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Graph Name Retrieved From View
workflow graph extract_gencoll_ids

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

Path: task_types/tt_extract_gencoll_ids.cwl

Branch/Commit ID: 42712bca4c3307d87b6b55f525a4c97cb6f7e288
workflow graph sum-wf.cwl

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

Path: cwltool/schemas/v1.0/v1.0/sum-wf.cwl

Branch/Commit ID: 814bd0405a7701efc7d63e8f0179df394c7766f7
workflow graph align_merge_sas

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

Path: task_types/tt_align_merge_sas.cwl

Branch/Commit ID: 953d7866bc70e14c02a6bb8c5a72305caa823bfc
workflow graph scatter-wf2.cwl

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

Path: v1.0/v1.0/scatter-wf2.cwl

Branch/Commit ID: f02557902989c749c9c2187c7045e340e2d76bfc
workflow graph tt_univec_wnode.cwl

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

Path: task_types/tt_univec_wnode.cwl

Branch/Commit ID: b560e3abadfb150a0013376d7a189df066ab56f9
workflow graph collect_pair_files.cwl

https://github.com/mskcc/roslin-cwl.git

Path: modules/pair/collect_pair_files.cwl

Branch/Commit ID: 4034144f39a9428307e82efe1f812c1d37c79de5
workflow graph exome alignment and germline variant detection

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

Path: definitions/subworkflows/germline_detect_variants.cwl

Branch/Commit ID: 457e101e3fb87e7fd792357afce00ed8ccbfbcdb
workflow graph taxonomy_check_16S

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

Path: task_types/tt_taxonomy_check_16S.cwl

Branch/Commit ID: 77a9fa25b89ce73582a1ce6ba75fa6d2537fb8e8
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: e0a30aa1ad516dd2ec0e9ce006428964b840daf4
workflow graph scatter-wf4.cwl#main

https://github.com/common-workflow-language/cwl-v1.1.git

Path: tests/scatter-wf4.cwl

Branch/Commit ID: 368b562a1449e8cd39ae8b7f05926b2bfb9b22df

Packed ID: main