_viash.yaml

viash_version: 0.9.0

name: task_spatially_variable_genes
organization: openproblems-bio
version: dev

license: MIT
keywords: [single-cell, openproblems, benchmark, spatial, transcriptomics, spatial variablility]
links:
  issue_tracker: https://github.com/openproblems-bio/task_spatially_variable_genes/issues
  repository: https://github.com/openproblems-bio/task_spatially_variable_genes
  docker_registry: ghcr.io

label: Spatially Variable Genes
summary: Spatially variable genes (SVGs) are genes whose expression levels vary significantly across different spatial regions within a tissue or across cells in a spatially structured context.
description: |
  Recent years have witnessed significant progress in spatially-resolved transcriptome profiling techniques that simultaneously characterize cellular gene expression and their physical position, generating spatial transcriptomic (ST) data. The application of these techniques has dramatically advanced our understanding of disease and developmental biology. One common task for all ST profiles, regardless of the employed protocols, is to identify genes that exhibit spatial patterns. These genes, defined as spatially variable genes (SVGs), contain additional information about the spatial structure of the tissues of interest, compared to highly variable genes (HVGs).

  Identification of spatially variable genes is crucial to for studying spatial domains within tissue microenvironmnets, developmental gradients and cell signaling pathways. In this task we attempt to evaluate various methods for detecting SVGs using a number of realistic simulated datasets with diverse patterns derived from real-world spatial transcriptomics data using scDesign3. Synthetic data is generated by mixing a Gaussian Process (GP) model and a non-spatial model (obtained by shuffling mean parameters of the GP model to remove spatial correlation between spots) to generate gene expressions with various spatial variability. For more details, please refer to our [manuscript](https://www.biorxiv.org/content/10.1101/2023.12.02.569717v1) and [Github](https://github.com/pinellolab/SVG_Benchmarking).

references:
  doi:
    - 10.1101/2023.12.02.569717
  
info:
  image: thumbnail.svg
  
  test_resources:
    - type: s3
      path: s3://openproblems-data/resources_test/task_spatially_variable_genes/
      dest: resources_test/task_spatially_variable_genes
    - type: s3
      path: s3://openproblems-data/resources_test/common/mouse_brain_coronal/
      dest: resources_test/common/mouse_brain_coronal

authors: 
  - name: Zhijian Li
    roles: [ author, maintainer ]
    info: 
      github: lzj1769
      orcid: 0000-0002-1523-1333
  - name: Zain M. Patel
    roles: [ author ]
    info: 
      github: doczmp
  - name: Dongyuan Song
    roles: [ author]
    info:
      github: SONGDONGYUAN1994
  - name: Guanao Yan
    roles: [ author ]
  - name: Jingyi Jessica Li
    roles: [ author ]
    info:
      github: JSB-UCLA
  - name: Luca Pinello
    roles: [ author ]
    info:
      github: pinellolab
  - name: Robrecht Cannoodt
    roles: [contributor]
    info:
      github: rcannood
      orcid: 0000-0003-3641-729X
  - name: Sai Nirmayi Yasa
    roles: [contributor]
    info: 
      github: sainirmayi
      orcid: 0009-0003-6319-9803

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" }
  .runners[.type == "nextflow"].config.script := "process.errorStrategy = 'ignore'"

repositories:
  - name: core
    type: github
    repo: openproblems-bio/core
    tag: build/main
    path: viash/core
  - name: openproblems
    type: github
    repo: openproblems-bio/openproblems
    tag: build/main