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, with Java Virtual Machines sized to use a fraction of the host VM memory, since as of July 2025 Terra.bio does not retry any host VM memory failures when triggering the OOM Killer, plus... Google Cloud Batch often fails with 50002 errors when the host is under strain as the Batch agent does not seem to reserve compute resources for itself. 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 |