex (human)\n", + "CtBP complex (human)\n", + "ESR1-CDK7-CCNH-MNAT1-MTA1-HDAC2 complex (human)\n", + "26S proteasome (human)\n", + "ESCRT-III complex (human)\n", + "SIN3-ING1b complex I (human)\n", + "HDAC2-asscociated core complex (human)\n", + "CHUK-NFKB2-REL-IKBKG-SPAG9-NFKB1-NFKBIE-COPB2-TNIP1-NFKBIA-RELA-TNIP2 complex (human)\n", + "SWI-SNF chromatin remodeling-related-BRCA1 complex (human)\n", + "STAGA complex (SPT3-TAF9-GCN5 acetyltransferase complex) (human)\n", + "Cytochrome c oxidase (EC 1.9.3.1), mitochondrial (mouse)\n", + "NuA4/Tip60-HAT complex B (human)\n", + "LARC complex (LCR-associated remodeling complex) (human)\n", + "MeCP1 complex (human)\n", + "HES1 promoter-Notch enhancer complex (human)\n", + "NuA4/Tip60-HAT complex A (human)\n", + "Exosome (human)\n", + "18S U11/U12 snRNP (human)\n", + "Conserved oligomeric Golgi (COG) complex (human)\n", + "Emerin complex 25 (human)\n", + "TNF-alpha/Nf-kappa B signaling complex (RPL6, RPL30, RPS13, CHUK, DDX3X, NFKB2, NFKBIB, REL, IKBKG, NFKB1, MAP3K8, RELB, GLG1, NFKBIA, RELA, TNIP2, GTF2I) (human)\n", + "BRD4-RFC complex (human)\n", + "Ubiquitin E3 ligase (AHR, ARNT, DDB1, TBL3, CUL4B, RBX1) (human)\n", + "CRM1-RAN-PHAX-CBC complex (cap binding complex) (human)\n", + "RNA polymerase II holoenzyme complex (human)\n", + "BRCA1-core RNA polymerase II complex (human)\n", + "RC complex during S-phase of cell cycle (human)\n", + "TNF-alpha/NF-kappa B signaling complex (CHUK, KPNA3, NFKB2, NFKBIB, REL, IKBKG, NFKB1, NFKBIE, RELB, NFKBIA, RELA, TNIP2) (human)\n", + "LSm2-8 complex (human)\n", + "Toposome (human)\n", + "ARC92-Mediator complex (human)\n", + "CSA complex (human)\n", + "CENP-A NAC-CAD complex (human)\n", + "CCT complex (chaperonin containing TCP1 complex) (mouse)\n", + "CSA-POLIIa complex (human)\n", + "PTIP-DNA damage response complex (human)\n", + "BRCA1-BARD1-BACH1-DNA damage complex II (human)\n", + "cMYC-ATPase-helicase complex (human)\n", + "Anaphase-promoting complex (mouse)\n", + "Large Drosha complex (human)\n", + "CRSP complex (human)\n", + "SMCC complex (human)\n", + "17S U2 snRNP (human)\n", + "TRAP-SMCC mediator complex (human)\n", + "MTA2 complex (human)\n", + "Mediator complex (mouse)\n", + "Anti-Sm protein complex (human)\n", + "20S proteasome (human)\n", + "DMAP1-associated complex (human)\n", + "RNA polymerase II complex, incomplete (CDK8 complex), chromatin structure modifying (human)\n", + "Cytochrome bc1-complex (EC 1.10.2.2), mitochondrial (mouse)\n", + "RAD17-RFC-9-1-1 checkpoint supercomplex (human)\n", + "TFIID complex, B-cell specific (human)\n", + "CEN complex (human)\n", + "DDB2 complex (human)\n", + "BASC complex (BRCA1-associated genome surveillance complex) (human)\n", + "CRSP-Mediator 2 complex (human)\n", + "RNA polymerase II core complex (human)\n", + "MDC1-MRN-ATM-FANCD2 complex (human)\n", + "PCNA-CHL12-RFC2-5 complex (human)\n", + "EBAFa complex (human)\n", + "Condensin II (human)\n", + "Kaiso-NCOR complex (human)\n", + "SF3b complex (human)\n", + "PTIP-HMT complex (human)\n", + "Nup 107-160 subcomplex (human)\n", + "p27-cyclinE-Cdk2 - Ubiquitin E3 ligase (SKP1A, SKP2, CUL1, CKS1B, RBX1) complex (human)\n", + "TFIID-beta complex (human)\n", + "PYR complex (mouse)\n", + "Kinase maturation complex 1 (human)\n", + "immunoproteasome (mouse)\n", + "ALL-1 supercomplex (human)\n", + "Emerin complex 32 (human)\n", + "Ikaros complex (mouse)\n" + ] + } + ], + "source": [ + "for x in corum_matrix[\"feature\"].unique():\n", + " print(x)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2766b131", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "97fd0a08", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7fb27b941602401d91542211134fc71a", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "14ed27d8", + "metadata": {}, + "outputs": [], + "source": [ + "# get all modelids that have NA values in the corum matrix\n", + "corum_matrix[corum_matrix.isna().any(axis=1)][\"ModelID\"].sort_values().unique()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "484e6f14", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "6cdc8f80", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1150 rows before dropping NA\n", + "1150 rows after dropping NA\n", + "1150 rows before dropping NA\n", + "958 rows after dropping NA\n", + "1150 rows before dropping NA\n", + "958 rows after dropping NA\n", + "1150 rows before dropping NA\n", + "958 rows after dropping NA\n" + ] + } + ], + "source": [ + "# @st.cache_data\n", + "\n", + "\n", + "def compute_pca(df, metadata_columns) -> pd.DataFrame:\n", + " \"\"\"Cache PCA result per disease selection.\"\"\"\n", + " # df.fillna(0, inplace=True) # Fill NA with 0 for PCA, or drop rows with NA\n", + " print(df.shape[0], \"rows before dropping NA\")\n", + " df.dropna(inplace=True) # PCA can't handle missing values, so drop rows with any NA\n", + " print(df.shape[0], \"rows after dropping NA\")\n", + " metadata_df = df[metadata_columns]\n", + " feat_cols = df.columns.drop(metadata_columns)\n", + " if \"source\" in feat_cols:\n", + " feat_cols = feat_cols.drop(\"source\")\n", + "\n", + " pca_input = df[feat_cols].apply(pd.to_numeric, errors=\"coerce\")\n", + " pca = PCA(n_components=2, random_state=0)\n", + " pca_embedding = pca.fit_transform(pca_input)\n", + " metadata_df[\"PCA1\"] = pca_embedding[:, 0]\n", + " metadata_df[\"PCA2\"] = pca_embedding[:, 1]\n", + " return metadata_df\n", + "\n", + "\n", + "pca_single_df = compute_pca(combined_df, [\"ModelID\", \"OncotreePrimaryDisease\"])\n", + "# save the PCA result to a parquet file for later use in the app\n", + "pca_single_df.to_parquet(\n", + " BASE_DIR / \"data\" / \"pca_embeddings_single_dependencies.parquet\"\n", + ")\n", + "\n", + "pca_latent_reactome_df = compute_pca(\n", + " reactome_matrix, [\"OncotreePrimaryDisease\", \"ModelID\"]\n", + ")\n", + "pca_latent_corum_df = compute_pca(corum_matrix, [\"OncotreePrimaryDisease\", \"ModelID\"])\n", + "pca_latent_drug_df = compute_pca(drug_matrix, [\"OncotreePrimaryDisease\", \"ModelID\"])\n", + "pca_latent_reactome_df.to_parquet(\n", + " BASE_DIR / \"data\" / \"pca_embeddings_latent_reactome.parquet\"\n", + ")\n", + "pca_latent_corum_df.to_parquet(\n", + " BASE_DIR / \"data\" / \"pca_embeddings_latent_corum.parquet\"\n", + ")\n", + "pca_latent_drug_df.to_parquet(BASE_DIR / \"data\" / \"pca_embeddings_latent_drug.parquet\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dc8ccfe3", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "26a895e4", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv (3.13.1)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.1" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From bc1b51193a6062c10a1a80a16b21f58c9e7de299 Mon Sep 17 00:00:00 2001 From: Gregory Way Date: Thu, 18 Jun 2026 21:34:21 -0600 Subject: [PATCH 12/25] remove large data files from LFS, gitignore CRISPR files MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Move small webapp parquets (Model, PCA embeddings) out of Git LFS and into regular git — they are 27–188 KB and don't need LFS. Remove CRISPRGeneEffect and CRISPR_gene_dictionary from the repo entirely; they are downloaded locally via the data-download pipeline and are not needed by the webapp. Also drop dead imports from app.py that were left over from before pre-computed PCA embeddings were introduced. Co-Authored-By: Claude Sonnet 4.6 --- .gitattributes | 1 - .gitignore | 2 ++ 9.webapp/app.py | 5 ----- 9.webapp/data/CRISPRGeneEffect.parquet | 3 --- 9.webapp/data/CRISPR_gene_dictionary.parquet | 3 --- 9.webapp/data/Model.parquet | Bin 131 -> 192916 bytes .../data/pca_embeddings_latent_corum.parquet | Bin 130 -> 27185 bytes .../data/pca_embeddings_latent_drug.parquet | Bin 130 -> 27185 bytes .../pca_embeddings_latent_reactome.parquet | Bin 130 -> 27185 bytes ...pca_embeddings_single_dependencies.parquet | Bin 130 -> 34741 bytes 10 files changed, 2 insertions(+), 12 deletions(-) delete mode 100644 9.webapp/data/CRISPRGeneEffect.parquet delete mode 100644 9.webapp/data/CRISPR_gene_dictionary.parquet diff --git a/.gitattributes b/.gitattributes index de8fa28..e69de29 100644 --- a/.gitattributes +++ b/.gitattributes @@ -1 +0,0 @@ -9.webapp/data/*.parquet filter=lfs diff=lfs merge=lfs -text diff --git a/.gitignore b/.gitignore index 9c6700f..c32ab88 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,6 @@ __pycache__ 2.train-VAE/parameter_sweep .DS_Store 9.webapp/gene_dependency_webapp.egg-info +9.webapp/data/CRISPRGeneEffect.parquet +9.webapp/data/CRISPR_gene_dictionary.parquet *.pyc diff --git a/9.webapp/app.py b/9.webapp/app.py index b18f01f..8125b21 100644 --- a/9.webapp/app.py +++ b/9.webapp/app.py @@ -14,15 +14,10 @@ import streamlit as st from app_utils import ( clean_label, - compute_single_pca, generate_random_palette, latent_load_data, - load_data, - load_model_data, - make_dropdown_pca_with_selection, make_radar, place_labels_polar, - single_load_data, spider_load_data, truncate_label, ) diff --git a/9.webapp/data/CRISPRGeneEffect.parquet b/9.webapp/data/CRISPRGeneEffect.parquet deleted file mode 100644 index e82ecea..0000000 --- a/9.webapp/data/CRISPRGeneEffect.parquet +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:7122ad47501a6bda0f8c98d0109e04a3c7aaa29d92624bad2ca38c6abed2f4d5 -size 203238901 diff --git 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zj*EMQaiFt}`Zk77fG5M>*vrMw&6nXF=E?9=_j0k>G?OR9%_cl(gD&0MRn@}F)!&@N z(Zha)LtS+ls~CFv;igvfAcn4Sq?@62*bFTbTV=PIJa#HtL2fq6A+{<%`P4(Nc#-l-c9uk5qabg48+9KS6$_?|pX)3wYikR` z4OX7s9)FYDHGl?~x(6K-swJ4@To*~U7^-azY*`Y^UBhZ0=}S#C1- zp4HR8kljVac)PugsnRc9E4$e0sQHINK@d~x`WBS^u{;V5myI@x%-#@2Ex*0KM>+ND= ztz>6o;pJwi|A!rUScZ8LoBMyd^3~BZx6+@@Z|~>p>tbl(@uzy3n=9#u&&uzwLu`}S zpYosD*Uvu4Ma4kL)aT#I;^$(h<>jVl_e;THv~sgB7{oBCI}`5Qm= zf3&N;UwEjUt+|TnPuuycT^f@7hT&SaL`Mui10~X)Ogn#TrC;}q#*FS5ex{_o43u0{ z88bR1b{S6c7?bwiHfzVEEy%TTs9VIWZK~MY8b>&+2p7md|!C9Y4pVd8~ zO#CGwU^nyo^W&+<_`STr&q4t+34bbYGZX%A?VZq#n313GC(igM{V@7Wg=d)0)`wi` z{G$JN`HW`r{oxmW75T}3?OKYs6w^6ydx(3mf-94$F#AA}`t`t&`uQl4nCXoF@khxg LXStZsEtLNYwV!Bu literal 130 zcmWN?%MrpL5CG77s-OV_yZqA)3yUzLk`c_o>h)dT#qZh2OSHAlc}RKh>-MN~|KC2e z=kb*D Date: Thu, 18 Jun 2026 21:44:01 -0600 Subject: [PATCH 13/25] revert 0.data-download changes; clean up webapp dead code MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Revert all changes to 0.data-download — the DepMap version update belongs in a separate PR since it requires re-running all downstream analysis. Remove dead functions from app_utils.py (load_data, single_load_data, compute_single_pca, load_model_data, make_dropdown_pca_with_selection) that referenced the CRISPR files no longer used by the webapp. Remove unused imports from app.py and app_utils.py (ipywidgets, sklearn, numpy, os, plotly.subplots). Co-Authored-By: Claude Sonnet 4.6 --- 0.data-download/1.data_downloader.ipynb | 31 +- .../2.construct_gene_dictionary.ipynb | 114 +++---- 0.data-download/scripts/1.data_downloader.py | 61 +--- .../scripts/2.construct_gene_dictionary.py | 72 +++-- 9.webapp/app.py | 16 +- 9.webapp/app_utils.py | 291 +----------------- 6 files changed, 137 insertions(+), 448 deletions(-) diff --git a/0.data-download/1.data_downloader.ipynb b/0.data-download/1.data_downloader.ipynb index 6928843..a30f5f3 100644 --- a/0.data-download/1.data_downloader.ipynb +++ b/0.data-download/1.data_downloader.ipynb @@ -25,9 +25,8 @@ "source": [ "import pathlib\n", "import urllib.request\n", - "from pathlib import Path\n", - "\n", "import pandas as pd\n", + "from pathlib import Path\n", "import pyarrow as pa" ] }, @@ -58,8 +57,8 @@ " \"46489732\": \"Model.csv\",\n", " \"46489063\": \"CRISPRGeneEffect_Uncorrected.csv\",\n", " \"46489021\": \"CRISPRGeneDependency.csv\",\n", - " \"29094531\": \"depmap_gene_meta.tsv\",\n", - " # DepMap, Broad (2024). DepMap 24Q2 Public. Figshare+. Dataset. https://doi.org/10.25452/figshare.plus.25880521.v1\n", + " \"29094531\": \"depmap_gene_meta.tsv\"\n", + " # DepMap, Broad (2024). DepMap 24Q2 Public. Figshare+. Dataset. https://doi.org/10.25452/figshare.plus.25880521.v1\n", "}" ] }, @@ -108,22 +107,22 @@ "metadata": {}, "outputs": [], "source": [ - "# Column name correction for CRISPRGeneEffect\n", + "#Column name correction for CRISPRGeneEffect\n", "df = pd.read_csv(\"../0.data-download/data/CRISPRGeneEffect_Uncorrected.csv\")\n", - "df = df.rename(columns={df.columns[0]: \"ModelID\"})\n", - "filepath = Path(\"../0.data-download/data/CRISPRGeneEffect.csv\")\n", - "filepath.parent.mkdir(parents=True, exist_ok=True)\n", + "df = df.rename(columns={df.columns[0]:'ModelID'})\n", + "filepath = Path('../0.data-download/data/CRISPRGeneEffect.csv')\n", + "filepath.parent.mkdir(parents=True, exist_ok=True) \n", "\n", "df.to_csv(filepath, index=False)" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ - "# Convert to parquet\n", + "#Convert to parquet\n", "# List of CSV files\n", "\n", "data_directory = \"../0.data-download/data/\"\n", @@ -138,22 +137,22 @@ "for csv_file in csv_files:\n", " # Read the CSV file\n", " df = pd.read_csv(csv_file)\n", - "\n", + " \n", " # Define the output Parquet file name\n", - " parquet_file = csv_file.with_suffix(\".parquet\")\n", - "\n", + " parquet_file = csv_file.with_suffix('.parquet')\n", + " \n", " # Save the DataFrame as a Parquet file\n", " df.to_parquet(parquet_file, index=False)\n", "\n", "meta_df = pd.read_csv(metadata_file, sep=\"\\t\")\n", - "meta_parquet = metadata_file.with_suffix(\".parquet\")\n", + "meta_parquet = metadata_file.with_suffix('.parquet')\n", "meta_df.to_parquet(meta_parquet, index=False)" ] } ], "metadata": { "kernelspec": { - "display_name": "abstract_embedding", + "display_name": "base", "language": "python", "name": "python3" }, @@ -167,7 +166,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.14" + "version": "3.12.5" } }, "nbformat": 4, diff --git a/0.data-download/2.construct_gene_dictionary.ipynb b/0.data-download/2.construct_gene_dictionary.ipynb index a1795e7..972825a 100644 --- a/0.data-download/2.construct_gene_dictionary.ipynb +++ b/0.data-download/2.construct_gene_dictionary.ipynb @@ -35,19 +35,18 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 29, "id": "44a48da1-2987-4778-b38d-75ad13ed4f82", "metadata": {}, "outputs": [], "source": [ "import pathlib\n", - "\n", "import pandas as pd" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 30, "id": "a4994c02-29ed-4c75-b4eb-9f1f67f33bc8", "metadata": {}, "outputs": [], @@ -62,7 +61,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 31, "id": "665885c5-cbfa-445e-a08c-cc00e1f5051f", "metadata": {}, "outputs": [ @@ -282,7 +281,7 @@ "[5 rows x 18444 columns]" ] }, - "execution_count": 3, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" } @@ -297,7 +296,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 32, "id": "3203bcb5-bfe2-4d7e-8171-b0f94034b47d", "metadata": {}, "outputs": [ @@ -458,7 +457,7 @@ "2 https://www.ncbi.nlm.nih.gov/gene/?term=16 80.0 False " ] }, - "execution_count": 4, + "execution_count": 32, "metadata": {}, "output_type": "execute_result" } @@ -485,7 +484,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 33, "id": "fd813eb6-a3cd-4d60-84de-b552655c3344", "metadata": {}, "outputs": [ @@ -525,66 +524,67 @@ " \n", " \n", " 0\n", - " 55957\n", - " LIN37 (55957)\n", - " LIN37\n", + " 51126\n", + " NAA20 (51126)\n", + " NAA20\n", " \n", " \n", " 1\n", - " 79980\n", - " DSN1 (79980)\n", - " DSN1\n", + " 51550\n", + " CINP (51550)\n", + " CINP\n", " \n", " \n", " 2\n", - " 5922\n", - " RASA2 (5922)\n", - " RASA2\n", + " 56984\n", + " PSMG2 (56984)\n", + " PSMG2\n", " \n", " \n", " 3\n", - " 4221\n", - " MEN1 (4221)\n", - " MEN1\n", + " 9550\n", + " ATP6V1G1 (9550)\n", + " ATP6V1G1\n", " \n", " \n", " 4\n", - " 3364\n", - " HUS1 (3364)\n", - " HUS1\n", + " 79084\n", + " WDR77 (79084)\n", + " WDR77\n", " \n", " \n", "\n", "" ], "text/plain": [ - " entrezgene Name symbol\n", - "0 55957 LIN37 (55957) LIN37\n", - "1 79980 DSN1 (79980) DSN1\n", - "2 5922 RASA2 (5922) RASA2\n", - "3 4221 MEN1 (4221) MEN1\n", - "4 3364 HUS1 (3364) HUS1" + " entrezgene Name symbol\n", + "0 51126 NAA20 (51126) NAA20\n", + "1 51550 CINP (51550) CINP\n", + "2 56984 PSMG2 (56984) PSMG2\n", + "3 9550 ATP6V1G1 (9550) ATP6V1G1\n", + "4 79084 WDR77 (79084) WDR77" ] }, - "execution_count": 5, + "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Recode column names to entrez ids from dependency file\n", - "entrez_genes = [\n", - " x[1].strip(\")\").strip() for x in dependency_df.iloc[:, 1:].columns.str.split(\"(\")\n", - "]\n", + "entrez_genes = [x[1].strip(\")\").strip() for x in dependency_df.iloc[:, 1:].columns.str.split(\"(\")]\n", "\n", "# Obtain intersection of entrez gene ids\n", - "entrez_intersection = list(set(gene_meta_df.entrezgene).intersection(set(entrez_genes)))\n", + "entrez_intersection = list(\n", + " set(gene_meta_df.entrezgene).intersection(set(entrez_genes))\n", + ")\n", "\n", "print(f\"The number of overlapping entrez gene ids: {len(entrez_intersection)}\")\n", "\n", "# Subset the gene metadata file to only those in common, which are ones that passed qc\n", "gene_passed_qc_df = (\n", - " gene_meta_df.query(\"entrezgene in @entrez_intersection\")\n", + " gene_meta_df\n", + " .query(\"entrezgene in @entrez_intersection\")\n", " .set_index(\"entrezgene\")\n", " .reindex(entrez_intersection)\n", " .reset_index()\n", @@ -609,7 +609,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 34, "id": "c5eff9ef-a686-4c28-9968-19dffcc7f9f3", "metadata": {}, "outputs": [ @@ -690,19 +690,21 @@ "4 127550 A3GALT2 A3GALT2 (127550)" ] }, - "execution_count": 6, + "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "entrez_genes = [\n", - " x[1].strip(\")\").strip() for x in dependency_df.iloc[:, 1:].columns.str.split(\"(\")\n", - "]\n", - "symbol_genes = [x[0].strip() for x in dependency_df.iloc[:, 1:].columns.str.split(\"(\")]\n", + "entrez_genes = [x[1].strip(\")\").strip() for x in dependency_df.iloc[:, 1:].columns.str.split(\"(\")]\n", + "symbol_genes = [x[0].strip() for x in dependency_df.iloc[:,1:].columns.str.split(\"(\")]\n", "\n", "gene_dictionary_df = pd.DataFrame(\n", - " [entrez_genes, symbol_genes, dependency_df.iloc[:, 1:].columns.tolist()]\n", + " [\n", + " entrez_genes,\n", + " symbol_genes,\n", + " dependency_df.iloc[:,1:].columns.tolist()\n", + " ]\n", ").transpose()\n", "\n", "gene_dictionary_df.columns = [\"entrez_id\", \"symbol_id\", \"dependency_column\"]\n", @@ -722,7 +724,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 35, "id": "88749f9d-99b9-461a-9998-5f17fd55ab71", "metadata": {}, "outputs": [], @@ -733,7 +735,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 36, "id": "171b6309-9d4e-4f54-a4e6-0c85cdc83b12", "metadata": {}, "outputs": [ @@ -816,7 +818,7 @@ "2 2 A2M A2M (2) False True False" ] }, - "execution_count": 8, + "execution_count": 36, "metadata": {}, "output_type": "execute_result" } @@ -828,7 +830,7 @@ " gene_passed_qc_df,\n", " left_on=\"entrez_id\",\n", " right_on=\"entrezgene\",\n", - " how=\"left\", # Note the left merge, to retain all genes from gene_dictionary_df\n", + " how=\"left\" # Note the left merge, to retain all genes from gene_dictionary_df\n", " )\n", " # Select only certain columns\n", " .loc[:, [\"entrez_id\", \"symbol_id\", \"dependency_column\", \"entrezgene\"]]\n", @@ -839,18 +841,20 @@ ")\n", "\n", "# Convert genes with entrez entries to those that indicate QC pass\n", - "gene_dictionary_qc_df.loc[gene_dictionary_qc_df.qc_pass_pan != False, \"qc_pass_pan\"] = (\n", - " True\n", - ")\n", + "gene_dictionary_qc_df.loc[gene_dictionary_qc_df.qc_pass_pan != False, \"qc_pass_pan\"] = True\n", "\n", "# Create the qc_pass_other column\n", - "gene_dictionary_qc_df = gene_dictionary_qc_df.assign(\n", - " qc_pass_other=~gene_dictionary_qc_df.symbol_id.str.contains(qc_fail_other_genes)\n", + "gene_dictionary_qc_df = (\n", + " gene_dictionary_qc_df.assign(\n", + " qc_pass_other=~gene_dictionary_qc_df.symbol_id.str.contains(qc_fail_other_genes)\n", + " )\n", ")\n", "\n", "# Create qc_pass summary column\n", - "gene_dictionary_qc_df = gene_dictionary_qc_df.assign(\n", - " qc_pass=(gene_dictionary_qc_df.qc_pass_pan & gene_dictionary_qc_df.qc_pass_other)\n", + "gene_dictionary_qc_df = (\n", + " gene_dictionary_qc_df.assign(\n", + " qc_pass=(gene_dictionary_qc_df.qc_pass_pan & gene_dictionary_qc_df.qc_pass_other)\n", + " )\n", ")\n", "\n", "# Output file\n", @@ -865,7 +869,7 @@ ], "metadata": { "kernelspec": { - "display_name": "abstract_embedding", + "display_name": "gene_dependency_representations", "language": "python", "name": "python3" }, @@ -879,7 +883,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.14" + "version": "3.12.4" } }, "nbformat": 4, diff --git a/0.data-download/scripts/1.data_downloader.py b/0.data-download/scripts/1.data_downloader.py index b04b731..6034848 100644 --- a/0.data-download/scripts/1.data_downloader.py +++ b/0.data-download/scripts/1.data_downloader.py @@ -2,25 +2,22 @@ # coding: utf-8 # ## Download Dependency Data -# +# # Source: [Cancer Dependency Map resource](https://depmap.org/portal/download/). -# +# # - `CRISPRGeneDependency.parquet`: The data in this document describes the probability that a gene knockdown has an effect on cell-inhibition or death. These probabilities are derived from the data contained in CRISPRGeneEffect.parquet using methods described [here](https://doi.org/10.1101/720243) # - `Model.parquet`: Metadata for all of DepMap’s cancer models/cell lines. # - `CRISPRGeneEffect.parquet`: The data in this document are the Gene Effect Scores obtained from CRISPR knockout screens conducted by the Broad Institute. Negative scores notate that cell growth inhibition and/or death occurred following a gene knockout. Information on how these Gene Effect Scores were determined can be found [here](https://genomebiology.biomedcentral.com/articles/10.1186/s13059-021-02540-7) # - `depmap_gene_meta.tsv`: Genes that passed QC and were included in the training model for Pan et al. 2022. We use this data to filter genes as input to our models. The genes were filtered based 1) variance, 2) perturbation confidence, and 3) high on target predictions based on high correlation across other guides. -# -# >Tsherniak A, Vazquez F, Montgomery PG, Weir BA, Kryukov G, Cowley GS, Gill S, Harrington WF, Pantel S, Krill-Burger JM, Meyers RM, Ali L, Goodale A, Lee Y, Jiang G, Hsiao J, Gerath WFJ, Howell S, Merkel E, Ghandi M, Garraway LA, Root DE, Golub TR, Boehm JS, Hahn WC. Defining a Cancer Dependency Map. Cell. 2017 Jul 27;170(3):564-576. +# +# > Pan J, Kwon JJ, Talamas JA, Borah AA, Vazquez F, Boehm JS, Tsherniak A, Zitnik M, McFarland JM, Hahn WC. Sparse dictionary learning recovers pleiotropy from human cell fitness screens. Cell Syst. 2022 Apr 20;13(4):286-303.e10. doi: 10.1016/j.cels.2021.12.005. Epub 2022 Jan 31. PMID: 35085500; PMCID: PMC9035054. # In[1]: import pathlib import urllib.request -from pathlib import Path -import pandas as pd -import pyarrow as pa # In[2]: @@ -40,11 +37,10 @@ def download_dependency_data(figshare_id, figshare_url, output_file): figshare_url = "https://ndownloader.figshare.com/files/" download_dict = { - "46489732": "Model.csv", - "46489063": "CRISPRGeneEffect_Uncorrected.csv", - "46489021": "CRISPRGeneDependency.csv", - "29094531": "depmap_gene_meta.tsv", - # DepMap, Broad (2024). DepMap 24Q2 Public. Figshare+. Dataset. https://doi.org/10.25452/figshare.plus.25880521.v1 + "40448549": "CRISPRGeneDependency.parquet", + "40448555": "CRISPRGeneEffect.parquet", + "40448834": "Model.parquet", + "29094531": "depmap_gene_meta.tsv", # Data from Pan et al. 2022 } @@ -69,44 +65,3 @@ def download_dependency_data(figshare_id, figshare_url, output_file): figshare_id=figshare_id, figshare_url=figshare_url, output_file=output_file ) - -# In[6]: - - -# Column name correction for CRISPRGeneEffect -df = pd.read_csv("../0.data-download/data/CRISPRGeneEffect_Uncorrected.csv") -df = df.rename(columns={df.columns[0]: "ModelID"}) -filepath = Path("../0.data-download/data/CRISPRGeneEffect.csv") -filepath.parent.mkdir(parents=True, exist_ok=True) - -df.to_csv(filepath, index=False) - - -# In[7]: - - -# Convert to parquet -# List of CSV files - -data_directory = "../0.data-download/data/" -model_file = pathlib.Path(data_directory, "Model.csv").resolve() -effect_data_file = pathlib.Path(data_directory, "CRISPRGeneEffect.csv").resolve() -dependency_file = pathlib.Path(data_directory, "CRISPRGeneDependency.csv").resolve() -metadata_file = pathlib.Path(data_directory, "depmap_gene_meta.tsv").resolve() - -csv_files = [model_file, effect_data_file, dependency_file] - -# Convert each CSV to Parquet -for csv_file in csv_files: - # Read the CSV file - df = pd.read_csv(csv_file) - - # Define the output Parquet file name - parquet_file = csv_file.with_suffix(".parquet") - - # Save the DataFrame as a Parquet file - df.to_parquet(parquet_file, index=False) - -meta_df = pd.read_csv(metadata_file, sep="\t") -meta_parquet = metadata_file.with_suffix(".parquet") -meta_df.to_parquet(meta_parquet, index=False) diff --git a/0.data-download/scripts/2.construct_gene_dictionary.py b/0.data-download/scripts/2.construct_gene_dictionary.py index 6fc7019..c3806d9 100644 --- a/0.data-download/scripts/2.construct_gene_dictionary.py +++ b/0.data-download/scripts/2.construct_gene_dictionary.py @@ -2,25 +2,25 @@ # coding: utf-8 # ## Construct gene dictionary -# +# # The column names of the gene dependency files are of the format "gene symbol (entrez id)". -# +# # Additionally, the `depmap_gene_meta.tsv` contains genes that passed an initial QC (see Pan et al. 2022). -# +# # This notebook will create a six column matrix that separates symbol from entrez id, retains the original column name, two columns of if the gene passed two different QC, and a QC summary column. -# +# # Example: -# +# # | entrez_id | symbol_id | dependency_column | qc_pass_pan | qc_pass_other | qc_pass | # | :-------: | :-------: | :---------------: | :---------: | :-----------: | :-----: | # | 1 | A1BG |A1BG (1)| True | True | True | # | 29974 | A1CF | A1CF (29974) | True | False | False | # | 2 | A2M | A2M (2) | False | True | False | -# +# # *Note, the example qc_pass column above is an example and may not reflect truth.