Explore Workflows

Prepare user input for NCBI-PGAP pipeline

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

Path: prepare_user_input2.cwl

Branch/Commit ID: 54c5074587af001a44eccb4762a4cb25fa24cb3e

Single-cell Format Transform Transforms single-cell sequencing data formats into Cell Ranger like output.

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

Path: workflows/sc-format-transform.cwl

Branch/Commit ID: 30031ca5e69cec603c4733681de54dc7bffa20a3

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-pe.cwl

Branch/Commit ID: 30031ca5e69cec603c4733681de54dc7bffa20a3

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

Path: task_types/tt_blastn_wnode.cwl

Branch/Commit ID: 54c5074587af001a44eccb4762a4cb25fa24cb3e

https://github.com/nci-gdc/gdc-dnaseq-cwl.git

Path: workflows/bamfastq_align/readgroup_fastq_pe.cwl

Branch/Commit ID: 6b43e8b03256492f2b36ffcf548704daaafee6f6

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

Path: tests/wf/nested.cwl

Branch/Commit ID: e2ec740fccc81ff7071dcd607c5c158fbc0dfb90

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

Path: definitions/pipelines/aml_trio_cle_gathered.cwl

Branch/Commit ID: f77a920bcc73f6cfdb091eed75a149d02cd8a263

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

Path: tests/wf/mut3.cwl

Branch/Commit ID: ecdfe1ee769d05790f70ac87a711131f441f3753

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

Path: cwltool/schemas/v1.0/v1.0/basename-fields-test.cwl

Branch/Commit ID: a858bb4db58ef2df17b4856294ad7904643c5c6e

This workflow uses MEME suite for motif finding

https://github.com/ncbi/cwl-ngs-workflows-cbb.git

Path: workflows/ChIP-Seq/meme-motif.cwl

Branch/Commit ID: 0207b0171ab142dfb85db9c39050c5b4be51dd9e