Explore Workflows

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

Graph	Name	Retrieved From	View
	Subworkflow that runs cnvkit in single sample mode and returns a vcf file	https://github.com/genome/analysis-workflows.git Path: definitions/subworkflows/cnvkit_single_sample.cwl Branch/Commit ID: 3a822294da63b4e19446a285e2fef075e23cf3d0
	scatter GATK HaplotypeCaller over intervals	https://github.com/litd/analysis-workflows.git Path: definitions/subworkflows/gatk_haplotypecaller_iterator.cwl Branch/Commit ID: 0d4e517d7c1c6deb0db02d3746c8ed4db841bd57
	kmer_cache_store	https://github.com/ncbi/pgap.git Path: task_types/tt_kmer_cache_store.cwl Branch/Commit ID: f6950321e5c9ee733ad68a273d2ad8e802a6b982
	03-map-pe.cwl ChIP-seq 03 mapping - reads: PE	https://github.com/Duke-GCB/GGR-cwl.git Path: v1.0/ChIP-seq_pipeline/03-map-pe.cwl Branch/Commit ID: 6d9457382f0b7cc2510e148d21383261280d17ed
	cluster_blastp_wnode and gpx_qdump combined	https://github.com/ncbi/pgap.git Path: task_types/tt_cluster_and_qdump.cwl Branch/Commit ID: f18c1dce463509170ee3bf2844d5a3637ff706f5
	Cut-n-Run pipeline paired-end Experimental pipeline for Cut-n-Run analysis. Uses mapping results from the following experiment types: - `chipseq-pe.cwl` - `trim-chipseq-pe.cwl` - `trim-atacseq-pe.cwl` Note, the upstream analyses should not have duplicates removed	https://github.com/datirium/workflows.git Path: workflows/trim-chipseq-pe-cut-n-run.cwl Branch/Commit ID: 17a4a68b20e0af656e09714c1f39fe761b518686
	gather AML trio outputs	https://github.com/genome/analysis-workflows.git Path: definitions/pipelines/aml_trio_cle_gathered.cwl Branch/Commit ID: 844c10a4466ab39c02e5bfa7a210c195b8efa77a
	Motif Finding with HOMER with target and background regions from peaks Motif Finding with HOMER with target and background regions from peaks --------------------------------------------------- HOMER contains a novel motif discovery algorithm that was designed for regulatory element analysis in genomics applications (DNA only, no protein). It is a differential motif discovery algorithm, which means that it takes two sets of sequences and tries to identify the regulatory elements that are specifically enriched in on set relative to the other. It uses ZOOPS scoring (zero or one occurrence per sequence) coupled with the hypergeometric enrichment calculations (or binomial) to determine motif enrichment. HOMER also tries its best to account for sequenced bias in the dataset. It was designed with ChIP-Seq and promoter analysis in mind, but can be applied to pretty much any nucleic acids motif finding problem. For more information please refer to: ------------------------------------- [Official documentation](http://homer.ucsd.edu/homer/motif/)	https://github.com/datirium/workflows.git Path: workflows/homer-motif-analysis-peak.cwl Branch/Commit ID: 1f03ff02ef829bdb9d582825bcd4ca239e84ca2e
	strelka workflow	https://github.com/genome/analysis-workflows.git Path: definitions/subworkflows/strelka_and_post_processing.cwl Branch/Commit ID: 3a822294da63b4e19446a285e2fef075e23cf3d0
	tt_blastn_wnode	https://github.com/ncbi/pgap.git Path: task_types/tt_blastn_wnode.cwl Branch/Commit ID: b12ec8c8e832151033b9e6c0a76a3c3df18d45da