Explore Workflows

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

Graph	Name	Retrieved From	View
	pipeline.cwl	https://github.com/hubmapconsortium/ome-tiff-pyramid.git Path: pipeline.cwl Branch/Commit ID: a063a3404a5f4345292508cb82313bd41ea6c615
	myAIWorkflow3.cwl This CWL workflow outlines the steps for setting up and executing an experiment based on objectives, SOP references, parameters, and experimental design. Version: 1.0 Description: Workflow for executing and tracking experiments. Includes validation and logging steps.	https://github.com/pascmont/cwltest.git Path: myAIWorkflow3.cwl Branch/Commit ID: e56456381c2588e3933d91b47c47b7e61023683b
	Running cellranger count and lineage inference	https://github.com/genome/analysis-workflows.git Path: definitions/subworkflows/single_cell_rnaseq.cwl Branch/Commit ID: 24e5290aec441665c6976ee3ee8ae3574c49c6b5
	SPRM pipeline	https://github.com/hubmapconsortium/sprm.git Path: pipeline.cwl Branch/Commit ID: dd8c266a1e4bc953e29671219e7bb004072f7838
	count-lines16-wf.cwl	https://github.com/common-workflow-language/cwl-v1.2.git Path: tests/count-lines16-wf.cwl Branch/Commit ID: 707ebcd2173889604459c5f4ffb55173c508abb3
	allele-vcf-rnaseq-se.cwl Allele specific RNA-Seq (using vcf) single-read workflow	https://github.com/datirium/workflows.git Path: workflows/allele-vcf-rnaseq-se.cwl Branch/Commit ID: a9551ece898f619167db58e4b74a6cae2d7f7d13
	steplevel-resreq.cwl	https://github.com/common-workflow-language/cwl-v1.2.git Path: tests/steplevel-resreq.cwl Branch/Commit ID: a5073143db4155e05df8d2e7eb59d9e62acd65a5
	count-lines11-wf.cwl	https://github.com/common-workflow-language/cwltool.git Path: cwltool/schemas/v1.0/v1.0/count-lines11-wf.cwl Branch/Commit ID: fd6e054510e2bb65eed4069a3a88013d7ecbb99c
	xenbase-rnaseq-se.cwl XenBase workflow for analysing RNA-Seq single-end data	https://github.com/datirium/workflows.git Path: workflows/xenbase-rnaseq-se.cwl Branch/Commit ID: a9551ece898f619167db58e4b74a6cae2d7f7d13
	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: 564156a9e1cc7c3679a926c479ba3ae133b1bfd4