Explore Workflows

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

Graph Name Retrieved From View
workflow graph star-stringtie_wf_pe.cwl

https://github.com/pitagora-network/pitagora-cwl.git

Path: workflows/star-stringtie/paired_end/star-stringtie_wf_pe.cwl

Branch/Commit ID: master

workflow graph compile1.cwl#main

https://github.com/YangYang-Lcos/legacy.git

Path: workflows/compile/compile1.cwl

Branch/Commit ID: master

Packed ID: main

workflow graph Unaligned BAM to BQSR

https://github.com/tmooney/cancer-genomics-workflow.git

Path: definitions/subworkflows/bam_to_bqsr.cwl

Branch/Commit ID: downsample_and_recall

workflow graph Whole genome alignment and somatic variant detection

https://github.com/tmooney/cancer-genomics-workflow.git

Path: definitions/pipelines/somatic_wgs.cwl

Branch/Commit ID: downsample_and_recall

workflow graph exome alignment and somatic variant detection

https://github.com/tmooney/cancer-genomics-workflow.git

Path: definitions/pipelines/somatic_exome_mouse.cwl

Branch/Commit ID: downsample_and_recall

workflow graph Detect Variants workflow for WGS pipeline

https://github.com/apaul7/cancer-genomics-workflow.git

Path: definitions/pipelines/detect_variants_wgs.cwl

Branch/Commit ID: low-vaf

workflow graph wgs alignment and tumor-only variant detection

https://github.com/tmooney/cancer-genomics-workflow.git

Path: definitions/pipelines/tumor_only_wgs.cwl

Branch/Commit ID: downsample_and_recall

workflow graph Whole Exome Sequencing

Whole Exome Sequence analysis using GATK best practices - Germline SNP & Indel Discovery

https://github.com/Duke-GCB/bespin-cwl.git

Path: packed/exomeseq.cwl

Branch/Commit ID: qiime2-workflow-paired

Packed ID: main

workflow graph 02-trim-se.cwl

ChIP-seq 02 trimming - reads: SE

https://github.com/Duke-GCB/GGR-cwl.git

Path: v1.0/ChIP-seq_pipeline/02-trim-se.cwl

Branch/Commit ID: master

workflow graph WGS QC workflow

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

Path: definitions/subworkflows/qc_wgs.cwl

Branch/Commit ID: c235dc6d623879a6c4f5fb307f545c9806eb2d23