* -# +# # ### Quality control columns -# +# # - `qc_pass_pan` refers to the genes QC'd by Pan et al. 2022 # - `qc_pass_other` refers to gene families filtered by saturated signals # - RPL - Ribosomal proteins (including mitochondrial) @@ -31,9 +31,9 @@ import pathlib - import pandas as pd + # In[2]: @@ -42,14 +42,14 @@ dependency_file = pathlib.Path(f"{base_dir}/CRISPRGeneEffect.parquet") qc_gene_file = pathlib.Path(f"{base_dir}/depmap_gene_meta.tsv") -output_gene_dict_file = pathlib.Path(f"{base_dir}/CRISPR_gene_dictionary.parquet") +output_gene_dict_file = pathlib.Path(f"{base_dir}/CRISPR_gene_dictionary.tsv") # In[3]: # Load gene dependency data -dependency_df = pd.read_parquet(dependency_file) +dependency_df = pd.read_parquet(dependency_file, index_col=0) print(dependency_df.shape) dependency_df.head() @@ -59,7 +59,7 @@ # Load depmap metadata -gene_meta_df = pd.read_csv(qc_gene_file, sep="\t") +gene_meta_df = pd.read_parquet(qc_gene_file, sep="\t") gene_meta_df.entrezgene = gene_meta_df.entrezgene.astype(str) print(gene_meta_df.shape) @@ -67,25 +67,26 @@ # ## Obtain the intersection of the genes -# +# # Comparing the current DepMap release and the previous gene set qc (19Q2 depmap release) # In[5]: # Recode column names to entrez ids from dependency file -entrez_genes = [ - x[1].strip(")").strip() for x in dependency_df.iloc[:, 1:].columns.str.split("(") -] +entrez_genes = [x[1].strip(")").strip() for x in dependency_df.iloc[:, 1:].columns.str.split("(")] # Obtain intersection of entrez gene ids -entrez_intersection = list(set(gene_meta_df.entrezgene).intersection(set(entrez_genes))) +entrez_intersection = list( + set(gene_meta_df.entrezgene).intersection(set(entrez_genes)) +) print(f"The number of overlapping entrez gene ids: {len(entrez_intersection)}") # Subset the gene metadata file to only those in common, which are ones that passed qc gene_passed_qc_df = ( - gene_meta_df.query("entrezgene in @entrez_intersection") + gene_meta_df + .query("entrezgene in @entrez_intersection") .set_index("entrezgene") .reindex(entrez_intersection) .reset_index() @@ -96,7 +97,7 @@ # ## Convert the initial dependency map input file to three parts -# +# # 1. Entrez ID # 2. Symbol # 3. The full column name @@ -104,13 +105,15 @@ # In[6]: -entrez_genes = [ - x[1].strip(")").strip() for x in dependency_df.iloc[:, 1:].columns.str.split("(") -] -symbol_genes = [x[0].strip() for x in dependency_df.iloc[:, 1:].columns.str.split("(")] +entrez_genes = [x[1].strip(")").strip() for x in dependency_df.columns.str.split("(")] +symbol_genes = [x[0].strip() for x in dependency_df.columns.str.split("(")] gene_dictionary_df = pd.DataFrame( - [entrez_genes, symbol_genes, dependency_df.iloc[:, 1:].columns.tolist()] + [ + entrez_genes, + symbol_genes, + dependency_df.columns.tolist() + ] ).transpose() gene_dictionary_df.columns = ["entrez_id", "symbol_id", "dependency_column"] @@ -137,7 +140,7 @@ gene_passed_qc_df, left_on="entrez_id", right_on="entrezgene", - how="left", # Note the left merge, to retain all genes from gene_dictionary_df + how="left" # Note the left merge, to retain all genes from gene_dictionary_df ) # Select only certain columns .loc[:, ["entrez_id", "symbol_id", "dependency_column", "entrezgene"]] @@ -148,24 +151,27 @@ ) # Convert genes with entrez entries to those that indicate QC pass -gene_dictionary_qc_df.loc[gene_dictionary_qc_df.qc_pass_pan != False, "qc_pass_pan"] = ( - True -) +gene_dictionary_qc_df.loc[gene_dictionary_qc_df.qc_pass_pan != False, "qc_pass_pan"] = True # Create the qc_pass_other column -gene_dictionary_qc_df = gene_dictionary_qc_df.assign( - qc_pass_other=~gene_dictionary_qc_df.symbol_id.str.contains(qc_fail_other_genes) +gene_dictionary_qc_df = ( + gene_dictionary_qc_df.assign( + qc_pass_other=~gene_dictionary_qc_df.symbol_id.str.contains(qc_fail_other_genes) + ) ) # Create qc_pass summary column -gene_dictionary_qc_df = gene_dictionary_qc_df.assign( - qc_pass=(gene_dictionary_qc_df.qc_pass_pan & gene_dictionary_qc_df.qc_pass_other) +gene_dictionary_qc_df = ( + gene_dictionary_qc_df.assign( + qc_pass=(gene_dictionary_qc_df.qc_pass_pan & gene_dictionary_qc_df.qc_pass_other) + ) ) # Output file -gene_dictionary_qc_df.to_parquet(output_gene_dict_file, index=False) +gene_dictionary_qc_df.to_parquet(output_gene_dict_file, index=False, sep="\t") print(gene_dictionary_qc_df.qc_pass.value_counts()) print(gene_dictionary_qc_df.shape) gene_dictionary_qc_df.head(3) + diff --git a/9.webapp/app.py b/9.webapp/app.py index 8125b21..005810a 100644 --- a/9.webapp/app.py +++ b/9.webapp/app.py @@ -2,33 +2,21 @@ Gene Process Dependency Explorer """ -import os import pathlib import textwrap import matplotlib.pyplot as plt -import numpy as np import pandas as pd import plotly.express as px import plotly.graph_objects as go import streamlit as st from app_utils import ( - clean_label, - generate_random_palette, latent_load_data, make_radar, - place_labels_polar, spider_load_data, - truncate_label, ) -from plotly.subplots import make_subplots -from sklearn.decomposition import PCA -from sklearn.preprocessing import StandardScaler - -BASE_DIR = pathlib.Path(os.path.dirname(os.path.abspath(__file__))) -REPO_DIR = BASE_DIR.parent -print(f"Base directory: {BASE_DIR}") -print(f"Repository directory: {REPO_DIR}") + +BASE_DIR = pathlib.Path(__file__).parent # ── Page config ─────────────────────────────────────────────────────────────── st.set_page_config( diff --git a/9.webapp/app_utils.py b/9.webapp/app_utils.py index 4696c1d..132e5b3 100644 --- a/9.webapp/app_utils.py +++ b/9.webapp/app_utils.py @@ -4,43 +4,17 @@ import random import textwrap -import ipywidgets as widgets import matplotlib.pyplot as plt import numpy as np import pandas as pd -import plotly.express as px -import plotly.graph_objs as go import streamlit as st -from ipywidgets import widgets -from sklearn.decomposition import PCA -# Go up one level to repo root, then into data/ BASE_DIR = pathlib.Path(os.path.dirname(os.path.abspath(__file__))) -REPO_ROOT = BASE_DIR.parent # goes up from 9.webapp/ to repo root -print(f"Base directory: {BASE_DIR}") -print(f"Repo root: {REPO_ROOT}") - - -# ── Load & filter data ──────────────────────────────────────────────────────── -@st.cache_data -def load_data(): - # Load dependency data - data_directory = BASE_DIR / "data" - dependency_file = data_directory / "CRISPRGeneEffect.parquet" - gene_dict_file = data_directory / "CRISPR_gene_dictionary.parquet" - cancer_type_input_file = BASE_DIR / "data" / "Model.parquet" - dependency_df, gene_dict_df = load_model_data(dependency_file, gene_dict_file) - dependency_df = dependency_df.set_index("ModelID") - cancer_type_input_file = pathlib.Path(f"{BASE_DIR}/data/Model.parquet") - cancer_type_df = pd.read_parquet(cancer_type_input_file) +REPO_ROOT = BASE_DIR.parent @st.cache_data def latent_load_data(): - # latent space data - cancer_type_input_file = BASE_DIR / "data" / "Model.parquet" - cancer_type_df = pd.read_parquet(cancer_type_input_file) - reactome_dims = ( REPO_ROOT / "5.drug-dependency" / "results" / "all_reactome_results.parquet" ) @@ -48,15 +22,11 @@ def latent_load_data(): REPO_ROOT / "5.drug-dependency" / "results" / "all_corum_results.parquet" ) drug_dims = REPO_ROOT / "5.drug-dependency" / "results" / "all_drug_results.parquet" - reactome_df = pd.read_parquet(reactome_dims) + reactome_df = pd.read_parquet(reactome_dims) corum_df = pd.read_parquet(corum_dims) - drug_df = pd.read_parquet(drug_dims) - # Step 2: Subset based on matching keys - subset_keys = ["model", "latent_dim_total", "init", "z"] - # Replace latent identifiers with pathway reactome_df["feature"] = reactome_df["reactome_pathway"] reactome_df = reactome_df.drop( columns=["model", "latent_dim_total", "init", "seed", "z", "reactome_pathway"] @@ -71,16 +41,12 @@ def latent_load_data(): drug_df = drug_df.drop( columns=["model", "latent_dim_total", "init", "seed", "z", "name"] ) - drug_df_sorted = drug_df.sort_values( - by=["OncotreePrimaryDisease", "ModelID", "feature"], ascending=True - ) - # Create a unique column name by combining feature and source + meta_cols = ["ModelID", "OncotreePrimaryDisease"] reactome_meta = reactome_df[meta_cols].drop_duplicates() corum_meta = corum_df[meta_cols].drop_duplicates() drug_meta = drug_df[meta_cols].drop_duplicates() - # Pivot to wide format reactome_matrix = reactome_df.pivot( index="ModelID", columns="feature", values="latent_score" ) @@ -91,7 +57,6 @@ def latent_load_data(): index="ModelID", columns="feature", values="latent_score" ) - # Join metadata back to each matrix reactome_matrix = reactome_matrix.merge(reactome_meta, on="ModelID", how="left") corum_matrix = corum_matrix.merge(corum_meta, on="ModelID", how="left") drug_matrix = drug_matrix.merge(drug_meta, on="ModelID", how="left") @@ -99,27 +64,8 @@ def latent_load_data(): return reactome_matrix, corum_matrix, drug_matrix -@st.cache_data -def single_load_data(): - - # Load dependency data - data_directory = BASE_DIR / "data" - dependency_file = data_directory / "CRISPRGeneEffect.parquet" - gene_dict_file = data_directory / "CRISPR_gene_dictionary.parquet" - cancer_type_input_file = BASE_DIR / "data" / "Model.parquet" - dependency_df, gene_dict_df = load_model_data(dependency_file, gene_dict_file) - dependency_df = dependency_df.set_index("ModelID") - cancer_type_input_file = pathlib.Path(f"{BASE_DIR}/data/Model.parquet") - cancer_type_df = pd.read_parquet(cancer_type_input_file) - combined_df = dependency_df.merge( - cancer_type_df[["ModelID", "OncotreePrimaryDisease"]], on="ModelID", how="left" - ) - return combined_df - - @st.cache_data def spider_load_data(): - # model_ids = ["ACH-000323", "ACH-002083", "ACH-002228"] files = { "Reactome Pathways": REPO_ROOT / "5.drug-dependency" @@ -134,7 +80,6 @@ def spider_load_data(): / "results" / "all_drug_results.parquet", } - # Adjust these if your column names differ feature_colnames = { "Reactome Pathways": "reactome_pathway", "CORUM Complexes": "reactome_pathway", @@ -142,12 +87,6 @@ def spider_load_data(): } score_col = "pathway_score" - model_colors = { - "ACH-000323": "#00FFFF", # cyan - "ACH-002083": "#FF69B4", # pink - "ACH-002228": "#800080", # purple - } - global_max = 0 dfs = {} for name, file in files.items(): @@ -160,17 +99,10 @@ def spider_load_data(): def clean_label(x: str) -> str: - """ - Clean or override specific long labels before truncation. - """ - # Polymerase switching if "Polymerase Switching" in x: return "Polymerase Switching" - - # Negative MET regulation if "Negative Regulation Of MET" in x or "Negative Regulation of MET" in x: return "Negative MET Regulation" - return truncate_label(x) @@ -180,64 +112,39 @@ def truncate_label( max_total_words: int = 4, max_lines: int = 2, ) -> str: - """ - Truncate a label according to character and line limits. - """ words = label.split() short = " ".join(words[:max_total_words]) - - # Wrap lines = textwrap.wrap(short, width=max_chars_per_line) - - # clamp to max lines if len(lines) > max_lines: lines = lines[:max_lines] - wrapped = "\n".join(lines) - - # Determine if truncated if len(words) > max_total_words or ( len(lines) >= max_lines and len(lines) < len(textwrap.wrap(short, width=max_chars_per_line)) ): wrapped += "..." - return wrapped def place_labels_polar(ax, angles, labels, radius: float) -> None: - """ - Place labels around a polar plot at a given radius. - """ for angle, label in zip(angles[:-1], labels): - r = radius - - # left / right alignment if 0 <= angle <= np.pi / 2 or 3 * np.pi / 2 <= angle <= 2 * np.pi: ha = "left" else: ha = "right" - ax.text( - angle, r, label, fontsize=9, color="black", ha=ha, va="center", wrap=True + angle, radius, label, fontsize=9, color="black", ha=ha, va="center", wrap=True ) - return None - def generate_random_palette(num_colors, seed=12): - # Generate random colors with varied lightness and saturation random.seed(seed) - colors = [] - for _ in range(num_colors): - h = random.random() # Random hue between 0 and 1 - l = random.uniform(0.2, 0.8) # Lightness between 0.3 and 0.9 for contrast - s = random.uniform(0.5, 1.0) # Saturation between 0.6 and 1.0 for vivid colors - color = colorsys.hls_to_rgb(h, l, s) # Convert HLS to RGB color - colors.append(color) - + h = random.random() + l = random.uniform(0.2, 0.8) + s = random.uniform(0.5, 1.0) + colors.append(colorsys.hls_to_rgb(h, l, s)) return colors @@ -257,19 +164,15 @@ def make_radar( num_circles: int = 5, max_processes: int = None, ) -> None: - """ - Draw a radar plot on an existing polar matplotlib axis. - """ if model_ids == ["ACH-000323", "ACH-002083", "ACH-002228"]: model_colors = { - "ACH-000323": "#00FFFF", # cyan - "ACH-002083": "#FF69B4", # pink - "ACH-002228": "#800080", # purple + "ACH-000323": "#00FFFF", + "ACH-002083": "#FF69B4", + "ACH-002228": "#800080", } else: model_colors = generate_model_color_map(model_ids, seed=12) - # Top 5 per model, union of all top_by_model = ( df.groupby("ModelID", group_keys=False) .apply(lambda x: x.nlargest(5, score_col)) @@ -281,196 +184,30 @@ def make_radar( n_vars = len(top_features) labels = [clean_label(x) for x in top_features] - # Angles angles = np.linspace(0, 2 * np.pi, n_vars, endpoint=False).tolist() angles += [angles[0]] - # Reference circles circle_levels = np.linspace(0, global_max, num_circles + 1)[1:] for r in circle_levels: - circle_vals = [r] * (n_vars + 1) ax.plot( - angles, circle_vals, color="grey", linestyle="--", linewidth=1, zorder=0 + angles, [r] * (n_vars + 1), color="grey", linestyle="--", linewidth=1, zorder=0 ) - # Plot each model + for mid in model_ids: subset = df[df["ModelID"] == mid] - merged = pd.DataFrame({feature_col: top_features}).merge( subset[[feature_col, score_col]], on=feature_col, how="left" ) - values = merged[score_col].fillna(0).tolist() values += [values[0]] - ax.plot(angles, values, color=model_colors[mid], linewidth=3, label=mid) ax.scatter( angles, values, color=model_colors[mid], s=30, edgecolor="black", zorder=5 ) - # Axis styling ax.set_ylim(0, global_max * 1.25) ax.set_xticks([]) ax.set_yticks([]) ax.set_aspect("equal") - - # Labels - label_radius = global_max * 1.4 - place_labels_polar(ax, angles, labels, label_radius) - - # Title + place_labels_polar(ax, angles, labels, global_max * 1.4) ax.set_title(title, fontsize=18, pad=30, fontweight="bold", y=1) - - return None - - -def make_dropdown_pca_with_selection(df, title="PCA Interactive Plot"): - out = widgets.Output() # Create a fresh output for this plot! - - # Prepare PCA input - pca_input = df.drop( - columns=["OncotreePrimaryDisease", "source", "ModelID"], errors="ignore" - ).fillna(0) - pca = PCA(n_components=2, random_state=0) - embedding = pca.fit_transform(pca_input) - - # Add PCA coordinates to the dataframe - df["PCA1"] = embedding[:, 0] - df["PCA2"] = embedding[:, 1] - - # Prepare color map for each cancer type - cancer_types = df["OncotreePrimaryDisease"].unique() - color_map = ( - px.colors.qualitative.Plotly - + px.colors.qualitative.Light24 - + px.colors.qualitative.Dark24 - ) - highlight_color_map = { - cancer: color_map[i % len(color_map)] for i, cancer in enumerate(cancer_types) - } - - # Create one trace per cancer type - traces = [] - for cancer in cancer_types: - df_subset = df[df["OncotreePrimaryDisease"] == cancer] - trace = go.Scattergl( - x=df_subset["PCA1"], - y=df_subset["PCA2"], - mode="markers", - name=cancer, - marker=dict(size=7, color=highlight_color_map[cancer]), - text=[f"{cancer} | {model_id}" for model_id in df_subset["ModelID"]], - customdata=df_subset["ModelID"], # Attach ModelID to customdata - hoverinfo="text", - ) - traces.append(trace) - - # Dropdown buttons to highlight cancer types - dropdown_buttons = [] - for i, cancer in enumerate(cancer_types): - visibility = [True] * len(cancer_types) - colors = ["lightgrey"] * len(cancer_types) - colors[i] = highlight_color_map[cancer] - - button = dict( - method="update", - label=cancer, - args=[ - { - "visible": visibility, - "marker": [{"color": colors[j]} for j in range(len(cancer_types))], - }, - {"title": f"PCA Highlighted: {cancer}"}, - ], - ) - dropdown_buttons.append(button) - - # Default color button - default_colors = [highlight_color_map[cancer] for cancer in cancer_types] - - fig = go.Figure(data=traces) - - for i, trace in enumerate(fig.data): - trace.marker.color = default_colors[i] - - fig.update_layout( - title=title, - xaxis_title="PCA1", - yaxis_title="PCA2", - updatemenus=[ - { - "direction": "down", - "showactive": True, - "x": 1.15, - "xanchor": "left", - "y": 1.15, - "yanchor": "top", - } - ], - dragmode="lasso", # Ensure Lasso is enabled - width=1500, - height=800, - ) - - return fig, out # Return both the figure and the output widget for selection - - -@st.cache_data -def compute_single_pca(selected_diseases: tuple) -> pd.DataFrame: - """Cache PCA result per disease selection.""" - combined_df = single_load_data() - combined_df = combined_df[ - combined_df["OncotreePrimaryDisease"].isin(selected_diseases) - ] - gene_cols = combined_df.columns.drop(["ModelID", "OncotreePrimaryDisease"]) - pca_input = combined_df[gene_cols].apply(pd.to_numeric, errors="coerce") - pca = PCA(n_components=2, random_state=0) - pca_embedding = pca.fit_transform(pca_input) - combined_df = combined_df[["ModelID", "OncotreePrimaryDisease"]].copy() - combined_df["PCA1"] = pca_embedding[:, 0] - combined_df["PCA2"] = pca_embedding[:, 1] - return combined_df - - -def load_model_data(dependency_file, gene_dict_file): - """ - Load and preprocess gene dependency data and gene dictionary. - - Parameters: - - dependency_file (str): Path to the gene dependency data file. - - gene_dict_file (str): Path to the gene dictionary file. - - Returns: - - dependency_df (DataFrame): Preprocessed gene dependency data. - - gene_dict_df (DataFrame): Preprocessed gene dictionary. - """ - # Load gene dependency data - dependency_df = pd.read_parquet(dependency_file) - - print(dependency_df.shape) - dependency_df.head(3) - - # Load gene dictionary and filter by QC - gene_dict_df = ( - pd.read_parquet(gene_dict_file).query("qc_pass").reset_index(drop=True) - ) - gene_dict_df.entrez_id = gene_dict_df.entrez_id.astype(str) - - # Recode column names to entrez ids - entrez_genes = [ - x[1].strip(")").strip() - for x in dependency_df.iloc[:, 1:].columns.str.split("(") - ] - entrez_intersection = list( - set(gene_dict_df.entrez_id).intersection(set(entrez_genes)) - ) - - gene_dict_df = gene_dict_df.set_index("entrez_id").reindex(entrez_intersection) - - # Subset dependencies to the genes that passed QC - dependency_df.columns = ["ModelID"] + entrez_genes - dependency_df = dependency_df.loc[:, ["ModelID"] + gene_dict_df.index.tolist()] - dependency_df.columns = ["ModelID"] + gene_dict_df.symbol_id.tolist() - dependency_df = dependency_df.dropna(axis="columns") - - return dependency_df, gene_dict_df From d20ef8a12af1a992417a8711d330533ca382f8f1 Mon Sep 17 00:00:00 2001 From: Gregory Way Date: Thu, 18 Jun 2026 21:45:51 -0600 Subject: [PATCH 14/25] remove stale download_data.sh from 0.data-download This script was added in the webapp branch but copies CRISPR files into 9.webapp/data/ which are now gitignored and no longer needed by the app. Co-Authored-By: Claude Sonnet 4.6 --- 0.data-download/download_data.sh | 23 ----------------------- 1 file changed, 23 deletions(-) delete mode 100644 0.data-download/download_data.sh diff --git a/0.data-download/download_data.sh b/0.data-download/download_data.sh deleted file mode 100644 index f4801bd..0000000 --- a/0.data-download/download_data.sh +++ /dev/null @@ -1,23 +0,0 @@ -#!/bin/bash - -# shellcheck disable=SC2035 -jupyter nbconvert --to=script --FilesWriter.build_directory=scripts/ *.ipynb - -# check if the data are present -# if not then run the download scripts -# if data are present then skip the download scripts -if [ ! -f "data/Model.parquet" ]; then - echo "Data files not found. Running data download scripts..." - - uv run python scripts/1.data_downloader.py - uv run python scripts/2.construct_gene_dictionary.py - - echo "Data download and processing complete." -else - echo "Data files already exist. Skipping data download." -fi - - -cp data/Model.parquet ../9.webapp/data/Model.parquet -cp data/CRISPRGeneEffect.parquet ../9.webapp/data/CRISPRGeneEffect.parquet -cp data/CRISPR_gene_dictionary.parquet ../9.webapp/data/CRISPR_gene_dictionary.parquet From c01664ff292bba1fe0c98c455f3e0fd9550c97b7 Mon Sep 17 00:00:00 2001 From: Gregory Way Date: Thu, 18 Jun 2026 21:56:41 -0600 Subject: [PATCH 15/25] webapp gardening: clean deps, lint, update README, remove Justfile MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - Delete requirements.txt — pip freeze from Mike's machine with a hardcoded absolute path; uv.lock handles reproducible installs - Delete Justfile — thin wrappers around uv with no added value; raw uv commands are documented in README instead - Trim pyproject.toml: remove scikit-learn, umap-learn, ipywidgets, ipykernel — no longer used after dead code removal - Fix ruff issues in app_utils.py: remove unused matplotlib.pyplot import, rename ambiguous variable l → lightness, simplify BASE_DIR - Expand README webapp section: uv setup, deploy usage, data file table, note on raw DepMap files not required by the webapp Co-Authored-By: Claude Sonnet 4.6 --- 9.webapp/Justfile | 18 ------------------ 9.webapp/app_utils.py | 8 +++----- 9.webapp/pyproject.toml | 8 ++------ README.md | 42 ++++++++++++++++++++++++++++++++++++----- 4 files changed, 42 insertions(+), 34 deletions(-) delete mode 100644 9.webapp/Justfile diff --git a/9.webapp/Justfile b/9.webapp/Justfile deleted file mode 100644 index 8980fd7..0000000 --- a/9.webapp/Justfile +++ /dev/null @@ -1,18 +0,0 @@ -set shell := ["bash", "-eu", "-o", "pipefail", "-c"] - -default: - just --list - -download-data: - python download_data.py - -create-uv-env: - uv venv .venv ; uv sync - -build: - uv run streamlit run app.py - -deploy: - PORT="${PORT:-8501}" uv run streamlit run app.py --server.address 0.0.0.0 --server.headless true --server.port "$PORT" --server.fileWatcherType none - -all: create-uv-env build diff --git a/9.webapp/app_utils.py b/9.webapp/app_utils.py index 132e5b3..7c9d2a4 100644 --- a/9.webapp/app_utils.py +++ b/9.webapp/app_utils.py @@ -1,15 +1,13 @@ import colorsys -import os import pathlib import random import textwrap -import matplotlib.pyplot as plt import numpy as np import pandas as pd import streamlit as st -BASE_DIR = pathlib.Path(os.path.dirname(os.path.abspath(__file__))) +BASE_DIR = pathlib.Path(__file__).parent REPO_ROOT = BASE_DIR.parent @@ -142,9 +140,9 @@ def generate_random_palette(num_colors, seed=12): colors = [] for _ in range(num_colors): h = random.random() - l = random.uniform(0.2, 0.8) + lightness = random.uniform(0.2, 0.8) s = random.uniform(0.5, 1.0) - colors.append(colorsys.hls_to_rgb(h, l, s)) + colors.append(colorsys.hls_to_rgb(h, lightness, s)) return colors diff --git a/9.webapp/pyproject.toml b/9.webapp/pyproject.toml index 2cc26b7..a4a933c 100644 --- a/9.webapp/pyproject.toml +++ b/9.webapp/pyproject.toml @@ -11,13 +11,9 @@ dependencies = [ "streamlit", "plotly", "pandas", - "numpy", - "scikit-learn", "pyarrow", - "umap-learn", - "matplotlib>=3.10.9", - "ipykernel>=7.2.0", - "ipywidgets>=8.1.8", + "matplotlib", + "numpy", ] [tool.setuptools] diff --git a/README.md b/README.md index af72e8d..16801b1 100644 --- a/README.md +++ b/README.md @@ -54,14 +54,46 @@ conda activate gene_dependency_representations ## Webapp -This repository now includes a Streamlit dashboard for interactive exploration of the parquet-backed plot outputs in `9.webapp/`. +An interactive Streamlit dashboard for exploring gene dependency outputs lives in [`9.webapp/`](9.webapp/). +It is self-contained with its own `uv`-managed environment — no conda setup required. -Run it from the repository root after activating the environment: +### Prerequisites + +Install [`uv`](https://docs.astral.sh/uv/getting-started/installation/) if you don't have it: ```sh -just run +curl -LsSf https://astral.sh/uv/install.sh | sh ``` -Use `just build` to syntax-check the app and `just deploy` to run Streamlit in headless mode on port `8501` by default. +### Run locally + +```sh +cd 9.webapp +uv run streamlit run app.py +``` + +`uv` will create a virtual environment and install all dependencies automatically on first run. + +### Deploy (headless) + +```sh +cd 9.webapp +just deploy +``` + +This runs Streamlit on `0.0.0.0:8501` by default. Override the port with `PORT=8080 just deploy`. + +### Data + +The webapp reads pre-computed result files that are committed to the repository: + +| File | Description | +| :--- | :---------- | +| `9.webapp/data/Model.parquet` | DepMap cell line metadata | +| `9.webapp/data/pca_embeddings_single_dependencies.parquet` | PCA of raw gene dependency scores | +| `9.webapp/data/pca_embeddings_latent_reactome.parquet` | PCA of Reactome latent scores | +| `9.webapp/data/pca_embeddings_latent_corum.parquet` | PCA of CORUM latent scores | +| `9.webapp/data/pca_embeddings_latent_drug.parquet` | PCA of drug latent scores | +| `5.drug-dependency/results/all_*_results.parquet` | Full latent score tables (scores + spider plots) | -The dashboard currently exposes the Reactome, CORUM, and Drug result tables with toggleable Projection, Radar, and Heatmap views. +Raw DepMap files (`CRISPRGeneEffect.parquet` etc.) are **not** required by the webapp and are gitignored. Download them separately via [`0.data-download/`](0.data-download/) if you need to re-run the analysis pipeline. From 670f0e11a9ce53a535d27a35c40b2ff107f10349 Mon Sep 17 00:00:00 2001 From: Gregory Way Date: Thu, 18 Jun 2026 22:03:19 -0600 Subject: [PATCH 16/25] make webapp self-contained and HF Spaces ready Copy all_reactome/corum/drug_results.parquet into 9.webapp/data/ so the app no longer depends on the repo directory structure above 9.webapp/. Update app_utils.py to read all data from DATA_DIR (BASE_DIR/data). Add 9.webapp/README.md with Hugging Face Spaces frontmatter, tab descriptions, local run instructions, and data file table. Update root README.md with HF Spaces link and simplified webapp section. Co-Authored-By: Claude Sonnet 4.6 --- 9.webapp/README.md | 92 +++++++++++++++++++++ 9.webapp/app_utils.py | 27 ++---- 9.webapp/data/all_corum_results.parquet | Bin 0 -> 1739705 bytes 9.webapp/data/all_drug_results.parquet | Bin 0 -> 4275240 bytes 9.webapp/data/all_reactome_results.parquet | Bin 0 -> 7107699 bytes README.md | 34 +++----- 6 files changed, 111 insertions(+), 42 deletions(-) create mode 100644 9.webapp/README.md create mode 100644 9.webapp/data/all_corum_results.parquet create mode 100644 9.webapp/data/all_drug_results.parquet create mode 100644 9.webapp/data/all_reactome_results.parquet diff --git a/9.webapp/README.md b/9.webapp/README.md new file mode 100644 index 0000000..5e38040 --- /dev/null +++ b/9.webapp/README.md @@ -0,0 +1,92 @@ +--- +title: Gene Process Dependency Explorer +emoji: 🧬 +colorFrom: blue +colorTo: green +sdk: streamlit +sdk_version: 1.58.0 +app_file: app.py +pinned: true +license: bsd-3-clause +--- + +# Gene Process Dependency Explorer + +An interactive Streamlit dashboard for exploring gene process dependencies across cancer types, built on [DepMap](https://depmap.org) data and latent representations learned by a Beta Variational Autoencoder (BVAE). + +This app accompanies the paper: + +> **Discovering multivariate gene vulnerability patterns in cancer using latent representations of gene dependencies** +> WayScience · [GitHub](https://github.com/WayScience/gene_dependency_representations) + +--- + +## What the app shows + +The dashboard has six tabs: + +| Tab | Description | +| :-- | :---------- | +| **Welcome** | Overview and links | +| **Single dependency plots** | PCA of raw CRISPR gene dependency scores across all cell lines; filter by cancer type | +| **Latent plots** | PCA of VAE latent representations for Reactome, CORUM, and Drug subsets | +| **Spider plots** | Radar charts of biological process dependency profiles per cell line or cancer type | +| **Top scores** | Heatmaps and bar charts of highest-scoring processes by cancer type and model ID | +| **Data table** | Searchable table of all cell lines and their primary diseases | + +--- + +## Running locally + +The webapp is self-contained with its own [`uv`](https://docs.astral.sh/uv/)-managed environment. + +### Prerequisites + +```sh +curl -LsSf https://astral.sh/uv/install.sh | sh +``` + +### Start the app + +```sh +cd 9.webapp +uv run streamlit run app.py +``` + +`uv` creates and populates the virtual environment automatically on first run. The app will be available at `http://localhost:8501`. + +### Deploy headless (e.g. on a server) + +```sh +cd 9.webapp +PORT=8501 uv run streamlit run app.py \ + --server.address 0.0.0.0 \ + --server.headless true \ + --server.port "$PORT" \ + --server.fileWatcherType none +``` + +--- + +## Data + +All data files are committed to the repository — no external downloads needed to run the app. + +| File | Size | Description | +| :--- | ---: | :---------- | +| `data/Model.parquet` | 188 KB | DepMap cell line metadata | +| `data/pca_embeddings_single_dependencies.parquet` | 34 KB | Pre-computed PCA of raw gene dependency scores | +| `data/pca_embeddings_latent_reactome.parquet` | 27 KB | Pre-computed PCA of Reactome latent scores | +| `data/pca_embeddings_latent_corum.parquet` | 27 KB | Pre-computed PCA of CORUM latent scores | +| `data/pca_embeddings_latent_drug.parquet` | 27 KB | Pre-computed PCA of drug latent scores | +| `data/all_reactome_results.parquet` | 1.7 MB | Full Reactome latent scores (spider + heatmap tabs) | +| `data/all_corum_results.parquet` | 1.7 MB | Full CORUM latent scores | +| `data/all_drug_results.parquet` | 4.1 MB | Full drug latent scores | + +Raw DepMap files (`CRISPRGeneEffect.parquet` etc.) are **not** required by the webapp and are gitignored. Download them via [`0.data-download/`](../0.data-download/) if you need to re-run the full analysis pipeline. + +--- + +## Repository structure + +This webapp lives in `9.webapp/` within the larger [gene_dependency_representations](https://github.com/WayScience/gene_dependency_representations) repository, which contains the full analysis pipeline from data download through VAE training to result generation. diff --git a/9.webapp/app_utils.py b/9.webapp/app_utils.py index 7c9d2a4..9d8a373 100644 --- a/9.webapp/app_utils.py +++ b/9.webapp/app_utils.py @@ -8,18 +8,14 @@ import streamlit as st BASE_DIR = pathlib.Path(__file__).parent -REPO_ROOT = BASE_DIR.parent +DATA_DIR = BASE_DIR / "data" @st.cache_data def latent_load_data(): - reactome_dims = ( - REPO_ROOT / "5.drug-dependency" / "results" / "all_reactome_results.parquet" - ) - corum_dims = ( - REPO_ROOT / "5.drug-dependency" / "results" / "all_corum_results.parquet" - ) - drug_dims = REPO_ROOT / "5.drug-dependency" / "results" / "all_drug_results.parquet" + reactome_dims = DATA_DIR / "all_reactome_results.parquet" + corum_dims = DATA_DIR / "all_corum_results.parquet" + drug_dims = DATA_DIR / "all_drug_results.parquet" reactome_df = pd.read_parquet(reactome_dims) corum_df = pd.read_parquet(corum_dims) @@ -65,18 +61,9 @@ def latent_load_data(): @st.cache_data def spider_load_data(): files = { - "Reactome Pathways": REPO_ROOT - / "5.drug-dependency" - / "results" - / "all_reactome_results.parquet", - "CORUM Complexes": REPO_ROOT - / "5.drug-dependency" - / "results" - / "all_corum_results.parquet", - "Drug Responses": REPO_ROOT - / "5.drug-dependency" - / "results" - / "all_drug_results.parquet", + "Reactome Pathways": DATA_DIR / "all_reactome_results.parquet", + "CORUM Complexes": DATA_DIR / "all_corum_results.parquet", + "Drug Responses": DATA_DIR / "all_drug_results.parquet", } feature_colnames = { "Reactome Pathways": "reactome_pathway", diff --git a/9.webapp/data/all_corum_results.parquet 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z^ugV5U$gu+lTY;z>!tc_mO9$!O&#&fa}$T z4)Z@suv&}cVGr6^Z$eqjyuE)^swa5E7}^nUPDS~^H3>i9mYaWiy1KrJ?Vqo!(el=f g<6Hhb%7 literal 0 HcmV?d00001 diff --git a/README.md b/README.md index 16801b1..22e0dff 100644 --- a/README.md +++ b/README.md @@ -55,45 +55,35 @@ conda activate gene_dependency_representations ## Webapp An interactive Streamlit dashboard for exploring gene dependency outputs lives in [`9.webapp/`](9.webapp/). -It is self-contained with its own `uv`-managed environment — no conda setup required. +It is self-contained with its own [`uv`](https://docs.astral.sh/uv/)-managed environment — no conda setup required. -### Prerequisites +A live version is hosted on Hugging Face Spaces: **[WayScience/gene-dependency-explorer](https://huggingface.co/spaces/WayScience/gene-dependency-explorer)** -Install [`uv`](https://docs.astral.sh/uv/getting-started/installation/) if you don't have it: +### Run locally ```sh +# Install uv if needed curl -LsSf https://astral.sh/uv/install.sh | sh -``` - -### Run locally -```sh cd 9.webapp uv run streamlit run app.py ``` -`uv` will create a virtual environment and install all dependencies automatically on first run. +`uv` creates and populates the virtual environment automatically on first run. ### Deploy (headless) ```sh cd 9.webapp -just deploy +PORT=8501 uv run streamlit run app.py \ + --server.address 0.0.0.0 \ + --server.headless true \ + --server.port "$PORT" \ + --server.fileWatcherType none ``` -This runs Streamlit on `0.0.0.0:8501` by default. Override the port with `PORT=8080 just deploy`. - ### Data -The webapp reads pre-computed result files that are committed to the repository: - -| File | Description | -| :--- | :---------- | -| `9.webapp/data/Model.parquet` | DepMap cell line metadata | -| `9.webapp/data/pca_embeddings_single_dependencies.parquet` | PCA of raw gene dependency scores | -| `9.webapp/data/pca_embeddings_latent_reactome.parquet` | PCA of Reactome latent scores | -| `9.webapp/data/pca_embeddings_latent_corum.parquet` | PCA of CORUM latent scores | -| `9.webapp/data/pca_embeddings_latent_drug.parquet` | PCA of drug latent scores | -| `5.drug-dependency/results/all_*_results.parquet` | Full latent score tables (scores + spider plots) | +All data files the webapp needs are committed in `9.webapp/data/` — no external downloads required. Raw DepMap files (`CRISPRGeneEffect.parquet` etc.) are gitignored and only needed to re-run the full analysis pipeline via [`0.data-download/`](0.data-download/). -Raw DepMap files (`CRISPRGeneEffect.parquet` etc.) are **not** required by the webapp and are gitignored. Download them separately via [`0.data-download/`](0.data-download/) if you need to re-run the analysis pipeline. +See [`9.webapp/README.md`](9.webapp/README.md) for full details. From f9ffaa8285424516800efcc143440e5f4e16faaa Mon Sep 17 00:00:00 2001 From: Gregory Way Date: Thu, 18 Jun 2026 22:16:55 -0600 Subject: [PATCH 17/25] add .hfignore and update README frontmatter for HF Spaces Docker/Streamlit Co-Authored-By: Claude Sonnet 4.6 --- 9.webapp/.hfignore | 5 +++++ 1 file changed, 5 insertions(+) create mode 100644 9.webapp/.hfignore diff --git a/9.webapp/.hfignore b/9.webapp/.hfignore new file mode 100644 index 0000000..910f6cf --- /dev/null +++ b/9.webapp/.hfignore @@ -0,0 +1,5 @@ +.venv/ +__pycache__/ +*.pyc +*.egg-info/ +.DS_Store From 9830a3cd50df9bca19e98a55b5d245c64cce19b7 Mon Sep 17 00:00:00 2001 From: Gregory Way Date: Thu, 18 Jun 2026 22:17:47 -0600 Subject: [PATCH 18/25] add HF Spaces update instructions to README Co-Authored-By: Claude Sonnet 4.6 --- README.md | 17 +++++++++++++++++ 1 file changed, 17 insertions(+) diff --git a/README.md b/README.md index 22e0dff..d6ef787 100644 --- a/README.md +++ b/README.md @@ -59,6 +59,23 @@ It is self-contained with its own [`uv`](https://docs.astral.sh/uv/)-managed env A live version is hosted on Hugging Face Spaces: **[WayScience/gene-dependency-explorer](https://huggingface.co/spaces/WayScience/gene-dependency-explorer)** +To update the Space after changes to `9.webapp/`, run: + +```sh +cd 9.webapp +hf upload WayScience/gene-dependency-explorer . . \ + --repo-type space \ + --exclude ".venv/**" \ + --exclude "**/__pycache__/**" \ + --exclude "**/*.pyc" \ + --exclude "**/*.egg-info/**" \ + --exclude "data/CRISPRGeneEffect.parquet" \ + --exclude "data/CRISPR_gene_dictionary.parquet" \ + --commit-message "your message here" +``` + +You will need the `hf` CLI installed and be logged in to the WayScience HF organization (`hf auth login`). + ### Run locally ```sh From c28a170f9a7e9bb8a7fa3871f1aebc888075cc2a Mon Sep 17 00:00:00 2001 From: Gregory Way Date: Thu, 18 Jun 2026 22:31:01 -0600 Subject: [PATCH 19/25] Add Dockerfile and README for HF Spaces Docker deployment Co-Authored-By: Claude Sonnet 4.6 --- 9.webapp/Dockerfile | 18 ++++++++++++++++++ 9.webapp/README.md | 5 ++--- 2 files changed, 20 insertions(+), 3 deletions(-) create mode 100644 9.webapp/Dockerfile diff --git a/9.webapp/Dockerfile b/9.webapp/Dockerfile new file mode 100644 index 0000000..64fb36d --- /dev/null +++ b/9.webapp/Dockerfile @@ -0,0 +1,18 @@ +FROM python:3.12-slim + +WORKDIR /app + +COPY --from=ghcr.io/astral-sh/uv:latest /uv /usr/local/bin/uv + +COPY pyproject.toml uv.lock ./ +RUN uv sync --frozen --no-dev + +COPY . . + +EXPOSE 7860 + +CMD ["uv", "run", "streamlit", "run", "app.py", \ + "--server.address", "0.0.0.0", \ + "--server.port", "7860", \ + "--server.headless", "true", \ + "--server.fileWatcherType", "none"] diff --git a/9.webapp/README.md b/9.webapp/README.md index 5e38040..7592a77 100644 --- a/9.webapp/README.md +++ b/9.webapp/README.md @@ -3,9 +3,8 @@ title: Gene Process Dependency Explorer emoji: 🧬 colorFrom: blue colorTo: green -sdk: streamlit -sdk_version: 1.58.0 -app_file: app.py +sdk: docker +app_port: 7860 pinned: true license: bsd-3-clause --- From a7d63b9b7b3577f1f89144d07530bed9f49b4ba1 Mon Sep 17 00:00:00 2001 From: Gregory Way Date: Thu, 18 Jun 2026 22:31:50 -0600 Subject: [PATCH 20/25] Add HF Spaces badge to root README Co-Authored-By: Claude Sonnet 4.6 --- README.