Explore Workflows
View already parsed workflows here or click here to add your own
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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: c5bae2ca862c764911b83d1f15ff6af4e2a0db28 |
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Seed Protein Alignments
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Path: protein_alignment/wf_seed_seqids.cwl Branch/Commit ID: 8ea3637b0f11eac1ea5599c41d74e00d85fb778d |
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output-arrays-int-wf.cwl
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Path: tests/output-arrays-int-wf.cwl Branch/Commit ID: e62f99dd79d6cb9c157cceb458f74200da84f6e9 |
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gathered exome alignment and somatic variant detection
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Path: definitions/pipelines/somatic_exome_gathered.cwl Branch/Commit ID: 5be54bf09092c53e6c7797a875f64a360d511d7f |
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umccrise-pipeline__2.3.0--0.cwl
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Path: workflows/umccrise-pipeline/2.3.0--0/umccrise-pipeline__2.3.0--0.cwl Branch/Commit ID: f10607b6b86e4d119c8f3279d67e537b91ba2365 |
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bam to trimmed fastqs and biscuit alignments
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Path: definitions/subworkflows/bam_to_trimmed_fastq_and_biscuit_alignments.cwl Branch/Commit ID: 3ee63d8757c341ca98b3b46ec4782862ad19b710 |
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mut.cwl
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Path: tests/wf/mut.cwl Branch/Commit ID: 78fe9d41ee5a44f8725dfbd7028e4a5ee42949cf |
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Unaligned to aligned BAM
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Path: definitions/subworkflows/align.cwl Branch/Commit ID: e59c77629936fad069007ba642cad49fef7ad29f |
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tt_univec_wnode.cwl
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Path: task_types/tt_univec_wnode.cwl Branch/Commit ID: 686b570a9fa46f3ace3f8e9935490b75df86a1fc |
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echo-wf-default.cwl
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Path: cwltool/schemas/v1.0/v1.0/echo-wf-default.cwl Branch/Commit ID: 4635090ef98247b1902b3c7a25c007d9db1cb883 |
