Explore Workflows

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Graph Name Retrieved From View
workflow graph Create tagAlign file

This workflow creates tagAlign file

 https://github.com/ncbi/cwl-ngs-workflows-cbb.git

Path: workflows/File-formats/create-tagAlign.cwl

Branch/Commit ID: 527251ebb77750d02dcc9a370d978a153fc9328f
workflow graph cmsearch-multimodel.cwl

https://github.com/ProteinsWebTeam/ebi-metagenomics-cwl.git

Path: workflows/cmsearch-multimodel.cwl

Branch/Commit ID: 7bb76f33bf40b5cd2604001cac46f967a209c47f
workflow graph 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/)

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

Path: workflows/homer-motif-analysis-peak.cwl

Branch/Commit ID: 7fb8a1ebf8145791440bc2fed9c5f2d78a19d04c
workflow graph foreign_screening.cwl

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

Path: vecscreen/foreign_screening.cwl

Branch/Commit ID: 8fb4ac7f5a66897206c7469101a471108b06eada
workflow graph 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/)

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

Path: workflows/homer-motif-analysis-peak.cwl

Branch/Commit ID: 581156366f91861bd4dbb5bcb59f67d468b32af3
workflow graph exome alignment with qc, no bqsr, no verify_bam_id

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

Path: definitions/pipelines/alignment_exome_nonhuman.cwl

Branch/Commit ID: 174f3b239018328cec1d821947438b457552724c
workflow graph exomeseq-00-prepare-reference-data.cwl

https://github.com/duke-gcb/bespin-cwl.git

Path: subworkflows/exomeseq-00-prepare-reference-data.cwl

Branch/Commit ID: bbe24d8d7fde2e918583b96805909a2867b749d6
workflow graph 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/)

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

Path: workflows/homer-motif-analysis-bg.cwl

Branch/Commit ID: 7fb8a1ebf8145791440bc2fed9c5f2d78a19d04c
workflow graph epigenome-chip-seq.packed.cwl#macs2.cwl

https://github.com/pitagora-network/DAT2-cwl.git

Path: workflow/epigenome-chip-seq/epigenome-chip-seq.packed.cwl

Branch/Commit ID: 69e7c0479af00695127e402962e1d81b6b8142df

Packed ID: macs2.cwl
workflow graph BLAST against rRNA db

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

Path: bacterial_noncoding/wf_blastn.cwl

Branch/Commit ID: 5cc4af517f82f4cda3023644d61abd85cbc1fc18