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Graph Name Retrieved From View
workflow graph maf2vcf_gz_workflow.cwl

Workflow to convert a maf file into a vcf.gz with .tbi index

https://github.com/mskcc/pluto-cwl.git

Path: cwl/maf2vcf_gz_workflow.cwl

Branch/Commit ID: 2e1a01a788126f2901ffecc92a48fcbcb81776e1
workflow graph Trim Galore RNA-Seq pipeline single-read

The original [BioWardrobe's](https://biowardrobe.com) [PubMed ID:26248465](https://www.ncbi.nlm.nih.gov/pubmed/26248465) **RNA-Seq** basic analysis for a **single-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 file 2. Use STAR to align reads from input FASTQ file according to the predefined reference indices; generate unsorted BAM file and alignment statistics file 3. Use fastx_quality_stats to analyze input FASTQ file and generate quality statistics file 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 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/trim-rnaseq-se.cwl

Branch/Commit ID: 9bf0aa495735f8081bb5870cb32fc898b9e6eb22
workflow graph qiime2 explore sample taxonomic composition

Taxonomic analysis from https://docs.qiime2.org/2018.4/tutorials/moving-pictures/

 https://github.com/duke-gcb/bespin-cwl.git

Path: packed/qiime2-step2-dada2.cwl

Branch/Commit ID: e2dc95d4f12210359360d814382e7201d836dfcf

Packed ID: qiime2-08-taxonomic-analysis.cwl
workflow graph predict-workflow.cwl

https://github.com/Duke-GCB/iMADS-worker.git

Path: predict_service/predict-workflow.cwl

Branch/Commit ID: 573ffce8fc1dbad90129ff94d5f8caae68850fe1
workflow graph RNA-seq alelle specific pipeline for single-read data

Allele specific RNA-Seq single-read workflow

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

Path: workflows/allele-rnaseq-se.cwl

Branch/Commit ID: 9bf0aa495735f8081bb5870cb32fc898b9e6eb22
workflow graph cnv_codex

CNV CODEX calling

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

Path: structuralvariants/cwl/subworkflows/cnv_codex.cwl

Branch/Commit ID: a4a3547b9790e99a58424a0dfcb4e467a7691d6a
workflow graph bacterial_kmer

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

Path: bacterial_kmer/wf_bacterial_kmer.cwl

Branch/Commit ID: f5d70f3ad365a2c017fab1c9654c88bc1caf41aa
workflow graph Trim Galore 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 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. A [FASTQ](http://maq.sourceforge.net/fastq.shtml) input file has to be provided. In outputs it returns coordinate sorted BAM file alongside with index BAI file, quality statistics for both the input FASTQ files, 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 running fastx_quality_stats (steps fastx_quality_stats_upstream and fastx_quality_stats_downstream) from FASTX-Toolkit to calculate quality statistics for both upstream and downstream input FASTQ files. At the same time Bowtie is used to align reads from input FASTQ files to reference genome (Step bowtie_aligner). The output of this step is unsorted SAM file which is being sorted and indexed by samtools sort and samtools index (Step samtools_sort_index). Depending on workflow’s input parameters indexed and sorted BAM file could be processed by samtools rmdup (Step samtools_rmdup) to remove all possible read duplicates. In a case when removing duplicates is not necessary the step returns original input BAM and BAI files without any processing. If the duplicates were removed the following step (Step samtools_sort_index_after_rmdup) reruns samtools sort and samtools index with BAM and BAI files, if not - the step returns original unchanged input files. Right after that macs2 callpeak performs peak calling (Step macs2_callpeak). On the base of returned outputs the next step (Step macs2_island_count) calculates the number of islands and estimated fragment size. If the last one is less that 80 (hardcoded in a workflow) macs2 callpeak is rerun again with forced fixed fragment size value (Step 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 estimated fragment size (Step 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 (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 (Step 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-pe.cwl

Branch/Commit ID: 17a4a68b20e0af656e09714c1f39fe761b518686
workflow graph RNA-seq (VCF) alelle specific pipeline for single-read data

Allele specific RNA-Seq (using vcf) single-read workflow

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

Path: workflows/allele-vcf-rnaseq-se.cwl

Branch/Commit ID: 9bf0aa495735f8081bb5870cb32fc898b9e6eb22
workflow graph count-lines6-wf.cwl

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

Path: tests/count-lines6-wf.cwl

Branch/Commit ID: a0f2d38e37ff51721fdeaf993bb2ab474b17246b