Explore Workflows

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

Path: cwltool/schemas/v1.0/v1.0/count-lines7-wf.cwl

Branch/Commit ID: 6e9f82a6d2195d4f16f28fd6e1485138372fb430

Workflow converts input BAM file into bigWig and bedGraph files. Input BAM file should be sorted by coordinates (required by `bam_to_bedgraph` step). If `split` input is not provided use true by default. Default logic is implemented in `valueFrom` field of `split` input inside `bam_to_bedgraph` step to avoid possible bug in cwltool with setting default values for workflow inputs. `scale` has higher priority over the `mapped_reads_number`. The last one is used to calculate `-scale` parameter for `bedtools genomecov` (step `bam_to_bedgraph`) only in a case when input `scale` is not provided. All logic is implemented inside `bedtools-genomecov.cwl`. `bigwig_filename` defines the output name only for generated bigWig file. `bedgraph_filename` defines the output name for generated bedGraph file and can influence on generated bigWig filename in case when `bigwig_filename` is not provided. All workflow inputs and outputs don't have `format` field to avoid format incompatibility errors when workflow is used as subworkflow.

https://github.com/Barski-lab/workflows.git

Path: tools/bam-bedgraph-bigwig.cwl

Branch/Commit ID: 94f3486d3867b9ece47c07bc8fe47f57569786f4

https://github.com/ncbi/pgap.git

Path: spurious_annot/wf_spurious_annot_pass2.cwl

Branch/Commit ID: 424a01693259a75641dc249d553235aa38a6ce23

https://github.com/ncbi/pgap.git

Path: spurious_annot/wf_spurious_annot_pass1.cwl

Branch/Commit ID: 424a01693259a75641dc249d553235aa38a6ce23

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: 93b844a80f4008cc973ea9b5efedaff32a343895

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

Path: testdata/stdout-wf_v1_1.cwl

Branch/Commit ID: b76b039edb62dea76c43f173848cdc57e4b4aab7

https://github.com/ncbi/pgap.git

Path: bacterial_annot/wf_bacterial_annot_pass3.cwl

Branch/Commit ID: 424a01693259a75641dc249d553235aa38a6ce23

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

Path: testdata/cond-wf-005.1.cwl

Branch/Commit ID: b76b039edb62dea76c43f173848cdc57e4b4aab7

https://github.com/Marco-Salvi/dtc61.git

Path: ST610109.cwl

Branch/Commit ID: 74185c230b8c2f979abc1c144bc93d8267b2cada

https://github.com/ncbi/pgap.git

Path: wf_bacterial_prot_src.cwl

Branch/Commit ID: 424a01693259a75641dc249d553235aa38a6ce23