Explore Workflows
View already parsed workflows here or click here to add your own
Graph | Name | Retrieved From | View |
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Single-Cell Preprocessing Pipeline
Devel version of Single-Cell Preprocessing Pipeline =================================================== |
https://github.com/datirium/workflows.git
Path: workflows/single-cell-preprocess.cwl Branch/Commit ID: 60854b5d299df91e135e05d02f4be61f6a310fbc |
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kmer_ref_compare_wnode
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https://github.com/ncbi/pgap.git
Path: task_types/tt_kmer_ref_compare_wnode.cwl Branch/Commit ID: 92118627c800e4addb7e29b9dabcca073a5bae71 |
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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 |
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cmsearch-multimodel.cwl
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https://github.com/ProteinsWebTeam/ebi-metagenomics-cwl.git
Path: workflows/cmsearch-multimodel.cwl Branch/Commit ID: 7bb76f33bf40b5cd2604001cac46f967a209c47f |
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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/) |
https://github.com/datirium/workflows.git
Path: workflows/homer-motif-analysis-peak.cwl Branch/Commit ID: 7fb8a1ebf8145791440bc2fed9c5f2d78a19d04c |
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foreign_screening.cwl
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https://github.com/ncbi/pgap.git
Path: vecscreen/foreign_screening.cwl Branch/Commit ID: 8fb4ac7f5a66897206c7469101a471108b06eada |
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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/) |
https://github.com/datirium/workflows.git
Path: workflows/homer-motif-analysis-peak.cwl Branch/Commit ID: 581156366f91861bd4dbb5bcb59f67d468b32af3 |
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exome alignment with qc, no bqsr, no verify_bam_id
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https://github.com/genome/analysis-workflows.git
Path: definitions/pipelines/alignment_exome_nonhuman.cwl Branch/Commit ID: 174f3b239018328cec1d821947438b457552724c |
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exomeseq-00-prepare-reference-data.cwl
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https://github.com/duke-gcb/bespin-cwl.git
Path: subworkflows/exomeseq-00-prepare-reference-data.cwl Branch/Commit ID: bbe24d8d7fde2e918583b96805909a2867b749d6 |
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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/) |
https://github.com/datirium/workflows.git
Path: workflows/homer-motif-analysis-bg.cwl Branch/Commit ID: 7fb8a1ebf8145791440bc2fed9c5f2d78a19d04c |