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Graph	Name	Retrieved From	View
	Seed Protein Alignments I	https://github.com/ncbi/pgap.git Path: protein_alignment/wf_seed_1.cwl Branch/Commit ID: e81df43c40bc6849ece095a05cb0247dc53b94b1
	exome alignment and somatic variant detection for cle purpose	https://github.com/genome/analysis-workflows.git Path: definitions/pipelines/somatic_exome_cle.cwl Branch/Commit ID: cc3e7f1ccfdc7101c22bf88792608504eea7d53a
	Interval overlapping alignments counts Interval overlapping alignments counts ====================================== Reports the count of alignments from multiple samples that overlap specific intervals.	https://github.com/datirium/workflows.git Path: workflows/bedtools-multicov.cwl Branch/Commit ID: 12e5256de1b680c551c87fd5db6f3bc65428af67
	phase VCF	https://github.com/genome/analysis-workflows.git Path: definitions/subworkflows/phase_vcf.cwl Branch/Commit ID: ae57b60e9b01e3f0f02f4e828042748409dff5a3
	QuantSeq 3' FWD, FWD-UMI or REV for single-read mRNA-Seq data ### Devel version of QuantSeq 3' FWD, FWD-UMI or REV for single-read mRNA-Seq data	https://github.com/datirium/workflows.git Path: workflows/trim-quantseq-mrnaseq-se-strand-specific.cwl Branch/Commit ID: bf80c9339d81a78aefb8de661bff998ed86e836e
	Trim Galore SMARTer RNA-Seq pipeline paired-end strand specific https://chipster.csc.fi/manual/library-type-summary.html 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-smarter-dutp.cwl Branch/Commit ID: cbefc215d8286447620664fb47076ba5d81aa47f
	FASTQ Vector Removal 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: ebf1dd3c243c08634b0b3d9766c0a354903920ee
	Bismark Methylation PE Sequence reads are first cleaned from adapters and transformed into fully bisulfite-converted forward (C->T) and reverse read (G->A conversion of the forward strand) versions, before they are aligned to similarly converted versions of the genome (also C->T and G->A converted). Sequence reads that produce a unique best alignment from the four alignment processes against the bisulfite genomes (which are running in parallel) are then compared to the normal genomic sequence and the methylation state of all cytosine positions in the read is inferred. A read is considered to align uniquely if an alignment has a unique best alignment score (as reported by the AS:i field). If a read produces several alignments with the same number of mismatches or with the same alignment score (AS:i field), a read (or a read-pair) is discarded altogether. On the next step we extract the methylation call for every single C analysed. The position of every single C will be written out to a new output file, depending on its context (CpG, CHG or CHH), whereby methylated Cs will be labelled as forward reads (+), non-methylated Cs as reverse reads (-). The output of the methylation extractor is then transformed into a bedGraph and coverage file. The bedGraph counts output is then used to generate a genome-wide cytosine report which reports the number on every single CpG (optionally every single cytosine) in the genome, irrespective of whether it was covered by any reads or not. As this type of report is informative for cytosines on both strands the output may be fairly large (~46mn CpG positions or >1.2bn total cytosine positions in the human genome).	https://github.com/datirium/workflows.git Path: workflows/bismark-methylation-pe.cwl Branch/Commit ID: 36fd18f11e939d3908b1eca8d2939402f7a99b0f
	bismark-methylation-se.cwl Bismark Methylation pipeline. We can use indices_folder as genome_folder for bismark_extract_methylation step, because it insludes the original FASTA files too.	https://github.com/Barski-lab/workflows.git Path: workflows/bismark-methylation-se.cwl Branch/Commit ID: 568da91bb1c6182ba4f146e2a729cac1c3d8783c
	Seed Search Compartments	https://github.com/ncbi/pgap.git Path: protein_alignment/wf_seed.cwl Branch/Commit ID: cb15f907132fb90bc66b39bb0af3c211801feba1