Explore Workflows
View already parsed workflows here or click here to add your own
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BioExcel-CWL-MDSetup.cwl
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https://github.com/longr/biobb_wf_cwl_tutorial.git
Path: biobb_wf_cwl_tutorial/examples/BioExcel-CWL-MDSetup.cwl Branch/Commit ID: 0d77918a9347b12af11fe71273b0c1f9dccbd2d3 |
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Create Genomic Collection for Bacterial Pipeline, ASN.1 input
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https://github.com/ncbi/pgap.git
Path: genomic_source/wf_genomic_source_asn.cwl Branch/Commit ID: f225cd99b0e0a5043dd102f8b33a6139fefe9ea4 |
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Bismark Methylation - pipeline for BS-Seq data analysis
Sequence reads are first cleaned from adapters and transformed into fully bisulfite-converted forward (C->T) and reverse read (G->A conversion of the forward strand) versions, before they are aligned to similarly converted versions of the genome (also C->T and G->A converted). Sequence reads that produce a unique best alignment from the four alignment processes against the bisulfite genomes (which are running in parallel) are then compared to the normal genomic sequence and the methylation state of all cytosine positions in the read is inferred. A read is considered to align uniquely if an alignment has a unique best alignment score (as reported by the AS:i field). If a read produces several alignments with the same number of mismatches or with the same alignment score (AS:i field), a read (or a read-pair) is discarded altogether. On the next step we extract the methylation call for every single C analysed. The position of every single C will be written out to a new output file, depending on its context (CpG, CHG or CHH), whereby methylated Cs will be labelled as forward reads (+), non-methylated Cs as reverse reads (-). The output of the methylation extractor is then transformed into a bedGraph and coverage file. The bedGraph counts output is then used to generate a genome-wide cytosine report which reports the number on every single CpG (optionally every single cytosine) in the genome, irrespective of whether it was covered by any reads or not. As this type of report is informative for cytosines on both strands the output may be fairly large (~46mn CpG positions or >1.2bn total cytosine positions in the human genome). |
https://github.com/datirium/workflows.git
Path: workflows/bismark-methylation-se.cwl Branch/Commit ID: b957a4f681bf0ca8ebba4e0d0ec3936bf79620c5 |
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Transcriptome Vector Detection
This workflow detect and remove vector from a transcriptome fasta file |
https://github.com/ncbi/cwl-ngs-workflows-cbb.git
Path: workflows/Annotation/transcriptome-vector-detection.cwl Branch/Commit ID: 2667814192299c0c7b4d23c6edb697b6cd636286 |
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wffail.cwl
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https://github.com/common-workflow-language/cwltool.git
Path: tests/wf/wffail.cwl Branch/Commit ID: e6c2d955a448225f026a04130443d13661844440 |
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cluster_blastp_wnode and gpx_qdump combined
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https://github.com/ncbi/pgap.git
Path: task_types/tt_cluster_and_qdump.cwl Branch/Commit ID: 2229f26ec424f9ebeb3db7fec3bd3f84a38c7485 |
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Build Bowtie indices
Workflow runs [Bowtie](http://bowtie-bio.sourceforge.net/tutorial.shtml) v1.2.0 (12/30/2016) to build indices for reference genome provided in a single FASTA file as fasta_file input. Generated indices are saved in a folder with the name that corresponds to the input genome |
https://github.com/datirium/workflows.git
Path: workflows/bowtie-index.cwl Branch/Commit ID: d1bef74924efcb8bfaa00987b3f148d5a192b7a9 |
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echo-wf.cwl
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https://github.com/common-workflow-language/cwltool.git
Path: tests/override/echo-wf.cwl Branch/Commit ID: e6c2d955a448225f026a04130443d13661844440 |
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Detect Docm variants
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https://github.com/genome/analysis-workflows.git
Path: definitions/subworkflows/docm_cle.cwl Branch/Commit ID: eb0092603bf57acb7bda08a06e4f2f1e2a8c9b6d |
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step-valuefrom2-wf.cwl
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https://github.com/common-workflow-language/cwltool.git
Path: cwltool/schemas/v1.0/v1.0/step-valuefrom2-wf.cwl Branch/Commit ID: e6c2d955a448225f026a04130443d13661844440 |
