Explore Workflows
View already parsed workflows here or click here to add your own
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Unaligned bam to sorted, markduped bam
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Path: definitions/subworkflows/align_sort_markdup.cwl Branch/Commit ID: 1585504ccffafac53b1594349ed934f45206ee2b |
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downsample unaligned BAM and align
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Path: definitions/subworkflows/downsampled_alignment.cwl Branch/Commit ID: 72c4c3115956340f35e72cda1fd46ec276f1ca03 |
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schemadef-wf.cwl
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Path: cwltool/schemas/v1.0/v1.0/schemadef-wf.cwl Branch/Commit ID: 31aa094dce60cbb176229d6b918bfd5ae09c0390 |
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Merge, annotate, and generate a TSV for SVs
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Path: definitions/subworkflows/merge_svs.cwl Branch/Commit ID: 28d1065759cbd389594ee33b41fd1103ced5436d |
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ani_top_n
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Path: task_types/tt_ani_top_n.cwl Branch/Commit ID: dc6014dc7c1f160ec4ae3d5a57388a6dceaacbc5 |
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blastp_wnode_naming
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Path: task_types/tt_blastp_wnode_naming.cwl Branch/Commit ID: 909f26beaf96c2cdfe208f87ecd1e9c3de20b81c |
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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: 8aa85573e659ef67163537d6811afdddcfad53dc |
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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: 78955730b492047429e00d0a0620d37efb6dbbfe |
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WGS QC workflow
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Path: definitions/subworkflows/qc_wgs.cwl Branch/Commit ID: 6bfb64375e7ebb6eb40f463ede86d8deccdb9eff |
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count-lines6-wf.cwl
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Path: cwltool/schemas/v1.0/v1.0/count-lines6-wf.cwl Branch/Commit ID: 31aa094dce60cbb176229d6b918bfd5ae09c0390 |
