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Graph	Name	Retrieved From	View
	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: 46a077b51619c6a14f85e0aa5260ae8a04426fab
	assm_assm_blastn_wnode	https://github.com/ncbi/pgap.git Path: task_types/tt_assm_assm_blastn_wnode.cwl Branch/Commit ID: 1b8d71c75156a1a62bf0477d59db26010e2dcc29
	revsort.cwl Reverse the lines in a document, then sort those lines.	https://github.com/common-workflow-language/cwltool.git Path: tests/wf/revsort.cwl Branch/Commit ID: 8d8512061f2367c90aac67bcbf92af1061b4af59
	EMG assembly for paired end Illumina	https://github.com/EBI-Metagenomics/ebi-metagenomics-cwl.git Path: workflows/emg-assembly.cwl Branch/Commit ID: cac44f2cf14110fde9951161c663c4525772f616
	Create tagAlign file This workflow creates tagAlign file	https://github.com/ncbi/cwl-ngs-workflows-cbb.git Path: workflows/File-formats/create-tagAlign.cwl Branch/Commit ID: 433720e6ba8c2d85b15de3ffb9ce1236f08978a4
	tt_hmmsearch_wnode.cwl	https://github.com/ncbi/pgap.git Path: task_types/tt_hmmsearch_wnode.cwl Branch/Commit ID: 686b570a9fa46f3ace3f8e9935490b75df86a1fc
	blastp_wnode_naming	https://github.com/ncbi/pgap.git Path: task_types/tt_blastp_wnode_naming.cwl Branch/Commit ID: add6b7724698694e0e72d972e2e85e1ae4e67902
	Xenbase RNA-Seq pipeline single-read 1. Convert input SRA file into pair of upsrtream and downstream FASTQ files (run fastq-dump) 2. Analyze quality of FASTQ files (run fastqc with each of the FASTQ files) 3. If any of the following fields in fastqc generated report is marked as failed for at least one of input FASTQ files: \"Per base sequence quality\", \"Per sequence quality scores\", \"Overrepresented sequences\", \"Adapter Content\", - trim adapters (run trimmomatic) 4. Align original or trimmed FASTQ files to reference genome, calculate genes and isoforms expression (run RSEM) 5. Count mapped reads number in sorted BAM file (run bamtools stats) 6. Generate genome coverage BED file (run bedtools genomecov) 7. Sort genearted BED file (run sort) 8. Generate genome coverage bigWig file from BED file (run bedGraphToBigWig)	https://github.com/datirium/workflows.git Path: workflows/xenbase-rnaseq-se.cwl Branch/Commit ID: 9bf0aa495735f8081bb5870cb32fc898b9e6eb22
	RNA-Seq pipeline single-read strand specific Note: should be updated The original [BioWardrobe's](https://biowardrobe.com) [PubMed ID:26248465](https://www.ncbi.nlm.nih.gov/pubmed/26248465) RNA-Seq basic analysis for strand specific single-read 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-read RNA-Seq data. It performs the following steps: 1. Use STAR to align reads from input FASTQ file according to the predefined reference indices; generate unsorted BAM file and alignment statistics file 2. Use fastx_quality_stats to analyze input FASTQ file and generate quality statistics file 3. 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/rnaseq-se-dutp.cwl Branch/Commit ID: 935a78f1aff757f977de4e3672aefead3b23606b
	EMG pipeline v3.0 (paired end version)	https://github.com/EBI-Metagenomics/ebi-metagenomics-cwl.git Path: workflows/emg-pipeline-v3-paired.cwl Branch/Commit ID: cac44f2cf14110fde9951161c663c4525772f616