Drop-seq WDL

WDL for analyzing Drop-seq data

Drop-seq questions may be directed to dropseq@gmail.com.
You may also use this address to be added to the Drop-seq Google group.

See the Drop-seq GitHub repository for more information on the tools.

Overview

• These WDLs are considered early but usable previews, subject to extensive changes!

• WDLs are separated by into pipelines and tasks

  • Pipelines are the top-level WDLs that define the executable workflows.
  • Some pipelines are further divided into sub-workflows.
  • Tasks are the individual steps that are called by the pipelines that execute a single tool.
  • There are experimental "combined" WDLs that aggregate multiple pipelines.

• The WDLs are designed to

  • Run on Terra.bio platform and its underlying Cromwell workflow management system.
  • Written in WDL version 1.0.
  • Optimize costs on Google Cloud Platform but may run on other platforms.
  • Compliment and extend pipelines from
    • WARP, especially Optimus.
    • CellBender Remove Background (CBRB)
    • pyQTL
    • sc-eQTLs in cell villages pipeline
    • broadinstitute_gtex
      • tensorqtl_cis_nominal_v1-0_BETA
      • tensorqtl_cis_permutations_v1-0_BETA
      • tensorqtl_cis_susie_v1-0_BETA
      • tensorqtl_cis_indep_v1-0_BETA
  • Optimize Google Compute memory while leaving a buffer, since as of November 2024 Terra.bio does not retry any host VM memory failures. Java Virtual Machines are sized to use a fraction of the host VM memory.

• Tasks contain a mix of Drop-seq tools and other tools

  • Drop-seq tools are from the Drop-seq GitHub repository.
  • Other tools are from the Broad Institute GATK and other sources.
  • Tasks may expose all or only some of the tool parameters.

Workflows

| Workflow | Summary | |---------------------------|-------------------------------------------------| | optimus_post_processing | Converts Optimus outputs to Drop-seq inputs | | dropseq_cbrb | Estimates parameters then invokes CBRB | | cell_selection | Sub-selects barcodes that captured nuclei | | standard_analysis | Assigns nuclei to donors and detects doublets | | cell_classification | Classifies cells based on their gene expression | | tensorqtl | cis-QTL mapping using tensorQTL |