Explore Workflows

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

Graph Name Retrieved From View
workflow graph Alignment without BQSR

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

Path: definitions/subworkflows/sequence_to_bqsr_mouse.cwl

Branch/Commit ID: d3e4bf55753cd92f97537c7d701187ea92d1e5f0
workflow graph waltz-workflow.cwl

https://github.com/mskcc/ACCESS-Pipeline.git

Path: workflows/waltz/waltz-workflow.cwl

Branch/Commit ID: 476f3dcda929ee9eb67391bbc819573d75751b7c
workflow graph Trim Galore 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 **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.cwl

Branch/Commit ID: c9e7f3de7f6ba38ee663bd3f9649e8d7dbac0c86
workflow graph Pairwise genomic regions intersection

Pairwise genomic regions intersection ============================================= Overlaps peaks from two ChIP/ATAC experiments

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

Path: workflows/peak-intersect.cwl

Branch/Commit ID: 1131f82a53315cca217a6c84b3bd272aa62e4bca
workflow graph Varscan Workflow

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

Path: definitions/subworkflows/varscan_germline.cwl

Branch/Commit ID: 441b85003fdc10cf4cbf333d89acb4d23b0fef32
workflow graph Cut-n-Run pipeline paired-end

Experimental pipeline for Cut-n-Run analysis. Uses mapping results from the following experiment types: - `chipseq-pe.cwl` - `trim-chipseq-pe.cwl` - `trim-atacseq-pe.cwl` Note, the upstream analyses should not have duplicates removed

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

Path: workflows/trim-chipseq-pe-cut-n-run.cwl

Branch/Commit ID: 09267e79fd867aa68a219c69e6db7d8e2e877be2
workflow graph Trim Galore 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 **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.cwl

Branch/Commit ID: 12c29f88855329192bfff977f046990031f04931
workflow graph FastQC - a quality control tool for high throughput sequence data

FastQC - a quality control tool for high throughput sequence data ===================================== FastQC aims to provide a simple way to do some quality control checks on raw sequence data coming from high throughput sequencing pipelines. It provides a modular set of analyses which you can use to give a quick impression of whether your data has any problems of which you should be aware before doing any further analysis. The main functions of FastQC are: - Import of data from FastQ files (any variant) - Providing a quick overview to tell you in which areas there may be problems - Summary graphs and tables to quickly assess your data - Export of results to an HTML based permanent report - Offline operation to allow automated generation of reports without running the interactive application

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

Path: workflows/fastqc.cwl

Branch/Commit ID: 1131f82a53315cca217a6c84b3bd272aa62e4bca
workflow graph gp_makeblastdb

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

Path: progs/gp_makeblastdb.cwl

Branch/Commit ID: 7f857f7f2d7c080d27c775b67a6d6f7d94bce31f
workflow graph count-lines1-wf.cwl

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

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

Branch/Commit ID: fec7a10466a26e376b14181a88734983cfb1b8cb