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Graph Name Retrieved From View
workflow graph 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: e99e80a2c19682d59947bde04a892d7b6d90091c

workflow graph mut2.cwl

https://github.com/common-workflow-language/cwltool.git

Path: tests/wf/mut2.cwl

Branch/Commit ID: 520acbfb82455c4bdabd5f2ea24842804e1c9f58

workflow graph mpi_simple_wf.cwl

Simple 2 step workflow to check that workflow steps are independently picking up on the number of processes. First run the parallel get PIDs step (on the input num procs) then run (on a single proc) the line count. This should equal the input.

https://github.com/common-workflow-language/cwltool.git

Path: tests/wf/mpi_simple_wf.cwl

Branch/Commit ID: eba80916b5cde8bdbd56c077c94240ddf796a27b

workflow graph TAP

https://github.com/MG-RAST/amplicon.git

Path: CWL/Workflows/tap.prok.workflow.cwl

Branch/Commit ID: 107cdd243d21449459a2126ddc7a365da64a74c0

workflow graph Trim Galore ATAC-Seq pipeline single-read

This ATAC pipeline is based on 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. ### Data Analysis Steps SciDAP starts from the .fastq files which most DNA cores and commercial NGS companies return. Starting from raw data allows us to ensure that all experiments have been processed in the same way and simplifies the deposition of data to GEO upon publication. The data can be uploaded from users computer, downloaded directly from an ftp server of the core facility by providing a URL or from GEO by providing SRA accession number. Our current pipelines include the following steps: 1. Trimming the adapters with TrimGalore. This step is particularly important when the reads are long and the fragments are short as in ATAC -resulting in sequencing adapters at the end of read. If adapter is not removed the read will not map. TrimGalore can recognize standard adapters, such as Nexterra/Tn5 adapters. 2. QC 3. (Optional) trimming adapters on 5' or 3' end by the specified number of bases. 4. Mapping reads with BowTie. Only uniquely mapped reads with less than 3 mismatches are used in the downstream analysis. Results are saved as a .bam file. 5. Reads mapping to chromosome M are removed. Since there are many copies of chromosome M in the cell and it is not protected by histones, some ATAC libraries have up to 50% of reads mapping to chrM. We recommend using OMNI-ATAC protocol that reduces chrM reads and provides better specificity. 6. (Optional) Removal of duplicates (reads/pairs of reads mapping to exactly same location). This step is used to remove reads overamplified in PCR. Unfortunately, it may also remove \"good\" reads. We usually do not remove duplicates unless the library is heavily duplicated. Please note that MACS2 will remove 'excessive' duplicates during peak calling ina smart way (those not supported by other nearby reads). 7. Peakcalling by MACS2. (Optionally), it is possible to specify read extension length for MACS2 to use if the length determined automatically is wrong. 8. Generation of BigWig coverage files for display on the browser. Since the cuts by the Tn5 transposome are 9bp apart, we show coverage by 9bp reads rather than fragments as in ChIP-Seq. The coverage shows the number of fragments at each base in the genome normalized to the number of millions of mapped reads. This way the peak of coverage will be located at the most accessible site. ### Details _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: 92f1a6da9c4f85fb51340b01b32373a50fde0891

workflow graph 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: 8bf36bfad5624fbc8fc315e82783a44e9e5e4470

workflow graph Build STAR indices

Workflow runs [STAR](https://github.com/alexdobin/STAR) v2.5.3a (03/17/2017) PMID: [23104886](https://www.ncbi.nlm.nih.gov/pubmed/23104886) to build indices for reference genome provided in a single FASTA file as fasta_file input and GTF annotation file from annotation_gtf_file input. Generated indices are saved in a folder with the name that corresponds to the input genome.

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

Path: workflows/star-index.cwl

Branch/Commit ID: 2cad55523d1b4ee7fd9e64df0f6263c6545e4b0e

workflow graph Varscan Workflow

https://github.com/genome/analysis-workflows.git

Path: definitions/subworkflows/varscan_germline.cwl

Branch/Commit ID: dc2c019c1aa24cc01b451a0f048cf94a35f163c4

workflow graph exomeseq-03-organizedirectories.cwl

https://github.com/Duke-GCB/bespin-cwl.git

Path: subworkflows/exomeseq-03-organizedirectories.cwl

Branch/Commit ID: 92b8d41bab2661919aa11aa84e1923748f8503c4

workflow graph scatter-valuefrom-inputs-wf1.cwl

https://github.com/common-workflow-language/cwl-v1.1.git

Path: tests/scatter-valuefrom-inputs-wf1.cwl

Branch/Commit ID: 368b562a1449e8cd39ae8b7f05926b2bfb9b22df