Explore Workflows

https://github.com/common-workflow-language/cwl-v1.1.git

Path: tests/io-union-input-default-wf.cwl

Branch/Commit ID: e515226f8ac0f7985cd94dae4a301150adae3050

https://github.com/genome/analysis-workflows.git

Path: definitions/pipelines/germline_wgs.cwl

Branch/Commit ID: adcae308fdccaa1190083616118dfadb4df65dca

Reverse the lines in a document, then sort those lines.

https://github.com/common-workflow-language/cwltool.git

Path: tests/wf/trick_revsort.cwl

Branch/Commit ID: 7bfe73a708dbf31d037303bb5a8fed1a79984b0f

https://github.com/ncbi/pgap.git

Path: task_types/tt_ani_top_n.cwl

Branch/Commit ID: 369e2b6c7f4db75099d258729dec1326f55d2cc5

https://github.com/genome/analysis-workflows.git

Path: definitions/subworkflows/germline_filter_vcf.cwl

Branch/Commit ID: 2f65fc96207a71b1cda4e246f808bed056608cd0

https://github.com/ncbi/pgap.git

Path: task_types/tt_extract_gencoll_ids.cwl

Branch/Commit ID: 1b8d71c75156a1a62bf0477d59db26010e2dcc29

Both `islands_file` and `islands_control_file` should be produced by the same cwl tool (iaintersect.cwl or macs2-callpeak-biowardrobe-only.cwl)

https://github.com/Barski-lab/workflows.git

Path: workflows/super-enhancer.cwl

Branch/Commit ID: 749460273e6c8d9e8b7d2395f0ac157701d3495e

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: 57863b6131d8262c5ce864adaf8e4038401e71a2

Cell Ranger Count (RNA+ATAC) Quantifies single-cell gene expression and chromatin accessibility of the sequencing data from a single 10x Genomics library in a combined manner. The results of this workflow are primarily used in either “Single-Cell Multiome ATAC and RNA-Seq Filtering Analysis” or “Cell Ranger Aggregate (RNA+ATAC)” pipelines.

https://github.com/datirium/workflows.git

Path: workflows/cellranger-arc-count.cwl

Branch/Commit ID: 57863b6131d8262c5ce864adaf8e4038401e71a2

https://github.com/griffithlab/pmbio.org.git

Path: assets/CWL/workflow.cwl

Branch/Commit ID: ac15c607dbc7c9da0bd3bf70eaa44ba357bf6a30