Explore Workflows

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

Graph Name Retrieved From View
workflow graph basename-fields-test.cwl

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

Path: cwltool/schemas/v1.0/v1.0/basename-fields-test.cwl

Branch/Commit ID: 7dec97bb8f0bc2d9e9eb710faf41f2e98cc7cdda
workflow graph nestedworkflows.cwl

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

Path: v1.0/examples/nestedworkflows.cwl

Branch/Commit ID: 4fe434e969c93c94b690ba72db295d9d52a6f576
workflow graph kmer_build_tree

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

Path: task_types/tt_kmer_build_tree.cwl

Branch/Commit ID: e71779665f42fcf34601b0f65e030bb0dd47fa79
workflow graph advanced-header.cwl

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

Path: metadata/advanced-header.cwl

Branch/Commit ID: 667280228c27c475969c6a331d26e0cf2337d677
workflow graph umi molecular alignment fastq workflow

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

Path: definitions/pipelines/alignment_umi_molecular.cwl

Branch/Commit ID: 97572e3a088d79f6a4166385f79e79ea77b11470
workflow graph cache_asnb_entries

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

Path: task_types/tt_cache_asnb_entries.cwl

Branch/Commit ID: e668f9c4047f1971ae53040a5af3eccc4bfc3c53
workflow graph mut.cwl

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

Path: tests/wf/mut.cwl

Branch/Commit ID: 5bdb3d3dd47d8d1b3a1685220b4b6ce0f94c055e
workflow graph bam to trimmed fastqs

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

Path: definitions/subworkflows/bam_to_trimmed_fastq.cwl

Branch/Commit ID: c6bbd4cdd612b3b5cc6e9000df4800c21e192bf5
workflow graph Motif Finding with HOMER with random background regions

Motif Finding with HOMER with random background regions --------------------------------------------------- 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. Here is how we generate background for Motifs Analysis ------------------------------------- 1. Take input file with regions in a form of “chr\" “start\" “end\" 2. Sort and remove duplicates from this regions file 3. Extend each region in 20Kb into both directions 4. Merge all overlapped extended regions 5. Subtract not extended regions from the extended ones 6. Randomly distribute not extended regions within the regions that we got as a result of the previous step 7. Get fasta file from these randomly distributed regions (from the previous step). Use it as background 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.cwl

Branch/Commit ID: 675a3ff982091faf304931e9261aacdbabf51702
workflow graph record-output-wf_v1_2.cwl

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

Path: testdata/record-output-wf_v1_2.cwl

Branch/Commit ID: c1875d54dedc41b1d2fa08634dcf1caa8f1bc631