Explore Workflows
View already parsed workflows here or click here to add your own
Graph | Name | Retrieved From | View |
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createindex.cwl
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![]() Path: workflow/createindex.cwl Branch/Commit ID: 49faf55f97c8f3084b426d2db6640519d6f2ce71 |
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joint genotyping for trios or small cohorts
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![]() Path: definitions/subworkflows/joint_genotype.cwl Branch/Commit ID: 061d3a2fbcd8a1c39c0b38c549e528deb24a9d54 |
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scatter-valuefrom-wf4.cwl#main
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![]() Path: cwltool/schemas/v1.0/v1.0/scatter-valuefrom-wf4.cwl Branch/Commit ID: 03af16c9df2ee77485d4ab092cd64ae096d2e71c Packed ID: main |
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count-lines2-wf.cwl
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![]() Path: cwltool/schemas/v1.0/v1.0/count-lines2-wf.cwl Branch/Commit ID: 3e9bca4e006eae7e9febd76eb9b8292702eba2cb |
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hmmsearch_wnode and gpx_qdump combined workflow to apply scatter/gather
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![]() Path: task_types/tt_hmmsearch_wnode_plus_qdump.cwl Branch/Commit ID: 146df33e2e44afa2a608ac72c036e6b6b871af93 |
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dynresreq-workflow.cwl
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![]() Path: cwltool/schemas/v1.0/v1.0/dynresreq-workflow.cwl Branch/Commit ID: 3e9bca4e006eae7e9febd76eb9b8292702eba2cb |
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Subworkflow to allow calling cnvkit with cram instead of bam files
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![]() Path: definitions/subworkflows/cram_to_cnvkit.cwl Branch/Commit ID: 441b85003fdc10cf4cbf333d89acb4d23b0fef32 |
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AltAnalyze ICGS
AltAnalyze ICGS =============== |
![]() Path: workflows/altanalyze-icgs.cwl Branch/Commit ID: 1a46cb0e8f973481fe5ae3ae6188a41622c8532e |
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QuantSeq 3' FWD, FWD-UMI or REV for single-read mRNA-Seq data
### Devel version of QuantSeq 3' FWD, FWD-UMI or REV for single-read mRNA-Seq data |
![]() Path: workflows/trim-quantseq-mrnaseq-se-strand-specific.cwl Branch/Commit ID: a8eaf61c809d76f55780b14f2febeb363cf6373f |
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Motif Finding with HOMER with target and background regions from peaks
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/) |
![]() Path: workflows/homer-motif-analysis-peak.cwl Branch/Commit ID: 10ce6e113f749c7bd725e426445220c3bdc5ddf1 |