Explore Workflows

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: 2caa50434966ebdf4b33e5ca689c2e4df32f9058

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

Path: testdata/record-output-wf_v1_2.cwl

Branch/Commit ID: 124a08ce3389eb49066c34a4163cbbed210a0355

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

Path: testdata/step_valuefrom5_wf_with_id_v1_2.cwl

Branch/Commit ID: e78db9870cb744fe36674f43b3223c688e9989e1

https://github.com/common-workflow-language/cwl-v1.2.git

Path: tests/count-lines11-null-step-wf.cwl

Branch/Commit ID: e62f99dd79d6cb9c157cceb458f74200da84f6e9

What is THOR? -------------- THOR is an HMM-based approach to detect and analyze differential peaks in two sets of ChIP-seq data from distinct biological conditions with replicates. THOR performs genomic signal processing, peak calling and p-value calculation in an integrated framework. For more information please refer to: ------------------------------------- Allhoff, M., Sere K., Freitas, J., Zenke, M., Costa, I.G. (2016), Differential Peak Calling of ChIP-seq Signals with Replicates with THOR, Nucleic Acids Research, epub gkw680.

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

Path: workflows/rgt-thor.cwl

Branch/Commit ID: ce058d892d330125cd03d0a0d5fb3b321cda0be3

Workflow runs group-isoforms.cwl tool using scatter for isoforms_file input. genes_filename and common_tss_filename inputs are ignored.

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

Path: tools/group-isoforms-batch.cwl

Branch/Commit ID: 5b1d3af2b36d64c15095e62ed0ba7543369f216c

This is a workflow to go from UMI-tagged fastqs to standard bams. It does not include collapsing, or QC It does include modules 1 and 2

https://github.com/mskcc/ACCESS-Pipeline.git

Path: workflows/standard_pipeline.cwl

Branch/Commit ID: 5bf88423593441e4bf6b432111160446cd8dcf13

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

Path: cwltool/schemas/v1.0/v1.0/conflict-wf.cwl

Branch/Commit ID: 7c7615c44b80f8e76e659433f8c7875603ae0b25

Packed ID: collision

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

Path: cwltool/schemas/v1.0/v1.0/env-wf2.cwl

Branch/Commit ID: 8010fd2bf1e7090ba6df6ca8c84bbb96e2272d32

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

Path: testdata/record-output-wf_v1_1.cwl

Branch/Commit ID: 0ab1d42d10f7311bb4032956c4a6f3d2730d9507