Explore Workflows
View already parsed workflows here or click here to add your own
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cwlsite.cwl
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![]() Path: cwltool/schemas/site/cwlsite.cwl Branch/Commit ID: 814bd0405a7701efc7d63e8f0179df394c7766f7 |
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kmer_seq_entry_extract_wnode
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![]() Path: task_types/tt_kmer_seq_entry_extract_wnode.cwl Branch/Commit ID: f225cd99b0e0a5043dd102f8b33a6139fefe9ea4 |
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kmer_seq_entry_extract_wnode
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![]() Path: task_types/tt_kmer_seq_entry_extract_wnode.cwl Branch/Commit ID: 2229f26ec424f9ebeb3db7fec3bd3f84a38c7485 |
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tt_kmer_compare_wnode
Pairwise comparison |
![]() Path: task_types/tt_kmer_compare_wnode.cwl Branch/Commit ID: f225cd99b0e0a5043dd102f8b33a6139fefe9ea4 |
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tt_kmer_compare_wnode
Pairwise comparison |
![]() Path: task_types/tt_kmer_compare_wnode.cwl Branch/Commit ID: 2229f26ec424f9ebeb3db7fec3bd3f84a38c7485 |
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kfdrc_alignment_wf_cyoa.cwl
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![]() Path: workflows/kfdrc_alignment_wf_cyoa.cwl Branch/Commit ID: d822501de724a7c8ecf49a2d9f15fbb62029afd1 |
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schemadef-wf.cwl
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![]() Path: v1.0/v1.0/schemadef-wf.cwl Branch/Commit ID: 148f11b11d31c098196e649f680797f0b4680114 |
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bgzip and index VCF
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![]() Path: definitions/subworkflows/bgzip_and_index.cwl Branch/Commit ID: eb0092603bf57acb7bda08a06e4f2f1e2a8c9b6d |
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vardictGermlineVariantCaller_v0_1_0.cwl
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![]() Path: janis_pipelines/wgs_germline/cwl/tools/vardictGermlineVariantCaller_v0_1_0.cwl Branch/Commit ID: 67f1401030337d9ba36f23d4a2bf8366764786b5 |
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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: b957a4f681bf0ca8ebba4e0d0ec3936bf79620c5 |