Explore Workflows
View already parsed workflows here or click here to add your own
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step-valuefrom3-wf.cwl
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Path: cwltool/schemas/v1.0/v1.0/step-valuefrom3-wf.cwl Branch/Commit ID: e8b3565a008d95859fc44227987a54e6a53a8c29 |
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Bisulfite QC tools
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Path: definitions/subworkflows/bisulfite_qc.cwl Branch/Commit ID: 3f3b186da9bf82a5e2ae74ba27aef35a46174ebe |
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step-valuefrom-wf.cwl
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Path: tests/step-valuefrom-wf.cwl Branch/Commit ID: e515226f8ac0f7985cd94dae4a301150adae3050 |
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Whole genome alignment and somatic variant detection
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Path: definitions/pipelines/somatic_wgs.cwl Branch/Commit ID: 3034168d652bfa930ba09af20e473a4564a8010d |
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THOR - differential peak calling of ChIP-seq signals with replicates
What is THOR? -------------- THOR is an HMM-based approach to detect and analyze differential peaks in two sets of ChIP-seq data from distinct biological conditions with replicates. THOR performs genomic signal processing, peak calling and p-value calculation in an integrated framework. For more information please refer to: ------------------------------------- Allhoff, M., Sere K., Freitas, J., Zenke, M., Costa, I.G. (2016), Differential Peak Calling of ChIP-seq Signals with Replicates with THOR, Nucleic Acids Research, epub gkw680. |
Path: workflows/rgt-thor.cwl Branch/Commit ID: 87f213456b3f966b773d396cce1fe5a272dad858 |
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tt_kmer_top_n.cwl
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Path: task_types/tt_kmer_top_n.cwl Branch/Commit ID: 7b21dc40840852f3942c31b9c472346ea3f9a3ca |
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count-lines9-wf-noET.cwl
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Path: v1.0/v1.0/count-lines9-wf-noET.cwl Branch/Commit ID: 9a23706ec061c5d2c02ff60238d218aadf0b5db9 |
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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: 7ae3b75bbe614e59cdeaba06047234a6c40c0fe9 |
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Hello World
Outputs a message using echo |
Path: tests/wf/hello-workflow.cwl Branch/Commit ID: aec33fcfa3459a90cbba8c88ebb991be94d21429 |
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DESeq2 Multi-factor Analysis
DESeq2 Multi-factor Analysis Runs DeSeq2 multi-factor analysis with manual control over major parameters |
Path: workflows/deseq-multi-factor.cwl Branch/Commit ID: 7ae3b75bbe614e59cdeaba06047234a6c40c0fe9 |
