Explore Workflows

https://github.com/proteinswebteam/ebi-metagenomics-cwl.git

Path: workflows/emg-pipeline-v3-paired.cwl

Branch/Commit ID: 5dc7c5ca618a248a99bd4bf5f3042cdb21947193

https://github.com/NCI-GDC/gdc-dnaseq-cwl.git

Path: workflows/dnaseq/transform.cwl

Branch/Commit ID: dd7f86b3cc10eb1cda07dc2fc279ba2529c8ad61

https://github.com/CERIT-SC/fireprot.git

Path: cmanalysis.cwl

Branch/Commit ID: a2b0c18f117dcf2b0d7e33c59c0f180b6a9bf709

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: 2c486543c335bb99b245dfe7e2f033f535efb9cf

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: 9bf0aa495735f8081bb5870cb32fc898b9e6eb22

This workflow clean up vectros from fastq files

https://github.com/ncbi/cwl-ngs-workflows-cbb.git

Path: workflows/File-formats/remove-fastq-reads-from-blast.cwl

Branch/Commit ID: 6eb7fec3bd018addf02bb3285cb56d9453319d5d

https://github.com/svonworl/Broad-Best-Practice-Data-pre-processing-CWL1.0-workflow.git

Path: broad-best-practice-data-pre-processing-workflow-4-1-0-0_decomposed.cwl

Branch/Commit ID: fe43d13c174816704f1d7941dc8cb5fce358c0de

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: 8a92669a566589d80fde9d151054ffc220ed4ddd

Workflow runs homer-make-tag-directory.cwl tool using scatter for the following inputs - bam_file - fragment_size - total_reads `dotproduct` is used as a `scatterMethod`, so one element will be taken from each array to construct each job: 1) bam_file[0] fragment_size[0] total_reads[0] 2) bam_file[1] fragment_size[1] total_reads[1] ... N) bam_file[N] fragment_size[N] total_reads[N] `bam_file`, `fragment_size` and `total_reads` arrays should have the identical order.

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

Path: subworkflows/heatmap-prepare.cwl

Branch/Commit ID: 02ffbbd7eb8e06bfb759edea440f78bdc8bb2631

https://gitlab.bsc.es/lrodrig1/structuralvariants_poc.git

Path: structuralvariants/cwl/subworkflows/indexing_bed.cwl

Branch/Commit ID: a4a3547b9790e99a58424a0dfcb4e467a7691d6a