Explore Workflows

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

Graph	Name	Retrieved From	View
	sequence (bam or fastqs) to trimmed fastqs and HISAT alignments	https://github.com/genome/analysis-workflows.git Path: definitions/subworkflows/sequence_to_trimmed_fastq_and_hisat_alignments.cwl Branch/Commit ID: 5be54bf09092c53e6c7797a875f64a360d511d7f
	cnv_gridss CNV GRIDSS calling	https://gitlab.bsc.es/lrodrig1/structuralvariants_poc.git Path: structuralvariants/subworkflows/cnv_gridss.cwl Branch/Commit ID: 548778e1733b1cac01ed2ec3d25a14bc484f3cbd
	waltz-workflow.cwl	https://github.com/mskcc/Innovation-Pipeline.git Path: workflows/waltz/waltz-workflow.cwl Branch/Commit ID: 9e6eae9eb8448e68d509397a46303551a93a164d
	qc_workflow_wo_waltz.cwl This workflow is intended to be used to test the QC module, without having to run the long waltz step	https://github.com/mskcc/ACCESS-Pipeline.git Path: workflows/QC/qc_workflow_wo_waltz.cwl Branch/Commit ID: 09ddd9711fb550f56d52f1806cdefd4a8cd943b0
	bam-filtering BAM filtering	https://gitlab.bsc.es/lrodrig1/structuralvariants_poc.git Path: structuralvariants/subworkflows/bam_filtering.cwl Branch/Commit ID: 548778e1733b1cac01ed2ec3d25a14bc484f3cbd
	cnv_exomedepth CNV ExomeDepth calling	https://gitlab.bsc.es/lrodrig1/structuralvariants_poc.git Path: structuralvariants/subworkflows/cnv_exome_depth.cwl Branch/Commit ID: 548778e1733b1cac01ed2ec3d25a14bc484f3cbd
	trimmed_fastq Quality Control and Raw Data trimming	https://gitlab.bsc.es/lrodrig1/structuralvariants_poc.git Path: structuralvariants/subworkflows/trimmed_fastq.cwl Branch/Commit ID: 548778e1733b1cac01ed2ec3d25a14bc484f3cbd
	cnv_codex CNV CODEX2 calling	https://gitlab.bsc.es/lrodrig1/structuralvariants_poc.git Path: structuralvariants/subworkflows/cnv_codex.cwl Branch/Commit ID: 548778e1733b1cac01ed2ec3d25a14bc484f3cbd
	qc_workflow.cwl	https://github.com/mskcc/ACCESS-Pipeline.git Path: workflows/QC/qc_workflow.cwl Branch/Commit ID: 0bd60a8962cc9960b7e4f6528547e220bcd2b941
	Trim Galore 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 with Trim Galore. _Trim Galore_ is a wrapper around [Cutadapt](https://github.com/marcelm/cutadapt) and [FastQC](http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) to consistently apply adapter and quality trimming to FastQ files, with extra functionality for RRBS data. In outputs it returns coordinate sorted BAM file alongside with index BAI file, quality statistics of the input FASTQ file, reads coverage in a form of 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 (on the base of BAM file). 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 unsorted SAM file which is being sorted and indexed by `samtools sort` and `samtools index` samtools\_sort\_index. Based 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 input BAM and BAI files return. Otherwise step samtools\_sort\_index\_after\_rmdup repeat `samtools sort` and `samtools index` with BAM and BAI files. Right after that `macs2 callpeak` performs peak calling macs2\_callpeak. On the base of returned outputs the next step macs2\_island\_count calculates the number of islands and estimated fragment size. If the last one is less that 80bp (hardcoded in the workflow) `macs2 callpeak` is rerun again with forced fixed fragment size value (macs2\_callpeak\_forced). If at the very beginning it was set in workflow input parameters to force run peak calling with fixed fragment size, this step is skipped and the original peak calling results are saved. In the next step workflow again calculates the number of islands and estimates fragment size (macs2\_island\_count\_forced) for the data obtained from macs2\_callpeak\_forced step. If the last one was skipped the results from macs2\_island\_count\_forced step are equal to the ones obtained from macs2\_island\_count step. 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 on the base of input BAM file and save it in BigWig format. For that purpose bamtools stats returns the number of mapped reads number which is then used as scaling factor by bedtools genomecov when it performs coverage calculation and saves it in BED format. The last one is then being 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 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 on the base of BAM file.	https://github.com/datirium/workflows.git Path: workflows/trim-chipseq-se.cwl Branch/Commit ID: 91bb63948c0a264334b9007ef85f936768d90d11