Explore Workflows
View already parsed workflows here or click here to add your own
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Per-region pindel
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Path: definitions/subworkflows/pindel_cat.cwl Branch/Commit ID: 2f65fc96207a71b1cda4e246f808bed056608cd0 |
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Per-chromosome pindel
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Path: definitions/subworkflows/pindel_cat.cwl Branch/Commit ID: 44ada20f3eeb59005d5bd999d2435102e9bae991 |
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Bisulfite QC tools
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Path: definitions/subworkflows/bisulfite_qc.cwl Branch/Commit ID: 049f4aeff4c4a1b8421cac9b1c1c1f0da5848315 |
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PCA - Principal Component Analysis
Principal Component Analysis -------------- Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables (entities each of which takes on various numerical values) into a set of values of linearly uncorrelated variables called principal components. The calculation is done by a singular value decomposition of the (centered and possibly scaled) data matrix, not by using eigen on the covariance matrix. This is generally the preferred method for numerical accuracy. |
Path: workflows/pca.cwl Branch/Commit ID: dda9e6e06a656b7b3fa7504156474b962fe3953c |
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tt_blastn_wnode
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Path: task_types/tt_blastn_wnode.cwl Branch/Commit ID: 16e3915d2a357e2a861b30911c832e5ddc0c1784 |
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trimmed_fastq
Quality Control and Raw Data trimming |
Path: structuralvariants/subworkflows/trimmed_fastq.cwl Branch/Commit ID: 86f2f3fb64e916607637d93cf6715bab90b1f1d3 |
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mut2.cwl
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Path: tests/wf/mut2.cwl Branch/Commit ID: 83038feb2a6fc3bab952e1ecc2a11bfbc8c557b4 |
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indices-header.cwl
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Path: metadata/indices-header.cwl Branch/Commit ID: 57863b6131d8262c5ce864adaf8e4038401e71a2 |
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timelimit3-wf.cwl
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Path: tests/timelimit3-wf.cwl Branch/Commit ID: 368b562a1449e8cd39ae8b7f05926b2bfb9b22df |
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step-valuefrom3-wf_v1_2.cwl
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Path: testdata/step-valuefrom3-wf_v1_2.cwl Branch/Commit ID: 77669d4dd1d1ebd2bdd9810f911608146d9b8e51 |
