Explore Workflows

Workflow runs [Bowtie](http://bowtie-bio.sourceforge.net/tutorial.shtml) v1.2.0 (12/30/2016) to build indices for reference genome provided in a single FASTA file as fasta_file input. Generated indices are saved in a folder with the name that corresponds to the input genome

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

Path: workflows/bowtie-index.cwl

Branch/Commit ID: 581156366f91861bd4dbb5bcb59f67d468b32af3

ATAC-seq 03 mapping - reads: SE - blacklist removal

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

Path: v1.0/ATAC-seq_pipeline/03-map-se-blacklist-removal.cwl

Branch/Commit ID: 8aabde14169421a7115c5cd48c4740b3a7bd818f

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: 581156366f91861bd4dbb5bcb59f67d468b32af3

https://github.com/ncbi/pgap.git

Path: task_types/tt_hmmsearch_wnode_plus_qdump.cwl

Branch/Commit ID: a402541b8530f30eab726c160da90a23036847a1

Wrapped in a workflow SoupX tool for easy access to Cell Ranger pipeline compressed outputs.

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

Path: tools/soupx-subworkflow.cwl

Branch/Commit ID: 581156366f91861bd4dbb5bcb59f67d468b32af3

https://github.com/ncbi/pgap.git

Path: task_types/tt_cluster_and_qdump.cwl

Branch/Commit ID: a402541b8530f30eab726c160da90a23036847a1

Super-enhancers, consist of clusters of enhancers that are densely occupied by the master regulators and Mediator. Super-enhancers differ from typical enhancers in size, transcription factor density and content, ability to activate transcription, and sensitivity to perturbation. Use to create stitched enhancers, and to separate super-enhancers from typical enhancers using sequencing data (.bam) given a file of previously identified constituent enhancers (.gff)

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

Path: workflows/super-enhancer.cwl

Branch/Commit ID: 581156366f91861bd4dbb5bcb59f67d468b32af3

https://github.com/yyoshiaki/VIRTUS.git

Path: workflow/createindex_singlevirus.cwl

Branch/Commit ID: 16dbe9d99137cbfee834fc22b79190f812543f7e

AltAnalyze CellHarmony ======================

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

Path: workflows/altanalyze-cellharmony.cwl

Branch/Commit ID: 581156366f91861bd4dbb5bcb59f67d468b32af3

https://github.com/bcbio/bcbio_validation_workflows.git

Path: NA12878-chr20/NA12878-platinum-chr20-workflow/wf-variantcall.cwl

Branch/Commit ID: af9a5621efcb44c249697d6df071fe4defe389ac