Explore Workflows

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Graph Name Retrieved From View
workflow graph blastp_wnode_naming

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

Path: task_types/tt_blastp_wnode_naming.cwl

Branch/Commit ID: d218e081d8f6a4fdab56a38ce0fc2fae6216cecc
workflow graph scatter GATK HaplotypeCaller over intervals

https://github.com/genome/cancer-genomics-workflow.git

Path: detect_variants/gatk_haplotypecaller_iterator.cwl

Branch/Commit ID: 6eb7d35ad46207f4ff49e84106b717e17331eb4b
workflow graph Running cellranger count and lineage inference

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

Path: definitions/subworkflows/single_cell_rnaseq.cwl

Branch/Commit ID: 31602b94b34ff55876147c7299e1bec47e8d1a31
workflow graph Generate genome indices for STAR & bowtie

Creates indices for: * [STAR](https://github.com/alexdobin/STAR) v2.5.3a (03/17/2017) PMID: [23104886](https://www.ncbi.nlm.nih.gov/pubmed/23104886) * [bowtie](http://bowtie-bio.sourceforge.net/tutorial.shtml) v1.2.0 (12/30/2016) It performs the following steps: 1. `STAR --runMode genomeGenerate` to generate indices, based on [FASTA](http://zhanglab.ccmb.med.umich.edu/FASTA/) and [GTF](http://mblab.wustl.edu/GTF2.html) input files, returns results as an array of files 2. Outputs indices as [Direcotry](http://www.commonwl.org/v1.0/CommandLineTool.html#Directory) data type 3. Separates *chrNameLength.txt* file from Directory output 4. `bowtie-build` to generate indices requires genome [FASTA](http://zhanglab.ccmb.med.umich.edu/FASTA/) file as input, returns results as a group of main and secondary files

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

Path: workflows/genome-indices.cwl

Branch/Commit ID: 00ea05e22788029370898fd4c17798b11edf0e57
workflow graph MEME motif

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: 7364aa3799fd3bd7584049228618301bda53a3af
workflow graph align_merge_sas

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

Path: task_types/tt_align_merge_sas.cwl

Branch/Commit ID: 50d161364e2859ed5c95ef07c9f7234f1431cf31
workflow graph assm_assm_blastn_wnode

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

Path: task_types/tt_assm_assm_blastn_wnode.cwl

Branch/Commit ID: be32f1363f9a9a9247d738e9593b207e9c5172c8
workflow graph Single-Cell ATAC-Seq Differential Accessibility Analysis

Single-Cell ATAC-Seq Differential Accessibility Analysis Identifies differentially accessible regions between any two groups of cells, optionally aggregating chromatin accessibility data from single-cell to pseudobulk form.

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

Path: workflows/sc-atac-dbinding.cwl

Branch/Commit ID: cc6fa135d04737fdde3b4414d6e214cf8c812f6e
workflow graph Bismark Methylation SE

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: cc6fa135d04737fdde3b4414d6e214cf8c812f6e
workflow graph hmmsearch_wnode and gpx_qdump combined workflow to apply scatter/gather

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

Path: task_types/tt_hmmsearch_wnode_plus_qdump.cwl

Branch/Commit ID: 76a9637a06e2102645eae29aff10b6f7185892a5