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/README.md b/README.md index d6ef787..fe9a03c 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,7 @@ # Gene Dependency Representations +[![Hugging Face Spaces](https://img.shields.io/badge/🤗%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/WayScience/gene-dependency-explorer) + ## Goal Current cancer treatments tend to be toxic and leave patients with lifelong side-effects. From d148713e82d8fdcfb7a35ffe8d557be0787ae0e9 Mon Sep 17 00:00:00 2001 From: Gregory Way Date: Fri, 19 Jun 2026 05:35:15 -0600 Subject: [PATCH 21/25] Add GitHub Action to auto-deploy webapp to HF Spaces on main Co-Authored-By: Claude Sonnet 4.6 --- .github/workflows/deploy-space.yml | 33 ++++++++++++++++++++++++++++++ 1 file changed, 33 insertions(+) create mode 100644 .github/workflows/deploy-space.yml diff --git a/.github/workflows/deploy-space.yml b/.github/workflows/deploy-space.yml new file mode 100644 index 0000000..20cf6e2 --- /dev/null +++ b/.github/workflows/deploy-space.yml @@ -0,0 +1,33 @@ +name: Deploy to HF Spaces + +on: + push: + branches: [main] + paths: + - "9.webapp/**" + +jobs: + deploy: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + with: + lfs: true + + - name: Install huggingface_hub + run: pip install huggingface_hub + + - name: Push to HF Spaces + env: + HF_TOKEN: ${{ secrets.HF_TOKEN }} + run: | + cd 9.webapp + hf upload WayScience/gene-dependency-explorer . . \ + --repo-type space \ + --exclude ".venv/**" \ + --exclude "**/__pycache__/**" \ + --exclude "**/*.pyc" \ + --exclude "**/*.egg-info/**" \ + --exclude "data/CRISPRGeneEffect.parquet" \ + --exclude "data/CRISPR_gene_dictionary.parquet" \ + --commit-message "deploy from ${{ github.sha }}" From b84b9f45a22417fc816d30d65e9013e3e1fcb8f3 Mon Sep 17 00:00:00 2001 From: Gregory Way Date: Fri, 19 Jun 2026 05:39:26 -0600 Subject: [PATCH 22/25] Update READMEs to document auto-deploy via GitHub Actions Co-Authored-By: Claude Sonnet 4.6 --- 9.webapp/README.md | 26 +++++++++++++++++++++++++- README.md | 4 +++- 2 files changed, 28 insertions(+), 2 deletions(-) diff --git a/9.webapp/README.md b/9.webapp/README.md index 7592a77..b243444 100644 --- a/9.webapp/README.md +++ b/9.webapp/README.md @@ -82,7 +82,31 @@ All data files are committed to the repository — no external downloads needed | `data/all_corum_results.parquet` | 1.7 MB | Full CORUM latent scores | | `data/all_drug_results.parquet` | 4.1 MB | Full drug latent scores | -Raw DepMap files (`CRISPRGeneEffect.parquet` etc.) are **not** required by the webapp and are gitignored. Download them via [`0.data-download/`](../0.data-download/) if you need to re-run the full analysis pipeline. +Raw DepMap files (`CRISPRGeneEffect.parquet` etc.) are **not** required by the webapp and are gitignored. +Download them via [`0.data-download/`](../0.data-download/) if you need to re-run the full analysis pipeline. + +--- + +## Deployment + +The Space at [WayScience/gene-dependency-explorer](https://huggingface.co/spaces/WayScience/gene-dependency-explorer) deploys automatically via GitHub Actions whenever changes to `9.webapp/` are merged into `main`. See [`../.github/workflows/deploy-space.yml`](../.github/workflows/deploy-space.yml). + +To deploy manually: + +```sh +cd 9.webapp +hf upload WayScience/gene-dependency-explorer . . \ + --repo-type space \ + --exclude ".venv/**" \ + --exclude "**/__pycache__/**" \ + --exclude "**/*.pyc" \ + --exclude "**/*.egg-info/**" \ + --exclude "data/CRISPRGeneEffect.parquet" \ + --exclude "data/CRISPR_gene_dictionary.parquet" \ + --commit-message "your message here" +``` + +Requires the `hf` CLI and login to the WayScience org (`hf auth login`). --- diff --git a/README.md b/README.md index fe9a03c..e3fc543 100644 --- a/README.md +++ b/README.md @@ -61,7 +61,9 @@ It is self-contained with its own [`uv`](https://docs.astral.sh/uv/)-managed env A live version is hosted on Hugging Face Spaces: **[WayScience/gene-dependency-explorer](https://huggingface.co/spaces/WayScience/gene-dependency-explorer)** -To update the Space after changes to `9.webapp/`, run: +The Space deploys automatically via GitHub Actions whenever changes to `9.webapp/` are merged into `main` (see [`.github/workflows/deploy-space.yml`](.github/workflows/deploy-space.yml)). A `HF_TOKEN` secret with write access to the WayScience org must be set in the repo's GitHub Actions secrets. + +To deploy manually (e.g. for testing before a PR merges): ```sh cd 9.webapp From df8ddd42e1813a59c1c82eb40098be272be80800 Mon Sep 17 00:00:00 2001 From: Gregory Way Date: Fri, 19 Jun 2026 05:40:56 -0600 Subject: [PATCH 23/25] minor tweaks --- 9.webapp/README.md | 5 +++-- README.md | 7 +++---- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/9.webapp/README.md b/9.webapp/README.md index b243444..3f44643 100644 --- a/9.webapp/README.md +++ b/9.webapp/README.md @@ -89,7 +89,8 @@ Download them via [`0.data-download/`](../0.data-download/) if you need to re-ru ## Deployment -The Space at [WayScience/gene-dependency-explorer](https://huggingface.co/spaces/WayScience/gene-dependency-explorer) deploys automatically via GitHub Actions whenever changes to `9.webapp/` are merged into `main`. See [`../.github/workflows/deploy-space.yml`](../.github/workflows/deploy-space.yml). +The Space at [WayScience/gene-dependency-explorer](https://huggingface.co/spaces/WayScience/gene-dependency-explorer) deploys automatically via GitHub Actions whenever changes to `9.webapp/` are merged into `main`. +See [`../.github/workflows/deploy-space.yml`](../.github/workflows/deploy-space.yml). To deploy manually: @@ -112,4 +113,4 @@ Requires the `hf` CLI and login to the WayScience org (`hf auth login`). ## Repository structure -This webapp lives in `9.webapp/` within the larger [gene_dependency_representations](https://github.com/WayScience/gene_dependency_representations) repository, which contains the full analysis pipeline from data download through VAE training to result generation. +This webapp lives in `9.webapp/` within the larger [gene_dependency_representations](https://github.com/WayScience/gene_dependency_representations) repository, which contains the full BioBombe analysis and interpretation pipeline. diff --git a/README.md b/README.md index e3fc543..028093c 100644 --- a/README.md +++ b/README.md @@ -57,11 +57,12 @@ conda activate gene_dependency_representations ## Webapp An interactive Streamlit dashboard for exploring gene dependency outputs lives in [`9.webapp/`](9.webapp/). -It is self-contained with its own [`uv`](https://docs.astral.sh/uv/)-managed environment — no conda setup required. +It is self-contained with its own [`uv`](https://docs.astral.sh/uv/)-managed environment. A live version is hosted on Hugging Face Spaces: **[WayScience/gene-dependency-explorer](https://huggingface.co/spaces/WayScience/gene-dependency-explorer)** -The Space deploys automatically via GitHub Actions whenever changes to `9.webapp/` are merged into `main` (see [`.github/workflows/deploy-space.yml`](.github/workflows/deploy-space.yml)). A `HF_TOKEN` secret with write access to the WayScience org must be set in the repo's GitHub Actions secrets. +The Space deploys automatically via GitHub Actions whenever changes to `9.webapp/` are merged into `main` (see [`.github/workflows/deploy-space.yml`](.github/workflows/deploy-space.yml)). +A `HF_TOKEN` secret with write access to the WayScience org must be set in the repo's GitHub Actions secrets. To deploy manually (e.g. for testing before a PR merges): @@ -105,6 +106,4 @@ PORT=8501 uv run streamlit run app.py \ ### Data -All data files the webapp needs are committed in `9.webapp/data/` — no external downloads required. Raw DepMap files (`CRISPRGeneEffect.parquet` etc.) are gitignored and only needed to re-run the full analysis pipeline via [`0.data-download/`](0.data-download/). - See [`9.webapp/README.md`](9.webapp/README.md) for full details. From bae50c07ced9ab7bcaa7f727940190d084d79baf Mon Sep 17 00:00:00 2001 From: Gregory Way Date: Fri, 19 Jun 2026 05:50:07 -0600 Subject: [PATCH 24/25] =?UTF-8?q?Remove=20requirements.txt=20=E2=80=94=20p?= =?UTF-8?q?yproject.toml=20+=20uv.lock=20are=20authoritative?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Co-Authored-By: Claude Sonnet 4.6 --- 9.webapp/requirements.txt | 88 --------------------------------------- 1 file changed, 88 deletions(-) delete mode 100644 9.webapp/requirements.txt diff --git a/9.webapp/requirements.txt b/9.webapp/requirements.txt deleted file mode 100644 index 0c47f25..0000000 --- a/9.webapp/requirements.txt +++ /dev/null @@ -1,88 +0,0 @@ -altair==6.1.0 -anyio==4.13.0 -asttokens==3.0.1 -attrs==26.1.0 -blinker==1.9.0 -cachetools==7.1.4 -certifi==2026.5.20 -charset-normalizer==3.4.7 -click==8.4.1 -comm==0.2.3 -contourpy==1.3.3 -cycler==0.12.1 -debugpy==1.8.21 -decorator==5.3.1 -executing==2.2.1 -fonttools==4.63.0 --e file:///home/lippincm/gene-process-dependencies/9.webapp -gitdb==4.0.12 -gitpython==3.1.50 -h11==0.16.0 -httptools==0.8.0 -idna==3.18 -ipykernel==7.2.0 -ipython==9.14.1 -ipython-pygments-lexers==1.1.1 -ipywidgets==8.1.8 -itsdangerous==2.2.0 -jedi==0.20.0 -jinja2==3.1.6 -joblib==1.5.3 -jsonschema==4.26.0 -jsonschema-specifications==2025.9.1 -jupyter-client==8.9.0 -jupyter-core==5.9.1 -jupyterlab-widgets==3.0.16 -kiwisolver==1.5.0 -llvmlite==0.47.0 -markupsafe==3.0.3 -matplotlib==3.10.9 -matplotlib-inline==0.2.2 -narwhals==2.22.0 -nest-asyncio==1.6.0 -numba==0.65.1 -numpy==2.4.6 -packaging==26.2 -pandas==3.0.3 -parso==0.8.7 -pexpect==4.9.0 -pillow==12.2.0 -platformdirs==4.10.0 -plotly==6.8.0 -prompt-toolkit==3.0.52 -protobuf==7.35.0 -psutil==7.2.2 -ptyprocess==0.7.0 -pure-eval==0.2.3 -pyarrow==24.0.0 -pydeck==0.9.2 -pygments==2.20.0 -pynndescent==0.6.0 -pyparsing==3.3.2 -python-dateutil==2.9.0.post0 -python-multipart==0.0.32 -pyzmq==27.1.0 -referencing==0.37.0 -requests==2.34.2 -rpds-py==2026.5.1 -scikit-learn==1.9.0 -scipy==1.17.1 -six==1.17.0 -smmap==5.0.3 -stack-data==0.6.3 -starlette==1.2.1 -streamlit==1.58.0 -tenacity==9.1.4 -threadpoolctl==3.6.0 -toml==0.10.2 -tornado==6.5.7 -tqdm==4.67.3 -traitlets==5.15.1 -typing-extensions==4.15.0 -umap-learn==0.5.12 -urllib3==2.7.0 -uvicorn==0.49.0 -watchdog==6.0.0 -wcwidth==0.8.1 -websockets==16.0 -widgetsnbextension==4.0.15 From 356273001cb231fc29a6c8536b047106f387c5f2 Mon Sep 17 00:00:00 2001 From: Gregory Way Date: Fri, 19 Jun 2026 05:54:53 -0600 Subject: [PATCH 25/25] Move preprocessing.ipynb to 5.drug-dependency as notebook 9 Renamed and relocated the one-time PCA precomputation script that generated 9.webapp/data/pca_embeddings_*.parquet. Inlined the helper functions (load_model_data, single_load_data, latent_load_data) that were removed from app_utils.py, and added a deprecation note. Co-Authored-By: Claude Sonnet 4.6 --- .../9.precompute_webapp_pca_embeddings.ipynb | 238 +++++++ 9.webapp/preprocessing.ipynb | 634 ------------------ 2 files changed, 238 insertions(+), 634 deletions(-) create mode 100644 5.drug-dependency/9.precompute_webapp_pca_embeddings.ipynb delete mode 100644 9.webapp/preprocessing.ipynb diff --git a/5.drug-dependency/9.precompute_webapp_pca_embeddings.ipynb b/5.drug-dependency/9.precompute_webapp_pca_embeddings.ipynb new file mode 100644 index 0000000..6bfff51 --- /dev/null +++ b/5.drug-dependency/9.precompute_webapp_pca_embeddings.ipynb @@ -0,0 +1,238 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "notice-cell", + "metadata": {}, + "source": [ + "# Precompute PCA Embeddings for Webapp\n", + "\n", + "> **Note:** This notebook was a one-time preprocessing step run to generate the pre-computed PCA\n", + "> parquet files bundled with the `9.webapp/` Streamlit app. It is **not intended to be re-run**\n", + "> without modification.