Explore Workflows

View already parsed workflows here or click here to add your own

Graph	Name	Retrieved From	View
	bgzip and index VCF	https://github.com/genome/analysis-workflows.git Path: definitions/subworkflows/bgzip_and_index.cwl Branch/Commit ID: 35e6b3ef71b4a2a9caba1dbd5dc424a8809bcc0a
	kfdrc_alignment_fqinput_CramOnly_wf.cwl	https://github.com/kids-first/kf-alignment-workflow.git Path: workflows/kfdrc_alignment_fqinput_CramOnly_wf.cwl Branch/Commit ID: 2afe4de3fe046623715bde6f58b218ca063f5a0c
	qiime2 create feature visual summaries FeatureTable and FeatureData summaries from https://docs.qiime2.org/2018.4/tutorials/moving-pictures/	https://github.com/Duke-GCB/bespin-cwl.git Path: packed/qiime2-step2-deblur.cwl Branch/Commit ID: ef08cb00bd55b4c712645d171dbc691e01ed6165 Packed ID: qiime2-04-features.cwl
	merge-bam-parallel This workflow merge BAM files per condition in parallel	https://github.com/ncbi/cwl-ngs-workflows-cbb.git Path: workflows/File-formats/merge-bam-parallel.cwl Branch/Commit ID: ff1f968fabc8da5d33bb5f727412f723ddf66c2d
	Unaligned BAM to BQSR and VCF	https://github.com/genome/analysis-workflows.git Path: definitions/subworkflows/bam_to_bqsr_no_dup_marking.cwl Branch/Commit ID: 5c4125344b1b9125ad04d7e768ecc99901570a7a
	SSU-from-tablehits.cwl	https://github.com/proteinswebteam/ebi-metagenomics-cwl.git Path: tools/SSU-from-tablehits.cwl Branch/Commit ID: 5dc7c5ca618a248a99bd4bf5f3042cdb21947193
	Detect DoCM variants	https://github.com/genome/analysis-workflows.git Path: definitions/subworkflows/docm_germline.cwl Branch/Commit ID: 35e6b3ef71b4a2a9caba1dbd5dc424a8809bcc0a
	Bismark Methylation - pipeline for BS-Seq data analysis 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-se.cwl Branch/Commit ID: e0a30aa1ad516dd2ec0e9ce006428964b840daf4
	js-expr-req-wf.cwl#wf	https://github.com/common-workflow-language/common-workflow-language.git Path: v1.0/v1.0/js-expr-req-wf.cwl Branch/Commit ID: d9ec78aa015755d07a1c60a9d11f1f5f0a012e1f Packed ID: wf
	FastQC - a quality control tool for high throughput sequence data FastQC - a quality control tool for high throughput sequence data ===================================== FastQC aims to provide a simple way to do some quality control checks on raw sequence data coming from high throughput sequencing pipelines. It provides a modular set of analyses which you can use to give a quick impression of whether your data has any problems of which you should be aware before doing any further analysis. The main functions of FastQC are: - Import of data from FastQ files (any variant) - Providing a quick overview to tell you in which areas there may be problems - Summary graphs and tables to quickly assess your data - Export of results to an HTML based permanent report - Offline operation to allow automated generation of reports without running the interactive application	https://github.com/datirium/workflows.git Path: workflows/fastqc.cwl Branch/Commit ID: e0a30aa1ad516dd2ec0e9ce006428964b840daf4