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Graph Name Retrieved From View
workflow graph wf_demultiplex_se.cwl

This workflow takes in single-end reads, and performs the following steps in order: demux_se.cwl (does not actually demux for single end, but mirrors the paired-end processing protocol)

https://github.com/YeoLab/eclip.git

Path: cwl/wf_demultiplex_se.cwl

Branch/Commit ID: c0fffc4979a92371dc0667a03e3d957bf7f77600
workflow graph alignment_workflow.cwl

https://github.com/databiosphere/topmed-workflows.git

Path: aligner/topmed-cwl/workflow/alignment_workflow.cwl

Branch/Commit ID: 6478d5df50d7340311d18f03a056e3db97811269
workflow graph Functional analyis of sequences that match the 16S SSU

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

Path: workflows/16S_taxonomic_analysis.cwl

Branch/Commit ID: 9c57dba558a4e04a1884eae1df8431dcaccafc1e
workflow graph Trim Galore ATAC-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. The pipeline was adapted for ATAC-Seq single-read data analysis by updating genome coverage step. _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. To adapt the pipeline for ATAC-Seq data analysis we calculate genome coverage using only the first 9 bp from every read. 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-atacseq-se.cwl

Branch/Commit ID: 7518b100d8cbc80c8be32e9e939dfbb27d6b4361
workflow graph Functional analyis of sequences that match the 16S SSU

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

Path: workflows/16S_taxonomic_analysis.cwl

Branch/Commit ID: 0cf06f13527b380d21d0f335aaea3e564094ed8f
workflow graph kallisto-demo.cwl

https://github.com/common-workflow-library/legacy.git

Path: workflows/kallisto-demo.cwl

Branch/Commit ID: 767d700e602805112a4c953d166e570cddfa2605
workflow graph wf_trim_and_map_se.cwl

This workflow takes in appropriate trimming params and demultiplexed reads, and performs the following steps in order: trimx1, trimx2, fastq-sort, filter repeat elements, fastq-sort, genomic mapping, sort alignment, index alignment, namesort, PCR dedup, sort alignment, index alignment

https://github.com/YeoLab/eclip.git

Path: cwl/wf_trim_and_map_se.cwl

Branch/Commit ID: c0fffc4979a92371dc0667a03e3d957bf7f77600
workflow graph Creates FASTA file from BED coordinates

This workflow creates FASTA file from BED coordinates

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

Path: workflows/File-formats/fasta-from-bed.cwl

Branch/Commit ID: 793e327acc1d159ff601043ee88651fca62350dd
workflow graph fail-unconnected.cwl

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

Path: tests/fail-unconnected.cwl

Branch/Commit ID: a0f2d38e37ff51721fdeaf993bb2ab474b17246b
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: 7518b100d8cbc80c8be32e9e939dfbb27d6b4361