Explore Workflows

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

Graph	Name	Retrieved From	View
	step-valuefrom-wf.cwl	https://github.com/common-workflow-language/cwltool.git Path: cwltool/schemas/v1.0/v1.0/step-valuefrom-wf.cwl Branch/Commit ID: 7bfd77118cdc80dd7150115dd7a1a7ee6046f6fe
	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: 8a92669a566589d80fde9d151054ffc220ed4ddd
	bacterial_orthology_cond	https://github.com/ncbi/pgap.git Path: bacterial_orthology/wf_bacterial_orthology_conditional.cwl Branch/Commit ID: 7cee09fb3e33c851e4e1dfc965c558b82290a785
	Build Bowtie indices Workflow runs [Bowtie](http://bowtie-bio.sourceforge.net/tutorial.shtml) v1.2.0 (12/30/2016) to build indices for reference genome provided in a single FASTA file as fasta_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/bowtie-index.cwl Branch/Commit ID: c9e7f3de7f6ba38ee663bd3f9649e8d7dbac0c86
	qc_workflow_wo_waltz.cwl This workflow is intended to be used to test the QC module, without having to run the long waltz step	https://github.com/mskcc/ACCESS-Pipeline.git Path: workflows/QC/qc_workflow_wo_waltz.cwl Branch/Commit ID: 9e6eae9eb8448e68d509397a46303551a93a164d
	Genomic regions intersection and visualization Genomic regions intersection and visualization ============================================== 1. Merges intervals within each of the filtered peaks files from ChIP/ATAC experiments 2. Overlaps merged intervals and assigns the nearest genes to them	https://github.com/datirium/workflows.git Path: workflows/intervene.cwl Branch/Commit ID: b1a5dabeeeb9079b30b2871edd9c9034a1e00c1c
	count-lines10-wf.cwl	https://github.com/common-workflow-language/cwltool.git Path: cwltool/schemas/v1.0/v1.0/count-lines10-wf.cwl Branch/Commit ID: 26870e38cec81af880cd3e4789ae6cee8fc27020
	Apply filters to VCF file	https://github.com/genome/analysis-workflows.git Path: definitions/subworkflows/germline_filter_vcf.cwl Branch/Commit ID: ef7f3345b352319ec22dffba26c79df033b141f9
	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: c9e7f3de7f6ba38ee663bd3f9649e8d7dbac0c86
	bam_filtering BAM filtering	https://gitlab.bsc.es/lrodrig1/structuralvariants_poc.git Path: structuralvariants/subworkflows/bam_filtering.cwl Branch/Commit ID: c494fa4f60d9215842c4d2c75ed7d89757435b0f