Explore Workflows

View already parsed workflows here or click here to add your own

Graph Name Retrieved From View
workflow graph schemadef-wf.cwl

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

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

Branch/Commit ID: 1e5ad10c6b0d1c5f531737d12ef64062a00baef2
workflow graph sec-wf.cwl

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

Path: tests/wf/sec-wf.cwl

Branch/Commit ID: 1b5633876aabd4cb57ef3f1fe91c853f3ee82e46
workflow graph Build Bismark indices

Copy fasta_file file to the folder and run run bismark_genome_preparation script to prepare indices for Bismark Methylation Analysis. Bowtie2 aligner is used by default. The name of the output indices folder is equal to the genome input.

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

Path: workflows/bismark-index.cwl

Branch/Commit ID: 7030da528559c7106d156284e50ff0ecedab0c4e
workflow graph Bismark Methylation PE

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-pe.cwl

Branch/Commit ID: 69643d8c15f5357a320aa7e2f6adb2e71302fd20
workflow graph Cell Ranger Aggregate (RNA+ATAC)

Cell Ranger Aggregate (RNA+ATAC) Combines outputs from multiple runs of “Cell Ranger Count (RNA+ATAC)” pipeline. The results of this workflow are primarily used in “Single-Cell Multiome ATAC and RNA-Seq Filtering Analysis” pipeline.

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

Path: workflows/cellranger-arc-aggr.cwl

Branch/Commit ID: 69643d8c15f5357a320aa7e2f6adb2e71302fd20
workflow graph format_rrnas_from_seq_entry

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

Path: task_types/tt_format_rrnas_from_seq_entry.cwl

Branch/Commit ID: 72804b6506c9f54ec75627f82aafe6a28d7a49fa
workflow graph kmer_cache_store

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

Path: task_types/tt_kmer_cache_store.cwl

Branch/Commit ID: cabb1a9a95244e93294727be8cf5816c38992cb0
workflow graph kmer_ref_compare_wnode

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

Path: task_types/tt_kmer_ref_compare_wnode.cwl

Branch/Commit ID: c28cfb9882dedd3c522160f933cff1050ae24100
workflow graph ROSE: rank ordering of super-enhancers

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: 69643d8c15f5357a320aa7e2f6adb2e71302fd20
workflow graph trim-chipseq-se.cwl

Runs ChIP-Seq BioWardrobe basic analysis with single-end data file.

https://github.com/Barski-lab/workflows.git

Path: workflows/trim-chipseq-se.cwl

Branch/Commit ID: de847468843203ce92b6d19323c5fe77dc488e34