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Graph	Name	Retrieved From	View
	DESeq2 Multi-factor Analysis DESeq2 Multi-factor Analysis Runs DeSeq2 multi-factor analysis with manual control over major parameters	https://github.com/datirium/workflows.git Path: workflows/deseq-multi-factor.cwl Branch/Commit ID: 7030da528559c7106d156284e50ff0ecedab0c4e
	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: 9ee330737f4603e4e959ffe786fbb2046db70a00
	search.cwl#main	https://github.com/common-workflow-language/common-workflow-language.git Path: v1.0/v1.0/search.cwl Branch/Commit ID: 9a23706ec061c5d2c02ff60238d218aadf0b5db9 Packed ID: main
	env-wf3.cwl	https://github.com/common-workflow-language/common-workflow-language.git Path: v1.0/v1.0/env-wf3.cwl Branch/Commit ID: 4fd45edb9531a03223c18a586e32d0baf0d5acb2
	workflow-blast-ebeye-pdbe.cwl	https://github.com/ebi-wp/webservice-cwl.git Path: workflows/workflow-blast-ebeye-pdbe.cwl Branch/Commit ID: 7c2c01c23d7a68a4f0c608881280576d65a01325
	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: d5f7fa162611243f0c66dd3e933c16a4964a09ca
	kmer_seq_entry_extract_wnode	https://github.com/ncbi/pgap.git Path: task_types/tt_kmer_seq_entry_extract_wnode.cwl Branch/Commit ID: a7fced3ed8c839272c8f3a8db9da7bc8cd50271f
	Bacterial Annotation, pass 1, genemark training, by HMMs (first pass)	https://github.com/ncbi/pgap.git Path: bacterial_annot/wf_ab_initio_training.cwl Branch/Commit ID: 8af4e2aabf43d5e3c7162efae4ad4649df5601e2
	mut.cwl	https://github.com/common-workflow-language/cwltool.git Path: tests/wf/mut.cwl Branch/Commit ID: 63f539ba60e91f0cb3ce7cda2c5da5c65525c375
	align_merge_sas	https://github.com/ncbi/pgap.git Path: task_types/tt_align_merge_sas.cwl Branch/Commit ID: e6fd7898b71a89b667d2eb38f412999920be5902