iBlastoids_scripts/iBlastoids_integration.Rmd at master · jibsch/iBlastoids_scripts · GitHub

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---
title: "iBlastoids_integration"
author: "jibsch"
date: "2021-01-23"
output: workflowr::wflow_html
editor_options:
  chunk_output_type: inline
---

## Integrate all data

```{r}
seurat_d6 = readRDS("../output/seurat_iblastoids.Rds")
seurat_pet3 = readRDS("../output/seurat_pet3.Rds")
blake  = readRDS("../output/blake.Rds")
```


### Remove NR and Integrate

```{r}
seurat_d6_noNR = seurat_iblastoids[,seurat_iblastoids$celltype!="NR_iBlastoids"]

blast.list = list("iBlast" = seurat_d6_noNR, "blake" = blake,   "pet" = seurat_pet3 )

blast.features <- SelectIntegrationFeatures(object.list = blast.list, nfeatures = 4000)
blast.list <- PrepSCTIntegration(object.list = blast.list, anchor.features = blast.features,
    verbose = FALSE)
```

```{r}
blast.anchors <- FindIntegrationAnchors(object.list = blast.list, normalization.method = "SCT",
    anchor.features = blast.features, verbose = FALSE, dims = 1:14,
    k.filter = 29, k.score = 29)
blast.integrated_d6_blake_pet_noNR <- IntegrateData(anchorset = blast.anchors, normalization.method = "SCT",
    verbose = FALSE)
```

```{r}
blast.integrated_d6_blake_pet_noNR = RunPCA(blast.integrated_d6_blake_pet_noNR, verbose = FALSE)
DimPlot(blast.integrated_d6_blake_pet_noNR, reduction = "pca", group.by = "orig.ident")

blast.integrated_d6_blake_pet_noNR = RunUMAP(blast.integrated_d6_blake_pet_noNR, dims=1:20)
DimPlot(blast.integrated_d6_blake_pet_noNR, reduction = "umap", group.by = "orig.ident")

DimPlot(blast.integrated_d6_blake_pet_noNR, reduction = "umap", group.by = "celltype", label = TRUE) ->p1

DimPlot(blast.integrated_d6_blake_pet_noNR, reduction = "umap", group.by = "group", label = TRUE) ->p2

CombinePlots(list(p1,p2))
```

```{r}
blast.integrated_d6_blake_pet_noNR$original_id =
factor(ifelse(blast.integrated_d6_blake_pet_noNR$orig.ident == "iBlastoids",
#as.character(blast.integrated_d6_blake_pet$cell_type),
as.character(blast.integrated_d6_blake_pet_noNR$celltype),
as.character(blast.integrated_d6_blake_pet_noNR$group %>% gsub("Epi", "EPI",.))))

n = blast.integrated_d6_blake_pet_noNR$original_id
blast.integrated_d6_blake_pet_noNR$type = ifelse(grepl("pre",n), "Pre_Blast",
ifelse(grepl("TE", n), "TE",
ifelse(grepl("PE", n), "PE",
ifelse(grepl("EPI",n), "EPI", "IM"))))

```


```{r}
blast.integrated_d6_blake_pet_noNR = FindNeighbors(blast.integrated_d6_blake_pet_noNR, dims = 1:20)

blast.integrated_d6_blake_pet_noNR = FindClusters(blast.integrated_d6_blake_pet_noNR, resolution = 0.2)

DimPlot(blast.integrated_d6_blake_pet_noNR, label = TRUE)
```
```{r}
blast.integrated_d6_blake_pet_noNR$cluster_int = factor(recode(blast.integrated_d6_blake_pet_noNR$seurat_clusters,
                                 "2" = "Int_EPI", "1" = "Int_PE", "0" = "Int_TE",
                                "3" = "Int_IM1", "4" = "Int_IM2"), levels =
                                  c("Int_EPI", "Int_TE", "Int_PE", "Int_IM1",
                                    "Int_IM2"))
```

```{r}
blast.integrated_d6_blake_pet_noNR = AddModuleScore(blast.integrated_d6_blake_pet_noNR, features = petro_sig.list[c("ALL-PE", "ALL-TE", "ALL-PE")], name = c("EPI", "TE", "PE"))
names([email protected]) = gsub("[123]$","", names([email protected]))
```

```{r}
[email protected] = [email protected][,c("orig.ident", "seurat_clusters", "original_id", "cluster_int", "EPI", "TE", "PE")]
```


```{r}
blast.integrated_d6_blake_pet_noNR$type =
  ifelse(grepl("EPI", blast.integrated_d6_blake_pet_noNR$original_id),
         "EPI",
         ifelse(grepl("TE", blast.integrated_d6_blake_pet_noNR$original_id),
                "TE",
                ifelse(grepl("PE", blast.integrated_d6_blake_pet_noNR$original_id),
                       "PE","IM")))
```