Explore Workflows

https://github.com/GeorgeAlehandro/cwl_1_11.git

Path: workflow1_11.cwl

Branch/Commit ID: main

Packed ID: UncompressDatatables.cwl

https://github.com/hamid58b/cancer-genomics-workflow.git

Path: strelka/workflow.cwl

Branch/Commit ID: master

https://github.com/KBNLresearch/ochre.git

Path: ochre/cwl/kb-tss-preprocess-all.cwl

Branch/Commit ID: master

Packed ID: kb-tss-preprocess-single-dir.cwl

https://github.com/pascmont/cwltest.git

Path: myWorkflow2.cwl

Branch/Commit ID: main

https://github.com/NCGM-genome/WGSpipeline.git

Path: Workflows/germline-gpu-v4.1.1.cwl

Branch/Commit ID: main

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

Path: unaligned_bam_to_bqsr/workflow.cwl

Branch/Commit ID: toil_compatibility

ATAC-seq 01 QC - reads: SE

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

Path: v1.0/ATAC-seq_pipeline/01-qc-se.cwl

Branch/Commit ID: v1.0.0

This workflow takes the PeptideProphet, and the ProteinProphet output files, and applies a stringent False Discovery Rate (FDR) filtering. Peptide and proteins are filtered individually at 1% FDR. The high-quality PSMs, peptides, and proteins are then quantified using a label-free algorithm that uses the apex peak intensity as a measurement. Finally, the isobaric tags are quantified and annotated with the correct sample labels.

https://github.com/cwl-apps/fragpipe-proteomics-pipeline-tutorial.git

Path: FragPipe-Filter-Quant-Report/fragpipe-filter-quant-report.cwl

Branch/Commit ID: main

https://github.com/uc-cdis/genomel_pipelines.git

Path: genomel/genomel_cohort_gatk4.cwl

Branch/Commit ID: master

https://github.com/ProteinsWebTeam/ebi-metagenomics-cwl.git

Path: tools/rRNA_selection.cwl

Branch/Commit ID: ef3c7b2