Explore Workflows

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

Graph Name Retrieved From View
workflow graph cond-wf-009.cwl

https://github.com/common-workflow-language/cwl-v1.2.git

Path: tests/conditionals/cond-wf-009.cwl

Branch/Commit ID: 7d7986a6e852ca6e3239c96d3a05dd536c76c903
workflow graph Cell Ranger Reference (RNA, ATAC, RNA+ATAC)

Cell Ranger Reference (RNA, ATAC, RNA+ATAC) Builds a reference genome of a selected species for quantifying gene expression and chromatin accessibility. The results of this workflow are used in all “Cell Ranger Count” and “Cell Ranger Aggregate” pipelines.

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

Path: workflows/cellranger-mkref.cwl

Branch/Commit ID: d76110e0bfc40c874f82e37cef6451d74df4f908
workflow graph cond-wf-006.cwl

https://github.com/common-workflow-language/cwl-v1.2.git

Path: tests/conditionals/cond-wf-006.cwl

Branch/Commit ID: 7d7986a6e852ca6e3239c96d3a05dd536c76c903
workflow graph sum-wf.cwl

https://github.com/common-workflow-language/cwl-v1.1.git

Path: tests/sum-wf.cwl

Branch/Commit ID: 3e90671b25f7840ef2926ad2bacbf447772dda94
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: 8a92669a566589d80fde9d151054ffc220ed4ddd
workflow graph Trim Galore RNA-Seq pipeline paired-end strand specific

Modified original [BioWardrobe's](https://biowardrobe.com) [PubMed ID:26248465](https://www.ncbi.nlm.nih.gov/pubmed/26248465) **RNA-Seq** basic analysis for a **pair-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 single-end RNA-Seq data. It performs the following steps: 1. Trim adapters from input FASTQ files 2. Use STAR to align reads from input FASTQ files according to the predefined reference indices; generate unsorted BAM file and alignment statistics file 3. Use fastx_quality_stats to analyze input FASTQ files and generate quality statistics files 4. 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 files 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/trim-rnaseq-pe-dutp.cwl

Branch/Commit ID: 8a92669a566589d80fde9d151054ffc220ed4ddd
workflow graph count-lines1-wf-noET.cwl

https://github.com/common-workflow-language/cwl-v1.1.git

Path: tests/count-lines1-wf-noET.cwl

Branch/Commit ID: 3e90671b25f7840ef2926ad2bacbf447772dda94
workflow graph helloworld.cwl

https://github.com/reanahub/reana-demo-helloworld.git

Path: workflow/cwl/helloworld.cwl

Branch/Commit ID: 7347d7ed441a442ce25927228b5bc7ac5b8e9a00
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: a8eaf61c809d76f55780b14f2febeb363cf6373f
workflow graph kmer_top_n_extract

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

Path: task_types/tt_kmer_top_n_extract.cwl

Branch/Commit ID: 2c7879b47890b9300ab9b5ebd35e17372e077757