Explore Workflows

Super-enhancers, consist of clusters of enhancers that are densely occupied by the master regulators and Mediator. Super-enhancers differ from typical enhancers in size, transcription factor density and content, ability to activate transcription, and sensitivity to perturbation. Use to create stitched enhancers, and to separate super-enhancers from typical enhancers using sequencing data (.bam) given a file of previously identified constituent enhancers (.gff)

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

Path: workflows/super-enhancer.cwl

Branch/Commit ID: 4a80f5b8f86c83af39494ecc309b789aeda77964

DNase-seq - map - Filter PCR Artifacts

https://github.com/alexbarrera/GGR-cwl.git

Path: v1.0/map/filter-pcr-artifacts.cwl

Branch/Commit ID: 33385c6a820a9d4d18cff6fc3a533ec8e3c11c6e

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

Path: definitions/pipelines/somatic_exome_mouse.cwl

Branch/Commit ID: 3f3b186da9bf82a5e2ae74ba27aef35a46174ebe

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

Path: cwltool/schemas/v1.0/v1.0/env-wf2.cwl

Branch/Commit ID: 75271e2a0887d47cca4077b60dd51ac763c09b63

https://github.com/common-workflow-language/cwl-v1.2.git

Path: tests/count-lines1-wf.cwl

Branch/Commit ID: ea9f8634e41824ac3f81c3dde698d5f0eef54f1b

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

Path: tests/wf/mut.cwl

Branch/Commit ID: a3d565bf8e630101d25d31804cfbceb0a0ba28de

https://gitlab.bsc.es/lrodrig1/structuralvariants_poc.git

Path: structuralvariants/cwl/subworkflows/indexing_bed.cwl

Branch/Commit ID: 6ccec9c5c5bc9fb4e75ca0b9cc22d13df9ffb815

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

Path: tests/wf/count-lines1-wf.cwl

Branch/Commit ID: a3d565bf8e630101d25d31804cfbceb0a0ba28de

Sequence reads are first cleaned from adapters and transformed into fully bisulfite-converted forward (C->T) and reverse read (G->A conversion of the forward strand) versions, before they are aligned to similarly converted versions of the genome (also C->T and G->A converted). Sequence reads that produce a unique best alignment from the four alignment processes against the bisulfite genomes (which are running in parallel) are then compared to the normal genomic sequence and the methylation state of all cytosine positions in the read is inferred. A read is considered to align uniquely if an alignment has a unique best alignment score (as reported by the AS:i field). If a read produces several alignments with the same number of mismatches or with the same alignment score (AS:i field), a read (or a read-pair) is discarded altogether. On the next step we extract the methylation call for every single C analysed. The position of every single C will be written out to a new output file, depending on its context (CpG, CHG or CHH), whereby methylated Cs will be labelled as forward reads (+), non-methylated Cs as reverse reads (-). The output of the methylation extractor is then transformed into a bedGraph and coverage file. The bedGraph counts output is then used to generate a genome-wide cytosine report which reports the number on every single CpG (optionally every single cytosine) in the genome, irrespective of whether it was covered by any reads or not. As this type of report is informative for cytosines on both strands the output may be fairly large (~46mn CpG positions or >1.2bn total cytosine positions in the human genome).

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

Path: workflows/bismark-methylation-se.cwl

Branch/Commit ID: 12c29f88855329192bfff977f046990031f04931

Reverse the lines in a document, then sort those lines.

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

Path: cwltool/schemas/v1.0/v1.0/revsort.cwl

Branch/Commit ID: e9c83739a93fa0b18f8dea2f98b632a9e32725c9