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viash_version: 0.9.4
name: task_spatial_trajectory_inference
organization: openproblems-bio
version: dev
license: MIT
keywords: [single-cell, openproblems, benchmark, spatial, trajectory inference]
links:
issue_tracker: https://github.com/openproblems-bio/task_spatial_trajectory_inference/issues
repository: https://github.com/openproblems-bio/task_spatial_trajectory_inference
docker_registry: ghcr.io
label: Spatial Trajectory Inference
summary: Predicting the spatial trajectory of cells in a tissue based on spatial transcriptomics data.
description:
Spatial transcriptomics preserves each cell's physical position alongside its expression profile, enabling pseudotime prediction using 2D spatial context.
Different methods make different assumptions about resolution, input format, and output, and are further complicated by spatial batch effects not present in dissociated single-cell data.
While dynbenchmark resolved this comparison problem for non-spatial trajectory inference methods, no equivalent standardized benchmark exists for spatial pseudotime prediction, and existing method papers are validated only against each other or qualitative marker trends rather than tissues with independently known trajectories.
This task benchmarks pseudotime prediction methods on 2D tissue datasets with well-characterized ground-truth spatial axes.
Input data consists of AnnData objects containing 2D spatial transcriptomics data with spatial coordinates.
The output is a set of quantitative metric scores comparing each method's predicted pseudotime against ground truth, capturing both trajectory accuracy and preservation of relevant biological information.
# A list of references to relevant literature. Each reference should be a DOI or a bibtex entry
references:
doi:
- 10.21203/rs.3.rs-4181617/v1
# bibtex:
# - |
# @article{doe_2021_template,
# doi = {10.21203/rs.3.rs-4181617/v1},
# url = {https://doi.org/10.21203/rs.3.rs-4181617/v1},
# author = {Doe, John},
# title = {A template for creating new tasks},
# publisher = {Research Square},
# year = {2021},
# }
info:
image: The name of the image file to use for the component on the website.
test_resources:
- type: s3
path: s3://openproblems-data/resources_test/common/
dest: resources_test/common
- type: s3
path: s3://openproblems-data/resources_test/task_spatial_trajectory_inference/
dest: resources_test/task_spatial_trajectory_inference
authors:
- name: Chit Tong Lio
roles: [ "author", "maintainer" ]
info:
github: yollct
orcid: 0000-0003-2297-831X
email: [email protected]
- name: Seo Hyon Kim
roles: [ "author", "maintainer" ]
info:
github: seohyonkim
orcid: 0009-0007-3062-4681
email: [email protected]
- name: Wenjia Zhong
roles: [ "author", "maintainer" ]
info:
github: Wenjia218
orcid: 0009-0009-1594-8009
email: [email protected]
- name: Luisa Katharina Bender
roles: [ "author", "maintainer" ]
info:
github: luisabender
orcid: 0009-0001-8753-7307
email: [email protected]
- name: Florian Röckl
roles: [ "author", "maintainer" ]
info:
github: floro5
orcid: 0009-0009-6050-890X
email: [email protected]
- name: Jonathan Unger
roles: [ "author", "maintainer" ]
info:
github: Jonique02
orcid: 0009-0009-5022-2975
email: [email protected]
# Step 7: Remove all of the comments of the steps you completed
config_mods: |
.runners[.type == "nextflow"].config.labels := { lowmem : "memory = 20.Gb", midmem : "memory = 50.Gb", highmem : "memory = 100.Gb", lowcpu : "cpus = 5", midcpu : "cpus = 15", highcpu : "cpus = 30", lowtime : "time = 1.h", midtime : "time = 4.h", hightime : "time = 8.h", veryhightime : "time = 24.h" }
repositories:
- name: openproblems
type: github
repo: openproblems-bio/openproblems
tag: build/main # Step 8: Set this to the latest release
# Step 9: High five yourself!