Explore Workflows

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: 1f03ff02ef829bdb9d582825bcd4ca239e84ca2e

ATAC-seq pipeline - reads: PE

https://github.com/Duke-GCB/GGR-cwl.git

Path: v1.0/ATAC-seq_pipeline/pipeline-pe.cwl

Branch/Commit ID: 8d02684ae0ff27e641f3704686e3bc8b1979b854

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

Path: definitions/subworkflows/bgzip_and_index.cwl

Branch/Commit ID: 35e6b3ef71b4a2a9caba1dbd5dc424a8809bcc0a

https://github.com/kids-first/kf-alignment-workflow.git

Path: workflows/kfdrc_alignment_fqinput_CramOnly_wf.cwl

Branch/Commit ID: 2afe4de3fe046623715bde6f58b218ca063f5a0c

FeatureTable and FeatureData summaries from https://docs.qiime2.org/2018.4/tutorials/moving-pictures/

https://github.com/Duke-GCB/bespin-cwl.git

Path: packed/qiime2-step2-deblur.cwl

Branch/Commit ID: ef08cb00bd55b4c712645d171dbc691e01ed6165

Packed ID: qiime2-04-features.cwl

This workflow merge BAM files per condition in parallel

https://github.com/ncbi/cwl-ngs-workflows-cbb.git

Path: workflows/File-formats/merge-bam-parallel.cwl

Branch/Commit ID: ff1f968fabc8da5d33bb5f727412f723ddf66c2d

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

Path: definitions/subworkflows/bam_to_bqsr_no_dup_marking.cwl

Branch/Commit ID: 5c4125344b1b9125ad04d7e768ecc99901570a7a

https://github.com/proteinswebteam/ebi-metagenomics-cwl.git

Path: tools/SSU-from-tablehits.cwl

Branch/Commit ID: 5dc7c5ca618a248a99bd4bf5f3042cdb21947193

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

Path: definitions/subworkflows/docm_germline.cwl

Branch/Commit ID: 35e6b3ef71b4a2a9caba1dbd5dc424a8809bcc0a

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: e0a30aa1ad516dd2ec0e9ce006428964b840daf4