Explore Workflows

View already parsed workflows here or click here to add your own

Graph Name Retrieved From View
workflow graph Cell Ranger Count (RNA+VDJ)

Cell Ranger Count (RNA+VDJ) Quantifies single-cell gene expression, performs V(D)J contigs assembly and clonotype calling of the sequencing data from a single 10x Genomics library in a combined manner. The results of this workflow are primarily used in either “Single-Cell RNA-Seq Filtering Analysis”, “Single-Cell Immune Profiling Analysis”, or “Cell Ranger Aggregate (RNA, RNA+VDJ)” pipelines.

 https://github.com/datirium/workflows.git

Path: workflows/cellranger-multi.cwl

Branch/Commit ID: 57863b6131d8262c5ce864adaf8e4038401e71a2
workflow graph Pipeline for evaluating differential expression of genes across datasets

https://github.com/hubmapconsortium/rna-data-products.git

Path: pipeline.cwl

Branch/Commit ID: 41ab146cbf51d1ffc9e22d577776813292792d70
workflow graph Resize sentinel2ard collection

Resize sentinel2ard collection

 https://github.com/EO-DataHub/eodh-training.git

Path: cwl/resize-sentinel2ard.cwl

Branch/Commit ID: cbd9df98847fb2921dd4384564857b52ceda43bc

Packed ID: resize-sentinel2ard
workflow graph DiffBind Multi-factor Analysis

DiffBind Multi-factor Analysis ------------------------------ DiffBind processes ChIP-Seq data enriched for genomic loci where specific protein/DNA binding occurs, including peak sets identified by ChIP-Seq peak callers and aligned sequence read datasets. It is designed to work with multiple peak sets simultaneously, representing different ChIP experiments (antibodies, transcription factor and/or histone marks, experimental conditions, replicates) as well as managing the results of multiple peak callers. For more information please refer to: ------------------------------------- Ross-Innes CS, Stark R, Teschendorff AE, Holmes KA, Ali HR, Dunning MJ, Brown GD, Gojis O, Ellis IO, Green AR, Ali S, Chin S, Palmieri C, Caldas C, Carroll JS (2012). “Differential oestrogen receptor binding is associated with clinical outcome in breast cancer.” Nature, 481, -4.

 https://github.com/datirium/workflows.git

Path: workflows/diffbind-multi-factor.cwl

Branch/Commit ID: 57863b6131d8262c5ce864adaf8e4038401e71a2
workflow graph Unaligned BAM to BQSR and VCF

https://github.com/genome/analysis-workflows.git

Path: definitions/subworkflows/bam_to_bqsr.cwl

Branch/Commit ID: 76a35e7d885790f30559beb31f3b58770e343afd
workflow graph Bisulfite QC tools

https://github.com/genome/analysis-workflows.git

Path: definitions/subworkflows/bisulfite_qc.cwl

Branch/Commit ID: adcae308fdccaa1190083616118dfadb4df65dca
workflow graph scatter-wf1_v1_1.cwl

https://github.com/common-workflow-language/cwl-utils.git

Path: testdata/scatter-wf1_v1_1.cwl

Branch/Commit ID: b926e330eba795f3acc1f71fd0645e75f925a2da
workflow graph 816_wf.cwl

https://github.com/common-workflow-language/cwltool.git

Path: tests/wf/816_wf.cwl

Branch/Commit ID: 6b8f06a9f6f6a570142c7aedc767fea2efa2a0cc
workflow graph Single-Cell ATAC-Seq Dimensionality Reduction Analysis

Single-Cell ATAC-Seq Dimensionality Reduction Analysis Removes noise and confounding sources of variation by reducing dimensionality of chromatin accessibility data from the outputs of “Single-Cell Multiome ATAC and RNA-Seq Filtering Analysis” pipelines. The results of this workflow are primarily used in “Single-Cell ATAC-Seq Cluster Analysis” or “Single-Cell WNN Cluster Analysis” pipelines.

 https://github.com/datirium/workflows.git

Path: workflows/sc-atac-reduce.cwl

Branch/Commit ID: 57863b6131d8262c5ce864adaf8e4038401e71a2
workflow graph Cellranger Reanalyze

Cellranger Reanalyze ====================

 https://github.com/datirium/workflows.git

Path: workflows/cellranger-reanalyze.cwl

Branch/Commit ID: 57863b6131d8262c5ce864adaf8e4038401e71a2