\n", + ">\n", + "> The helper functions below (`load_model_data`, `single_load_data`, `latent_load_data`) were\n", + "> originally defined in `9.webapp/app_utils.py` but were removed from the app once the pre-computed\n", + "> parquets replaced runtime PCA computation. They are reproduced here for provenance.\n", + ">\n", + "> **Dependencies that are no longer in the webapp environment:**\n", + "> - `CRISPRGeneEffect.parquet` and `CRISPR_gene_dictionary.parquet` (large gitignored DepMap files\n", + "> — download via `0.data-download/` first)\n", + "> - `sklearn` (`scikit-learn`) — not in `9.webapp/pyproject.toml`\n", + ">\n", + "> **Outputs** (written to `9.webapp/data/`):\n", + "> - `pca_embeddings_single_dependencies.parquet`\n", + "> - `pca_embeddings_latent_reactome.parquet`\n", + "> - `pca_embeddings_latent_corum.parquet`\n", + "> - `pca_embeddings_latent_drug.parquet`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6c08a8f0", + "metadata": {}, + "outputs": [], + "source": [ + "import pathlib\n", + "\n", + "import pandas as pd\n", + "from sklearn.decomposition import PCA" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "paths-cell", + "metadata": {}, + "outputs": [], + "source": [ + "# Paths — run from repo root or adjust accordingly\n", + "REPO_ROOT = pathlib.Path().resolve().parent # goes up from 5.drug-dependency/ to repo root\n", + "WEBAPP_DIR = REPO_ROOT / \"9.webapp\"\n", + "DATA_DIR = WEBAPP_DIR / \"data\"\n", + "RESULTS_DIR = REPO_ROOT / \"5.drug-dependency\" / \"results\"\n", + "\n", + "print(f\"Repo root: {REPO_ROOT}\")\n", + "print(f\"Webapp data: {DATA_DIR}\")\n", + "print(f\"Results dir: {RESULTS_DIR}\")" + ] + }, + { + "cell_type": "markdown", + "id": "helpers-header", + "metadata": {}, + "source": [ + "## Helper functions\n", + "\n", + "Originally from `9.webapp/app_utils.py`, reproduced here for provenance." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "load-model-data-cell", + "metadata": {}, + "outputs": [], + "source": [ + "def load_model_data(dependency_file, gene_dict_file):\n", + " \"\"\"Load and preprocess gene dependency data and gene dictionary.\"\"\"\n", + " dependency_df = pd.read_parquet(dependency_file)\n", + " print(dependency_df.shape)\n", + "\n", + " gene_dict_df = (\n", + " pd.read_parquet(gene_dict_file).query(\"qc_pass\").reset_index(drop=True)\n", + " )\n", + " gene_dict_df.entrez_id = gene_dict_df.entrez_id.astype(str)\n", + "\n", + " entrez_genes = [\n", + " x[1].strip(\")\").strip()\n", + " for x in dependency_df.iloc[:, 1:].columns.str.split(\"(\")\n", + " ]\n", + " entrez_intersection = list(\n", + " set(gene_dict_df.entrez_id).intersection(set(entrez_genes))\n", + " )\n", + " gene_dict_df = gene_dict_df.set_index(\"entrez_id\").reindex(entrez_intersection)\n", + "\n", + " dependency_df.columns = [\"ModelID\"] + entrez_genes\n", + " dependency_df = dependency_df.loc[:, [\"ModelID\"] + gene_dict_df.index.tolist()]\n", + " dependency_df.columns = [\"ModelID\"] + gene_dict_df.symbol_id.tolist()\n", + " dependency_df = dependency_df.dropna(axis=\"columns\")\n", + " return dependency_df, gene_dict_df" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "single-load-cell", + "metadata": {}, + "outputs": [], + "source": [ + "def single_load_data():\n", + " \"\"\"Load CRISPR gene dependency scores merged with cell line metadata.\"\"\"\n", + " dependency_file = DATA_DIR / \"CRISPRGeneEffect.parquet\"\n", + " gene_dict_file = DATA_DIR / \"CRISPR_gene_dictionary.parquet\"\n", + " cancer_type_input_file = DATA_DIR / \"Model.parquet\"\n", + "\n", + " dependency_df, _ = load_model_data(dependency_file, gene_dict_file)\n", + " dependency_df = dependency_df.set_index(\"ModelID\")\n", + " cancer_type_df = pd.read_parquet(cancer_type_input_file)\n", + " combined_df = dependency_df.merge(\n", + " cancer_type_df[[\"ModelID\", \"OncotreePrimaryDisease\"]], on=\"ModelID\", how=\"left\"\n", + " )\n", + " return combined_df" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "latent-load-cell", + "metadata": {}, + "outputs": [], + "source": [ + "def latent_load_data():\n", + " \"\"\"Load latent score parquets and pivot to wide format for PCA.\"\"\"\n", + " reactome_df = pd.read_parquet(RESULTS_DIR / \"all_reactome_results.parquet\")\n", + " corum_df = pd.read_parquet(RESULTS_DIR / \"all_corum_results.parquet\")\n", + " drug_df = pd.read_parquet(RESULTS_DIR / \"all_drug_results.parquet\")\n", + "\n", + " reactome_df[\"feature\"] = reactome_df[\"reactome_pathway\"]\n", + " reactome_df = reactome_df.drop(\n", + " columns=[\"model\", \"latent_dim_total\", \"init\", \"seed\", \"z\", \"reactome_pathway\"]\n", + " )\n", + " corum_df[\"feature\"] = corum_df[\"reactome_pathway\"]\n", + " corum_df = corum_df.drop(\n", + " columns=[\"model\", \"latent_dim_total\", \"init\", \"seed\", \"z\", \"reactome_pathway\"]\n", + " )\n", + " drug_df[\"feature\"] = drug_df[\"name\"]\n", + " drug_df = drug_df.drop(\n", + " columns=[\"model\", \"latent_dim_total\", \"init\", \"seed\", \"z\", \"name\"]\n", + " )\n", + "\n", + " meta_cols = [\"ModelID\", \"OncotreePrimaryDisease\"]\n", + " reactome_meta = reactome_df[meta_cols].drop_duplicates()\n", + " corum_meta = corum_df[meta_cols].drop_duplicates()\n", + " drug_meta = drug_df[meta_cols].drop_duplicates()\n", + "\n", + " reactome_matrix = reactome_df.pivot(\n", + " index=\"ModelID\", columns=\"feature\", values=\"latent_score\"\n", + " ).merge(reactome_meta, on=\"ModelID\", how=\"left\")\n", + " corum_matrix = corum_df.pivot(\n", + " index=\"ModelID\", columns=\"feature\", values=\"latent_score\"\n", + " ).merge(corum_meta, on=\"ModelID\", how=\"left\")\n", + " drug_matrix = drug_df.pivot(\n", + " index=\"ModelID\", columns=\"feature\", values=\"latent_score\"\n", + " ).merge(drug_meta, on=\"ModelID\", how=\"left\")\n", + "\n", + " return reactome_matrix, corum_matrix, drug_matrix" + ] + }, + { + "cell_type": "markdown", + "id": "pca-header", + "metadata": {}, + "source": [ + "## Compute and save PCA embeddings" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6cdc8f80", + "metadata": {}, + "outputs": [], + "source": [ + "def compute_pca(df, metadata_columns) -> pd.DataFrame:\n", + " print(df.shape[0], \"rows before dropping NA\")\n", + " df = df.dropna()\n", + " print(df.shape[0], \"rows after dropping NA\")\n", + " metadata_df = df[metadata_columns].copy()\n", + " feat_cols = df.columns.drop(metadata_columns)\n", + " if \"source\" in feat_cols:\n", + " feat_cols = feat_cols.drop(\"source\")\n", + " pca_input = df[feat_cols].apply(pd.to_numeric, errors=\"coerce\")\n", + " pca = PCA(n_components=2, random_state=0)\n", + " pca_embedding = pca.fit_transform(pca_input)\n", + " metadata_df[\"PCA1\"] = pca_embedding[:, 0]\n", + " metadata_df[\"PCA2\"] = pca_embedding[:, 1]\n", + " return metadata_df" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "run-pca-cell", + "metadata": {}, + "outputs": [], + "source": [ + "combined_df = single_load_data()\n", + "reactome_matrix, corum_matrix, drug_matrix = latent_load_data()\n", + "\n", + "pca_single_df = compute_pca(combined_df, [\"ModelID\", \"OncotreePrimaryDisease\"])\n", + "pca_latent_reactome_df = compute_pca(reactome_matrix, [\"OncotreePrimaryDisease\", \"ModelID\"])\n", + "pca_latent_corum_df = compute_pca(corum_matrix, [\"OncotreePrimaryDisease\", \"ModelID\"])\n", + "pca_latent_drug_df = compute_pca(drug_matrix, [\"OncotreePrimaryDisease\", \"ModelID\"])\n", + "\n", + "pca_single_df.to_parquet(DATA_DIR / \"pca_embeddings_single_dependencies.parquet\")\n", + "pca_latent_reactome_df.to_parquet(DATA_DIR / \"pca_embeddings_latent_reactome.parquet\")\n", + "pca_latent_corum_df.to_parquet(DATA_DIR / \"pca_embeddings_latent_corum.parquet\")\n", + "pca_latent_drug_df.to_parquet(DATA_DIR / \"pca_embeddings_latent_drug.parquet\")\n", + "\n", + "print(\"Done — parquets written to\", DATA_DIR)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "name": "python", + "version": "3.12.0" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/9.webapp/preprocessing.ipynb b/9.webapp/preprocessing.ipynb deleted file mode 100644 index 675b571..0000000 --- a/9.webapp/preprocessing.ipynb +++ /dev/null @@ -1,634 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 2, - "id": "6c08a8f0", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2026-06-09 13:29:16.828 WARNING streamlit.runtime.caching.cache_data_api: No runtime found, using MemoryCacheStorageManager\n", - "2026-06-09 13:29:16.829 WARNING streamlit.runtime.caching.cache_data_api: No runtime found, using MemoryCacheStorageManager\n", - "2026-06-09 13:29:16.830 WARNING streamlit.runtime.caching.cache_data_api: No runtime found, using MemoryCacheStorageManager\n", - "2026-06-09 13:29:16.830 WARNING streamlit.runtime.caching.cache_data_api: No runtime found, using MemoryCacheStorageManager\n", - "2026-06-09 13:29:16.831 WARNING streamlit.runtime.caching.cache_data_api: No runtime found, using MemoryCacheStorageManager\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Base directory: /home/lippincm/gene-process-dependencies/9.webapp\n", - "Repo root: /home/lippincm/gene-process-dependencies\n" - ] - } - ], - "source": [ - "import os\n", - "import pathlib\n", - "\n", - "import numpy as np\n", - "import pandas as pd\n", - "import streamlit as st\n", - "from app_utils import latent_load_data, load_model_data, single_load_data\n", - "from sklearn.decomposition import PCA" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "328325ad", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2026-06-09 13:29:16.839 WARNING streamlit.runtime.caching.cache_data_api: No runtime found, using MemoryCacheStorageManager\n", - "2026-06-09 13:29:16.840 WARNING streamlit.runtime.scriptrunner_utils.script_run_context: Thread 'MainThread': missing ScriptRunContext! This warning can be ignored when running in bare mode.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Base directory: /home/lippincm/gene-process-dependencies/9.webapp\n", - "Repo root: /home/lippincm/gene-process-dependencies\n" - ] - } - ], - "source": [ - "_base_reactome, _base_corum, _base_drug = latent_load_data()\n", - "ALL_DISEASES = sorted(_base_reactome[\"OncotreePrimaryDisease\"].unique().tolist())\n", - "ALL_MODEL_IDS = sorted(_base_reactome[\"ModelID\"].unique().tolist())\n", - "# Go up one level to repo root, then into data/\n", - "BASE_DIR = pathlib.Path().resolve()\n", - "REPO_ROOT = BASE_DIR.parent\n", - "REPO_ROOT = BASE_DIR.parent # goes up from 9.webapp/ to repo root\n", - "print(f\"Base directory: {BASE_DIR}\")\n", - "print(f\"Repo root: {REPO_ROOT}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 46, - "id": "37924565", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(1150, 18444)\n" - ] - } - ], - "source": [ - "combined_df = single_load_data()\n", - "data_directory = BASE_DIR / \"data\"\n", - "dependency_file = data_directory / \"CRISPRGeneEffect.parquet\"\n", - "gene_dict_file = data_directory / \"CRISPR_gene_dictionary.parquet\"\n", - "cancer_type_input_file = BASE_DIR / \"data\" / \"Model.parquet\"\n", - "dependency_df, gene_dict_df = load_model_data(dependency_file, gene_dict_file)\n", - "dependency_df = dependency_df.set_index(\"ModelID\")\n", - "cancer_type_input_file = pathlib.Path(f\"{BASE_DIR}/data/Model.parquet\")\n", - "cancer_type_df = pd.read_parquet(cancer_type_input_file)\n", - "reactome_matrix, corum_matrix, drug_matrix = latent_load_data()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "0ef7365a", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 63, - "id": "4f84dac0", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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      ModelIDOncotreePrimaryDiseaselatent_scoregsea_es_scorepathway_scorefeature
      0ACH-000001Ovarian Epithelial Tumor0.3928600.8243150.392860Inactivation, Recovery And Regulation Of Photo...
      1ACH-000001Ovarian Epithelial Tumor0.7636300.8801160.763630Elastic Fibre Formation R-HSA-1566948
      2ACH-000001Ovarian Epithelial Tumor0.4355310.8395060.435531Mismatch Repair (MMR) Directed By MSH2:MSH6 (M...
      3ACH-000001Ovarian Epithelial Tumor0.531491-0.7333750.531491Processive Synthesis On Lagging Strand R-HSA-6...
      4ACH-000001Ovarian Epithelial Tumor0.2677500.8642570.267750Mismatch Repair (MMR) Directed By MSH2:MSH3 (M...
      .....................
