Explore Workflows

https://github.com/hubmapconsortium/sc-atac-seq-pipeline.git

Path: steps/bulk_analysis.cwl

Branch/Commit ID: 44dbe381f68878ab607b167b62267c4ea97f3322

Resize sentinel2ard collection

https://github.com/EO-DataHub/eodh-training.git

Path: cwl/resize-sentinel2ard.cwl

Branch/Commit ID: 9047f151da2db909a091ca9fd27e62b6bfe54ea0

Packed ID: resize-sentinel2ard

https://github.com/genome/analysis-workflows.git

Path: definitions/subworkflows/sequence_to_bqsr_mouse.cwl

Branch/Commit ID: a59a803e1809a8fbfabca6b8962a8ad66dd01f1d

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

Path: testdata/step-valuefrom3-wf_v1_0.cwl

Branch/Commit ID: e949503ac0dd7e22ba9b04ac51926d13780f9cee

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

Path: testdata/step_valuefrom5_wf_with_id_v1_0.cwl

Branch/Commit ID: e949503ac0dd7e22ba9b04ac51926d13780f9cee

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

Path: testdata/workflow_input_format_expr_v1_2.cwl

Branch/Commit ID: e949503ac0dd7e22ba9b04ac51926d13780f9cee

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

Path: testdata/count-lines7-single-source-wf_v1_1.cwl

Branch/Commit ID: e949503ac0dd7e22ba9b04ac51926d13780f9cee

Simulation of 2 workflows

https://github.com/ILIAD-ocean-twin/application_package.git

Path: workflow_in_workflow/workflow_same_level.cwl

Branch/Commit ID: aab1b560c6a855c645f43635f155a15800a7ce0d

Packed ID: second_pipeline

https://github.com/hubmapconsortium/multiome-rna-atac-pipeline.git

Path: sc-atac-seq-pipeline/sc_atac_seq_prep_process_analyze.cwl

Branch/Commit ID: 68e0cc1be35751f5ef5958050742ddfffd564d3c

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: 3a311af320e65271f3efb4f27a6ed10aa5d50a0e