Explore Workflows

View already parsed workflows here or click here to add your own

Graph Name Retrieved From View
workflow graph kmer_cache_retrieve

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

Path: task_types/tt_kmer_cache_retrieve.cwl

Branch/Commit ID: 2afb5ebafd1353ba063cc74ee9a7eaf347afce5c
workflow graph kmer_cache_store

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

Path: task_types/tt_kmer_cache_store.cwl

Branch/Commit ID: cb15f907132fb90bc66b39bb0af3c211801feba1
workflow graph scatter2.cwl

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

Path: tests/wf/scatter2.cwl

Branch/Commit ID: 8ef515037de411abd2f84b569ad4d4a4f7a2c7a0
workflow graph trim-chipseq-pe.cwl

Runs ChIP-Seq BioWardrobe basic analysis with paired-end input data files.

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

Path: workflows/trim-chipseq-pe.cwl

Branch/Commit ID: 4b8bb1a1ec39056253ca8eee976078e51f4a954e
workflow graph wgs alignment and germline variant detection

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

Path: definitions/pipelines/germline_wgs.cwl

Branch/Commit ID: f77a920bcc73f6cfdb091eed75a149d02cd8a263
workflow graph Prepare user input

Prepare user input for NCBI-PGAP pipeline

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

Path: prepare_user_input2.cwl

Branch/Commit ID: 54c5074587af001a44eccb4762a4cb25fa24cb3e
workflow graph Single-cell Format Transform

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
workflow graph Bismark Methylation PE

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
workflow graph tt_blastn_wnode

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

Path: task_types/tt_blastn_wnode.cwl

Branch/Commit ID: 54c5074587af001a44eccb4762a4cb25fa24cb3e
workflow graph readgroup_fastq_pe.cwl

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

Path: workflows/bamfastq_align/readgroup_fastq_pe.cwl

Branch/Commit ID: 6b43e8b03256492f2b36ffcf548704daaafee6f6