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workflow graph RNA-Seq pipeline paired-end

The original [BioWardrobe's](https://biowardrobe.com) [PubMed ID:26248465](https://www.ncbi.nlm.nih.gov/pubmed/26248465) **RNA-Seq** basic analysis for a **paired-end** experiment. A corresponded input [FASTQ](http://maq.sourceforge.net/fastq.shtml) file has to be provided. Current workflow should be used only with the paired-end RNA-Seq data. It performs the following steps: 1. Use STAR to align reads from input FASTQ files according to the predefined reference indices; generate unsorted BAM file and alignment statistics file 2. Use fastx_quality_stats to analyze input FASTQ files and generate quality statistics files 3. Use samtools sort to generate coordinate sorted BAM(+BAI) file pair from the unsorted BAM file obtained on the step 1 (after running STAR) 4. Generate BigWig file on the base of sorted BAM file 5. Map input FASTQ files to predefined rRNA reference indices using Bowtie to define the level of rRNA contamination; export resulted statistics to file 6. Calculate isoform expression level for the sorted BAM file and GTF/TAB annotation file using GEEP reads-counting utility; export results to file

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

Path: workflows/rnaseq-pe.cwl

Branch/Commit ID: 2cad55523d1b4ee7fd9e64df0f6263c6545e4b0e
workflow graph RNA-Seq pipeline single-read strand specific

Note: should be updated The original [BioWardrobe's](https://biowardrobe.com) [PubMed ID:26248465](https://www.ncbi.nlm.nih.gov/pubmed/26248465) **RNA-Seq** basic analysis for **strand specific single-read** experiment. A corresponded input [FASTQ](http://maq.sourceforge.net/fastq.shtml) file has to be provided. Current workflow should be used only with the single-read RNA-Seq data. It performs the following steps: 1. Use STAR to align reads from input FASTQ file according to the predefined reference indices; generate unsorted BAM file and alignment statistics file 2. Use fastx_quality_stats to analyze input FASTQ file and generate quality statistics file 3. Use samtools sort to generate coordinate sorted BAM(+BAI) file pair from the unsorted BAM file obtained on the step 1 (after running STAR) 5. Generate BigWig file on the base of sorted BAM file 6. Map input FASTQ file to predefined rRNA reference indices using Bowtie to define the level of rRNA contamination; export resulted statistics to file 7. Calculate isoform expression level for the sorted BAM file and GTF/TAB annotation file using GEEP reads-counting utility; export results to file

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

Path: workflows/rnaseq-se-dutp.cwl

Branch/Commit ID: 2cad55523d1b4ee7fd9e64df0f6263c6545e4b0e
workflow graph ChIP-Seq pipeline paired-end

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 **paired-end** 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-pe.cwl

Branch/Commit ID: 480e99a4bb3046e0565113d9dca294e0895d3b0c
workflow graph allele-process-reference.cwl

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

Path: subworkflows/allele-process-reference.cwl

Branch/Commit ID: 00ced0fc44ceeb3495e891232e1000235e56ee6b
workflow graph count-lines8-wf.cwl

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

Path: cwltool/schemas/v1.0/v1.0/count-lines8-wf.cwl

Branch/Commit ID: f997d13af87216e9b5048c732a511053c7ba714c
workflow graph snaptools_create_snap_file.cwl

https://github.com/denis-yuen/SnapTools.git

Path: snaptools_create_snap_file.cwl

Branch/Commit ID: 9e4554d12dd0718009a551f3cb591452505f6dad
workflow graph Single-cell Multiome ATAC and RNA-Seq Alignment

Single-cell Multiome ATAC and RNA-Seq Alignment Runs Cell Ranger ARC Count to quantifies chromatin accessibility and gene expression from a single-cell Multiome ATAC and RNA-Seq library

 https://github.com/Barski-lab/sc-seq-analysis.git

Path: workflows/sc-multiome-align-wf.cwl

Branch/Commit ID: e70b7fab45e4bd2abfb7dab2b8b1f79ce904ac69
workflow graph Generate ATDP heatmap using Homer

Generate ATDP heatmap centered on TSS from an array of input BAM files and genelist TSV file. Returns array of heatmap JSON files with the names that have the same basenames as input BAM files, but with .json extension

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

Path: workflows/heatmap.cwl

Branch/Commit ID: d6ec0dee61ef65a110e10141bde1a79332a64ab0
workflow graph 811.cwl

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

Path: tests/wf/811.cwl

Branch/Commit ID: 1441c285e8a5afe399f5d52ca9059cb8bb513edb
workflow graph RNA-Seq pipeline single-read stranded mitochondrial

Slightly changed original [BioWardrobe's](https://biowardrobe.com) [PubMed ID:26248465](https://www.ncbi.nlm.nih.gov/pubmed/26248465) **RNA-Seq** basic analysis for **strand specific single-read** experiment. An additional steps were added to map data to mitochondrial chromosome only and then merge the output. Experiment files in [FASTQ](http://maq.sourceforge.net/fastq.shtml) format either compressed or not can be used. Current workflow should be used only with single-read strand specific RNA-Seq data. It performs the following steps: 1. `STAR` to align reads from input FASTQ file according to the predefined reference indices; generate unsorted BAM file and alignment statistics file 2. `fastx_quality_stats` to analyze input FASTQ file and generate quality statistics file 3. `samtools sort` to generate coordinate sorted BAM(+BAI) file pair from the unsorted BAM file obtained on the step 1 (after running STAR) 5. Generate BigWig file on the base of sorted BAM file 6. Map input FASTQ file to predefined rRNA reference indices using Bowtie to define the level of rRNA contamination; export resulted statistics to file 7. Calculate isoform expression level for the sorted BAM file and GTF/TAB annotation file using `GEEP` reads-counting utility; export results to file

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

Path: workflows/rnaseq-se-dutp-mitochondrial.cwl

Branch/Commit ID: c602e3cdd72ff904dd54d46ba2b5146eb1c57022