Explore Workflows

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

Graph	Name	Retrieved From	View
	mutect parallel workflow	https://github.com/genome/analysis-workflows.git Path: definitions/subworkflows/mutect.cwl Branch/Commit ID: 49508a2757ff2f49f1c200774a38af1c12b531bf
	run-one.cwl	https://github.com/hubmapconsortium/hra-workflows.git Path: steps/run-one.cwl Branch/Commit ID: 118a0e83052b6edfb72dd46bab8828314a0db34c
	protein annotation Proteins - predict, filter, cluster, identify, annotate	https://github.com/MG-RAST/pipeline.git Path: CWL/Workflows/protein-filter-annotation.workflow.cwl Branch/Commit ID: d9cf22cd615542c94f7974e8bce4cf29b24d985f
	preprocess fasta Remove reads from fasta files based on sequence stats. Return fasta files with reads passed and reads removed.	https://github.com/MG-RAST/pipeline.git Path: CWL/Workflows/preprocess-fasta.workflow.cwl Branch/Commit ID: d9cf22cd615542c94f7974e8bce4cf29b24d985f
	screen out taxa Remove sequences which align against a reference set using bowtie2. The references are preformatted (index files)	https://github.com/MG-RAST/pipeline.git Path: CWL/Workflows/organism-screening.workflow.cwl Branch/Commit ID: d9cf22cd615542c94f7974e8bce4cf29b24d985f
	abundance abundace profiles from annotated files, for protein and/or rna	https://github.com/MG-RAST/pipeline.git Path: CWL/Workflows/abundance-clca.workflow.cwl Branch/Commit ID: d9cf22cd615542c94f7974e8bce4cf29b24d985f
	count-lines11-null-step-wf-noET.cwl	https://github.com/common-workflow-language/cwl-v1.2.git Path: tests/count-lines11-null-step-wf-noET.cwl Branch/Commit ID: 707ebcd2173889604459c5f4ffb55173c508abb3
	ChIP-Seq pipeline single-read The original [BioWardrobe's](https://biowardrobe.com) [PubMed ID:26248465](https://www.ncbi.nlm.nih.gov/pubmed/26248465) ChIP-Seq basic analysis workflow for a single-read experiment. A [FASTQ](http://maq.sourceforge.net/fastq.shtml) input file has to be provided. The pipeline produces a sorted BAM file alongside with index BAI file, quality statistics of the input FASTQ file, coverage by estimated fragments as a BigWig file, peaks calling data in a form of narrowPeak or broadPeak files, islands with the assigned nearest genes and region type, data for average tag density plot. Workflow starts with step fastx\_quality\_stats from FASTX-Toolkit to calculate quality statistics for input FASTQ file. At the same time `bowtie` is used to align reads from input FASTQ file to reference genome bowtie\_aligner. The output of this step is an unsorted SAM file which is being sorted and indexed by `samtools sort` and `samtools index` samtools\_sort\_index. Depending on workflow’s input parameters indexed and sorted BAM file can be processed by `samtools rmdup` samtools\_rmdup to get rid of duplicated reads. If removing duplicates is not required the original BAM and BAI files are returned. Otherwise step samtools\_sort\_index\_after\_rmdup repeat `samtools sort` and `samtools index` with BAM and BAI files without duplicates. Next `macs2 callpeak` performs peak calling macs2\_callpeak and the next step reports macs2\_island\_count the number of islands and estimated fragment size. If the latter is less that 80bp (hardcoded in the workflow) `macs2 callpeak` is rerun again with forced fixed fragment size value (macs2\_callpeak\_forced). It is also possible to force MACS2 to use pre set fragment size in the first place. Next step (macs2\_stat) is used to define which of the islands and estimated fragment size should be used in workflow output: either from macs2\_island\_count step or from macs2\_island\_count\_forced step. If input trigger of this step is set to True it means that macs2\_callpeak\_forced step was run and it returned different from macs2\_callpeak step results, so macs2\_stat step should return [fragments\_new, fragments\_old, islands\_new], if trigger is False the step returns [fragments\_old, fragments\_old, islands\_old], where sufix \"old\" defines results obtained from macs2\_island\_count step and sufix \"new\" - from macs2\_island\_count\_forced step. The following two steps (bamtools\_stats and bam\_to\_bigwig) are used to calculate coverage from BAM file and save it in BigWig format. For that purpose bamtools stats returns the number of mapped reads which is then used as scaling factor by bedtools genomecov when it performs coverage calculation and saves it as a BEDgraph file whichis then sorted and converted to BigWig format by bedGraphToBigWig tool from UCSC utilities. Step get\_stat is used to return a text file with statistics in a form of [TOTAL, ALIGNED, SUPRESSED, USED] reads count. Step island\_intersect assigns nearest genes and regions to the islands obtained from macs2\_callpeak\_forced. Step average\_tag\_density is used to calculate data for average tag density plot from the BAM file.	https://github.com/datirium/workflows.git Path: workflows/chipseq-se.cwl Branch/Commit ID: bfa3843bcf36125ff258d6314f64b41336f06e6b
	Seed Protein Alignments	https://github.com/ncbi/pgap.git Path: protein_alignment/wf_seed_1.cwl Branch/Commit ID: 656113dcac0de7cef6cff6c688f61441ee05872a
	RNA-seq (VCF) alelle specific pipeline for single-read data Allele specific RNA-Seq (using vcf) single-read workflow	https://github.com/datirium/workflows.git Path: workflows/allele-vcf-rnaseq-se.cwl Branch/Commit ID: b141f7e73005227d6d02fa03a47151836dd4109b