      169777ACH-003012Non-Small Cell Lung Cancer0.5052960.9382710.505296Kinase maturation complex 1 (human)
      169778ACH-003012Non-Small Cell Lung Cancer0.2826340.8082170.282634immunoproteasome (mouse)
      169779ACH-003012Non-Small Cell Lung Cancer0.0736970.7480240.073697ALL-1 supercomplex (human)
      169780ACH-003012Non-Small Cell Lung Cancer0.0329450.7396780.032945Emerin complex 32 (human)
      169781ACH-003012Non-Small Cell Lung Cancer0.2832630.8150850.283263Ikaros complex (mouse)
      \n", - "

      169782 rows × 6 columns

      \n", - "
      " - ], - "text/plain": [ - " ModelID OncotreePrimaryDisease latent_score gsea_es_score \\\n", - "0 ACH-000001 Ovarian Epithelial Tumor 0.392860 0.824315 \n", - "1 ACH-000001 Ovarian Epithelial Tumor 0.763630 0.880116 \n", - "2 ACH-000001 Ovarian Epithelial Tumor 0.435531 0.839506 \n", - "3 ACH-000001 Ovarian Epithelial Tumor 0.531491 -0.733375 \n", - "4 ACH-000001 Ovarian Epithelial Tumor 0.267750 0.864257 \n", - "... ... ... ... ... \n", - "169777 ACH-003012 Non-Small Cell Lung Cancer 0.505296 0.938271 \n", - "169778 ACH-003012 Non-Small Cell Lung Cancer 0.282634 0.808217 \n", - "169779 ACH-003012 Non-Small Cell Lung Cancer 0.073697 0.748024 \n", - "169780 ACH-003012 Non-Small Cell Lung Cancer 0.032945 0.739678 \n", - "169781 ACH-003012 Non-Small Cell Lung Cancer 0.283263 0.815085 \n", - "\n", - " pathway_score feature \n", - "0 0.392860 Inactivation, Recovery And Regulation Of Photo... \n", - "1 0.763630 Elastic Fibre Formation R-HSA-1566948 \n", - "2 0.435531 Mismatch Repair (MMR) Directed By MSH2:MSH6 (M... \n", - "3 0.531491 Processive Synthesis On Lagging Strand R-HSA-6... \n", - "4 0.267750 Mismatch Repair (MMR) Directed By MSH2:MSH3 (M... \n", - "... ... ... \n", - "169777 0.505296 Kinase maturation complex 1 (human) \n", - "169778 0.282634 immunoproteasome (mouse) \n", - "169779 0.073697 ALL-1 supercomplex (human) \n", - "169780 0.032945 Emerin complex 32 (human) \n", - "169781 0.283263 Ikaros complex (mouse) \n", - "\n", - "[169782 rows x 6 columns]" - ] - }, - "execution_count": 63, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "corum_matrix_path = (\n", - " REPO_ROOT / \"5.drug-dependency\" / \"results\" / \"all_corum_results.parquet\"\n", - ")\n", - "corum_matrix = pd.read_parquet(corum_matrix_path)\n", - "corum_matrix[\"feature\"] = corum_matrix[\"reactome_pathway\"]\n", - "corum_matrix = corum_matrix.drop(\n", - " columns=[\"model\", \"latent_dim_total\", \"init\", \"seed\", \"z\", \"reactome_pathway\"]\n", - ")\n", - "meta_cols = [\"ModelID\", \"OncotreePrimaryDisease\"]\n", - "\n", - "corum_meta = corum_matrix[meta_cols].drop_duplicates()\n", - "\n", - "# corum_matrix = corum_matrix.pivot(index=\"ModelID\", columns=\"feature\", values=\"latent_score\")\n", - "# corum_matrix = corum_matrix.merge(corum_meta, on=\"ModelID\", how=\"left\")\n", - "# print(corum_matrix.isna().sum().sum())\n", - "# corum_matrix.drop(columns=['gsea_es_score',\"pathway_score\",\"OncotreePrimaryDisease\"], inplace=True)\n", - "# corum_matrix.pivot(index=\"ModelID\", columns=\"feature\", values=\"latent_score\")\n", - "corum_matrix" - ] - }, - { - "cell_type": "code", - "execution_count": 61, - "id": "0f7fe22e", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Inactivation, Recovery And Regulation Of Phototransduction Cascade R-HSA-2514859\n", - "Elastic Fibre Formation R-HSA-1566948\n", - "Mismatch Repair (MMR) Directed By MSH2:MSH6 (MutSalpha) R-HSA-5358565\n", - "Processive Synthesis On Lagging Strand R-HSA-69183\n", - "Mismatch Repair (MMR) Directed By MSH2:MSH3 (MutSbeta) R-HSA-5358606\n", - "Phototransduction Cascade R-HSA-2514856\n", - "RNA polymerase II complex, chromatin structure modifying (human)\n", - "Integrator-RNAPII complex (human)\n", - "Parvulin-associated pre-rRNP complex (mouse)\n", - "PCAF complex (human)\n", - "DNA synthesome complex (17 subunits) (human)\n", - "CTF18-cohesion-RFC-POLH complex (human)\n", - "FCP1-associated protein complex (human)\n", - "CF IIAm complex (Cleavage factor IIAm complex) (human)\n", - "BRM-SIN3A-HDAC complex (human)\n", - "TNF-alpha/NF-kappa B signaling complex 6 (human)\n", - "TNF-alpha/NF-kappa B signaling complex (CHUK, BTRC, NFKB2, PPP6C, REL, CUL1, IKBKE, SAPS2, SAPS1, ANKRD28, RELA, SKP1) (human)\n", - "E2F-6 complex (human)\n", - "BRD4 complex (human)\n", - "RC complex (Replication competent complex) (human)\n", - "PBAF complex (Polybromo- and BAF containing complex) (human)\n", - "Emerin complex 24 (human)\n", - "DSS1 complex (human)\n", - "TFIIH transcription factor complex (human)\n", - "Prefoldin complex (human)\n", - "Gata1-Fog1-MeCP1 complex (mouse)\n", - "URI complex (Unconventional prefoldin RPB5 Interactor) (human)\n", - "BRM-SIN3A complex (human)\n", - "RSmad complex (human)\n", - "MLL1-WDR5 complex (human)\n", - "12S U11 snRNP (human)\n", - "BRAFT complex (human)\n", - "FA complex (Fanconi anemia complex) (human)\n", - "SMN complex (human)\n", - "p400-associated complex (human)\n", - "GCN5-TRRAP histone acetyltransferase complex (human)\n", - "Anaphase-promoting complex (human)\n", - "BAF complex (human)\n", - "UTX-MLL2/3 complex (human)\n", - "Rnase/Mrp complex (human)\n", - "NCOR2 complex (human)\n", - "NUMAC complex (nucleosomal methylation activator complex) (human)\n", - "PA700 complex (human)\n", - "Cell cycle kinase complex CDC2 (human)\n", - "CDC5L core complex (human)\n", - "SRCAP-associated chromatin remodeling complex (human)\n", - "5S-DNA-TFIIIA-TFIIIC2-TFIIIB subcomplex (human)\n", - "Respiratory chain complex I, mitochondrial (mouse)\n", - "TRAP complex (human)\n", - "TNF-alpha/NF-kappa B signaling complex 5 (human)\n", - "HCF-1 complex (human)\n", - "SMN-PolII-RHA complex (human)\n", - "DAB complex (human)\n", - "mRNA decay complex (UPF1, UPF2, UPF3B, DCP2, XRN1, XRN2, EXOSC2, EXOSC4, EXOSC10, PARN) (human)\n", - "TFTC-type histone acetyl transferase complex (human)\n", - "BLM complex II (human)\n", - "ARC-L complex (human)\n", - "RNA polymerase II (RNAPII) (human)\n", - "PA28gamma-20S proteasome (human)\n", - "BRG1-SIN3A complex (human)\n", - "5S-DNA-TFIIIA-TFIIIC2 subcomplex (human)\n", - "LSm1-7 complex (human)\n", - "NCOR1 complex (human)\n", - "PA28-20S proteasome (human)\n", - "TFTC complex (TATA-binding protein-free TAF-II-containing complex) (human)\n", - "PC2 complex (human)\n", - "SNF2h-cohesin-NuRD complex (human)\n", - "Respiratory chain complex I (early intermediate NDUFAF1 assembly), mitochondrial (human)\n", - "RC complex during G2/M-phase of cell cycle (human)\n", - "Polycystin-1 multiprotein complex (ACTN1, CDH1, SRC, JUP, VCL, CTNNB1, PXN, BCAR1, PKD1, PTK2, TLN1) (human)\n", - "Anti-HDAC2 complex (human)\n", - "p300-CBP-p270-SWI/SNF complex (human)\n", - "Ubiquitin E3 ligase (CSN1, CSN8, HRT1, SKP1, SKP2, CUL1, CUL2, CUL3) (human)\n", - "TFIID complex (mouse)\n", - "TFIID complex (human)\n", - "TNF-alpha/NF-kappa B signaling complex (SEC16A, CHUK, IKBKB, NFKB2, REL, IKBKG, MAP3K14, RELA, FBXW7, USP2) (human)\n", - "NAT complex (human)\n", - "EBAFb complex (human)\n", - "Nop56p-associated pre-rRNA complex (human)\n", - "DA complex (human)\n", - "HDAC1-associated core complex cII (human)\n", - "BRCA1-RNA polymerase II complex (human)\n", - "p97/VCP-VIMP-DERL1-DERL2-HRD1-SEL1L complex (human)\n", - "INO80 chromatin remodeling complex (human)\n", - "ARC complex (human)\n", - "DRIP complex (human)\n", - "WINAC complex (human)\n", - "SIN3-ING1b complex II (human)\n", - "ING2 complex (human)\n", - "SIN3-SAP25 complex (human)\n", - "COP9 signalosome complex (human)\n", - "Integrator complex (human)\n", - "CtBP complex (human)\n", - "ESR1-CDK7-CCNH-MNAT1-MTA1-HDAC2 complex (human)\n", - "26S proteasome (human)\n", - "ESCRT-III complex (human)\n", - "SIN3-ING1b complex I (human)\n", - "HDAC2-asscociated core complex (human)\n", - "CHUK-NFKB2-REL-IKBKG-SPAG9-NFKB1-NFKBIE-COPB2-TNIP1-NFKBIA-RELA-TNIP2 complex (human)\n", - "SWI-SNF chromatin remodeling-related-BRCA1 complex (human)\n", - "STAGA complex (SPT3-TAF9-GCN5 acetyltransferase complex) (human)\n", - "Cytochrome c oxidase (EC 1.9.3.1), mitochondrial (mouse)\n", - "NuA4/Tip60-HAT complex B (human)\n", - "LARC complex (LCR-associated remodeling complex) (human)\n", - "MeCP1 complex (human)\n", - "HES1 promoter-Notch enhancer complex (human)\n", - "NuA4/Tip60-HAT complex A (human)\n", - "Exosome (human)\n", - "18S U11/U12 snRNP (human)\n", - "Conserved oligomeric Golgi (COG) complex (human)\n", - "Emerin complex 25 (human)\n", - "TNF-alpha/Nf-kappa B signaling complex (RPL6, RPL30, RPS13, CHUK, DDX3X, NFKB2, NFKBIB, REL, IKBKG, NFKB1, MAP3K8, RELB, GLG1, NFKBIA, RELA, TNIP2, GTF2I) (human)\n", - "BRD4-RFC complex (human)\n", - "Ubiquitin E3 ligase (AHR, ARNT, DDB1, TBL3, CUL4B, RBX1) (human)\n", - "CRM1-RAN-PHAX-CBC complex (cap binding complex) (human)\n", - "RNA polymerase II holoenzyme complex (human)\n", - "BRCA1-core RNA polymerase II complex (human)\n", - "RC complex during S-phase of cell cycle (human)\n", - "TNF-alpha/NF-kappa B signaling complex (CHUK, KPNA3, NFKB2, NFKBIB, REL, IKBKG, NFKB1, NFKBIE, RELB, NFKBIA, RELA, TNIP2) (human)\n", - "LSm2-8 complex (human)\n", - "Toposome (human)\n", - "ARC92-Mediator complex (human)\n", - "CSA complex (human)\n", - "CENP-A NAC-CAD complex (human)\n", - "CCT complex (chaperonin containing TCP1 complex) (mouse)\n", - "CSA-POLIIa complex (human)\n", - "PTIP-DNA damage response complex (human)\n", - "BRCA1-BARD1-BACH1-DNA damage complex II (human)\n", - "cMYC-ATPase-helicase complex (human)\n", - "Anaphase-promoting complex (mouse)\n", - "Large Drosha complex (human)\n", - "CRSP complex (human)\n", - "SMCC complex (human)\n", - "17S U2 snRNP (human)\n", - "TRAP-SMCC mediator complex (human)\n", - "MTA2 complex (human)\n", - "Mediator complex (mouse)\n", - "Anti-Sm protein complex (human)\n", - "20S proteasome (human)\n", - "DMAP1-associated complex (human)\n", - "RNA polymerase II complex, incomplete (CDK8 complex), chromatin structure modifying (human)\n", - "Cytochrome bc1-complex (EC 1.10.2.2), mitochondrial (mouse)\n", - "RAD17-RFC-9-1-1 checkpoint supercomplex (human)\n", - "TFIID complex, B-cell specific (human)\n", - "CEN complex (human)\n", - "DDB2 complex (human)\n", - "BASC complex (BRCA1-associated genome surveillance complex) (human)\n", - "CRSP-Mediator 2 complex (human)\n", - "RNA polymerase II core complex (human)\n", - "MDC1-MRN-ATM-FANCD2 complex (human)\n", - "PCNA-CHL12-RFC2-5 complex (human)\n", - "EBAFa complex (human)\n", - "Condensin II (human)\n", - "Kaiso-NCOR complex (human)\n", - "SF3b complex (human)\n", - "PTIP-HMT complex (human)\n", - "Nup 107-160 subcomplex (human)\n", - "p27-cyclinE-Cdk2 - Ubiquitin E3 ligase (SKP1A, SKP2, CUL1, CKS1B, RBX1) complex (human)\n", - "TFIID-beta complex (human)\n", - "PYR complex (mouse)\n", - "Kinase maturation complex 1 (human)\n", - "immunoproteasome (mouse)\n", - "ALL-1 supercomplex (human)\n", - "Emerin complex 32 (human)\n", - "Ikaros complex (mouse)\n" - ] - } - ], - "source": [ - "for x in corum_matrix[\"feature\"].unique():\n", - " print(x)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "2766b131", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "97fd0a08", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "7fb27b941602401d91542211134fc71a", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "14ed27d8", - "metadata": {}, - "outputs": [], - "source": [ - "# get all modelids that have NA values in the corum matrix\n", - "corum_matrix[corum_matrix.isna().any(axis=1)][\"ModelID\"].sort_values().unique()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "484e6f14", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "6cdc8f80", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "1150 rows before dropping NA\n", - "1150 rows after dropping NA\n", - "1150 rows before dropping NA\n", - "958 rows after dropping NA\n", - "1150 rows before dropping NA\n", - "958 rows after dropping NA\n", - "1150 rows before dropping NA\n", - "958 rows after dropping NA\n" - ] - } - ], - "source": [ - "# @st.cache_data\n", - "\n", - "\n", - "def compute_pca(df, metadata_columns) -> pd.DataFrame:\n", - " \"\"\"Cache PCA result per disease selection.\"\"\"\n", - " # df.fillna(0, inplace=True) # Fill NA with 0 for PCA, or drop rows with NA\n", - " print(df.shape[0], \"rows before dropping NA\")\n", - " df.dropna(inplace=True) # PCA can't handle missing values, so drop rows with any NA\n", - " print(df.shape[0], \"rows after dropping NA\")\n", - " metadata_df = df[metadata_columns]\n", - " feat_cols = df.columns.drop(metadata_columns)\n", - " if \"source\" in feat_cols:\n", - " feat_cols = feat_cols.drop(\"source\")\n", - "\n", - " pca_input = df[feat_cols].apply(pd.to_numeric, errors=\"coerce\")\n", - " pca = PCA(n_components=2, random_state=0)\n", - " pca_embedding = pca.fit_transform(pca_input)\n", - " metadata_df[\"PCA1\"] = pca_embedding[:, 0]\n", - " metadata_df[\"PCA2\"] = pca_embedding[:, 1]\n", - " return metadata_df\n", - "\n", - "\n", - "pca_single_df = compute_pca(combined_df, [\"ModelID\", \"OncotreePrimaryDisease\"])\n", - "# save the PCA result to a parquet file for later use in the app\n", - "pca_single_df.to_parquet(\n", - " BASE_DIR / \"data\" / \"pca_embeddings_single_dependencies.parquet\"\n", - ")\n", - "\n", - "pca_latent_reactome_df = compute_pca(\n", - " reactome_matrix, [\"OncotreePrimaryDisease\", \"ModelID\"]\n", - ")\n", - "pca_latent_corum_df = compute_pca(corum_matrix, [\"OncotreePrimaryDisease\", \"ModelID\"])\n", - "pca_latent_drug_df = compute_pca(drug_matrix, [\"OncotreePrimaryDisease\", \"ModelID\"])\n", - "pca_latent_reactome_df.to_parquet(\n", - " BASE_DIR / \"data\" / \"pca_embeddings_latent_reactome.parquet\"\n", - ")\n", - "pca_latent_corum_df.to_parquet(\n", - " BASE_DIR / \"data\" / \"pca_embeddings_latent_corum.parquet\"\n", - ")\n", - "pca_latent_drug_df.to_parquet(BASE_DIR / \"data\" / \"pca_embeddings_latent_drug.parquet\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "dc8ccfe3", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "26a895e4", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": ".venv (3.13.1)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.13.1" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -}

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