Explore Workflows
View already parsed workflows here or click here to add your own
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                                        blastp_wnode_naming
                                         
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                                             Path: task_types/tt_blastp_wnode_naming.cwl Branch/Commit ID: c18a7e5164cb6b19f06b3d1e869407c118a87f7e  | 
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                                        Generate genome indices for STAR & bowtie
                                         Creates indices for: * [STAR](https://github.com/alexdobin/STAR) v2.5.3a (03/17/2017) PMID: [23104886](https://www.ncbi.nlm.nih.gov/pubmed/23104886) * [bowtie](http://bowtie-bio.sourceforge.net/tutorial.shtml) v1.2.0 (12/30/2016) It performs the following steps: 1. `STAR --runMode genomeGenerate` to generate indices, based on [FASTA](http://zhanglab.ccmb.med.umich.edu/FASTA/) and [GTF](http://mblab.wustl.edu/GTF2.html) input files, returns results as an array of files 2. Outputs indices as [Direcotry](http://www.commonwl.org/v1.0/CommandLineTool.html#Directory) data type 3. Separates *chrNameLength.txt* file from Directory output 4. `bowtie-build` to generate indices requires genome [FASTA](http://zhanglab.ccmb.med.umich.edu/FASTA/) file as input, returns results as a group of main and secondary files  | 
                                    
                                        
                                             Path: workflows/genome-indices.cwl Branch/Commit ID: 8049a781ac4aae579fbd3036fa0bf654532f15be  | 
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                                        Pairwise genomic regions intersection
                                         Pairwise genomic regions intersection ============================================= Overlaps peaks from two ChIP/ATAC experiments  | 
                                    
                                        
                                             Path: workflows/peak-intersect.cwl Branch/Commit ID: e45ab1b9ac5c9b99fdf7b3b1be396dc42c2c9620  | 
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                                        SAMSA2 pipeline
                                         SAMSA2 complete workflow for meta-omics read annotation Steps: - Diamond read blastx - Refseq - SEED - SAMSA2 processing  | 
                                    
                                        
                                            
                                             Path: cwl/workflows/workflow_samsa2.cwl Branch/Commit ID: cd0c19d51068c5407cd70b718a561d4662819d87  | 
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                                        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  | 
                                    
                                        
                                             Path: workflows/trim-rnaseq-pe-smarter-dutp.cwl Branch/Commit ID: e45ab1b9ac5c9b99fdf7b3b1be396dc42c2c9620  | 
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                                        protein annotation
                                         Proteins - predict, filter, cluster, identify, annotate  | 
                                    
                                        
                                             Path: CWL/Workflows/protein-filter-annotation.workflow.cwl Branch/Commit ID: 091374dc59a23966338638a668ae397d4ee20b2f  | 
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                                        hello_world_checker.cwl
                                         
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                                             Path: hello_world_checker.cwl Branch/Commit ID: 3f52d3e0e82c2df70ecada74cab879c490b9c2ee  | 
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                                        Cut-n-Run pipeline paired-end
                                         Experimental pipeline for Cut-n-Run analysis. Uses mapping results from the following experiment types: - `chipseq-pe.cwl` - `trim-chipseq-pe.cwl` - `trim-atacseq-pe.cwl` Note, the upstream analyses should not have duplicates removed  | 
                                    
                                        
                                             Path: workflows/trim-chipseq-pe-cut-n-run.cwl Branch/Commit ID: 564156a9e1cc7c3679a926c479ba3ae133b1bfd4  | 
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                                        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. A [FASTQ](http://maq.sourceforge.net/fastq.shtml) input file has to be provided. The pipeline produces a sorted BAM file alongside with index BAI file, quality statistics of the input FASTQ file, coverage by estimated fragments as a 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. 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 an unsorted SAM file which is being sorted and indexed by `samtools sort` and `samtools index` *samtools\_sort\_index*. Depending 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 BAM and BAI files are returned. Otherwise step *samtools\_sort\_index\_after\_rmdup* repeat `samtools sort` and `samtools index` with BAM and BAI files without duplicates. Next `macs2 callpeak` performs peak calling *macs2\_callpeak* and the next step reports *macs2\_island\_count* the number of islands and estimated fragment size. If the latter is less that 80bp (hardcoded in the workflow) `macs2 callpeak` is rerun again with forced fixed fragment size value (*macs2\_callpeak\_forced*). It is also possible to force MACS2 to use pre set fragment size in the first place. 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 from BAM file and save it in BigWig format. For that purpose bamtools stats returns the number of mapped reads which is then used as scaling factor by bedtools genomecov when it performs coverage calculation and saves it as a BEDgraph file whichis then 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 nearest 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 from the BAM file.  | 
                                    
                                        
                                             Path: workflows/chipseq-pe.cwl Branch/Commit ID: 8049a781ac4aae579fbd3036fa0bf654532f15be  | 
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                                        Filter differentially expressed genes from DESeq for Tag Density Profile Analyses
                                         Filters differentially expressed genes from DESeq for Tag Density Profile Analyses ================================================================================== Tool filters output from DESeq pipeline run for genes to create a file with regions of interest for Tag Density Profile Analyses.  | 
                                    
                                        
                                             Path: workflows/filter-deseq-for-heatmap.cwl Branch/Commit ID: e45ab1b9ac5c9b99fdf7b3b1be396dc42c2c9620  | 
                                    
