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Graph Name Retrieved From View
workflow graph LBA_calibrator.cwl

https://git.astron.nl/RD/LINC.git

Path: workflows/LBA_calibrator.cwl

Branch/Commit ID: 0c5bd78e3f2d08564f5c9a563bcc8bb7704e6202

workflow graph Seed Search Compartments

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

Path: protein_alignment/wf_seed.cwl

Branch/Commit ID: 54c5074587af001a44eccb4762a4cb25fa24cb3e

workflow graph chipseq-gen-bigwig.cwl

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

Path: workflows/chipseq-gen-bigwig.cwl

Branch/Commit ID: 4b8bb1a1ec39056253ca8eee976078e51f4a954e

workflow graph Run tRNAScan

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

Path: bacterial_trna/wf_trnascan.cwl

Branch/Commit ID: 54c5074587af001a44eccb4762a4cb25fa24cb3e

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: b4d578c2ba4713a5a22163d9f8c7105acda1f22e

workflow graph scatter-valuefrom-wf4.cwl#main

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

Path: cwltool/schemas/v1.0/v1.0/scatter-valuefrom-wf4.cwl

Branch/Commit ID: 8010fd2bf1e7090ba6df6ca8c84bbb96e2272d32

Packed ID: main

workflow graph 1st-workflow.cwl

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

Path: tests/wf/1st-workflow.cwl

Branch/Commit ID: ae401a813472ca453a99ad067a5e6fc3bd71112b

workflow graph heatmap.cwl

Generates ATDP heatmap centered on TSS from an array of input BAM files and genelist TSV file. Returns array of heatmap JSON files with the names that have the same basenames as input BAM files, but with .json extension

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

Path: workflows/heatmap.cwl

Branch/Commit ID: cb5e5b8563be4977e9f2babc14fe084faa234847

workflow graph gp_makeblastdb

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

Path: progs/gp_makeblastdb.cwl

Branch/Commit ID: f18c1dce463509170ee3bf2844d5a3637ff706f5

workflow graph readgroups_bam_to_readgroups_fastq_lists.cwl

https://github.com/nci-gdc/gdc-dnaseq-cwl.git

Path: workflows/bamfastq_align/readgroups_bam_to_readgroups_fastq_lists.cwl

Branch/Commit ID: 6b43e8b03256492f2b36ffcf548704daaafee6f6