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Motif Finding with HOMER with custom background regions
Motif Finding with HOMER with custom 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. For more information please refer to: ------------------------------------- [Official documentation](http://homer.ucsd.edu/homer/motif/) |
![]() Path: workflows/homer-motif-analysis-bg.cwl Branch/Commit ID: 29bf638904709cfbf10908adcd51ba4886ace94a |
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Tumor-Only Detect Variants workflow
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![]() Path: definitions/pipelines/tumor_only_detect_variants.cwl Branch/Commit ID: 233f026ffce240071edda526391be0c03186fce8 |
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Raw sequence data to BQSR
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![]() Path: definitions/subworkflows/sequence_to_bqsr.cwl Branch/Commit ID: 457e101e3fb87e7fd792357afce00ed8ccbfbcdb |
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kmer_cache_retrieve
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![]() Path: task_types/tt_kmer_cache_retrieve.cwl Branch/Commit ID: 8dcf1cc79ea26e9fec999e77ceae1aebfff2cff6 |
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align_sort_sa
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![]() Path: task_types/tt_align_sort_sa.cwl Branch/Commit ID: 5331b0836aa7c451d759ef39dc2062000ac21a47 |
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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: e0a30aa1ad516dd2ec0e9ce006428964b840daf4 |
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WGS QC workflow mouse
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![]() Path: definitions/subworkflows/qc_wgs_mouse.cwl Branch/Commit ID: 449bc7e45bb02316d040f73838ef18359e770268 |
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count-lines12-wf.cwl
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![]() Path: cwltool/schemas/v1.0/v1.0/count-lines12-wf.cwl Branch/Commit ID: 814bd0405a7701efc7d63e8f0179df394c7766f7 |
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SSU-from-tablehits.cwl
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![]() Path: tools/SSU-from-tablehits.cwl Branch/Commit ID: 0cd2d70d63a8ceb2de28f0faac19c919a7bd35ff |
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align_merge_sas
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![]() Path: task_types/tt_align_merge_sas.cwl Branch/Commit ID: 2229f26ec424f9ebeb3db7fec3bd3f84a38c7485 |