Explore Workflows
View already parsed workflows here or click here to add your own
| Graph | Name | Retrieved From | View |
|---|---|---|---|
|
|
Run tRNAScan
|
https://github.com/ncbi/pgap.git
Path: bacterial_trna/wf_trnascan.cwl Branch/Commit ID: b38b0070edf910984f29a4a495b5dfa525b8b305 |
|
|
|
Workflow to run pVACseq from detect_variants and rnaseq pipeline outputs
|
https://github.com/genome/analysis-workflows.git
Path: definitions/subworkflows/pvacseq.cwl Branch/Commit ID: 8438316338e66823e1c9aca9f675b2bf33f2aa59 |
|
|
|
Run genomic CMsearch
|
https://github.com/ncbi/pgap.git
Path: bacterial_noncoding/wf_gcmsearch.cwl Branch/Commit ID: b38b0070edf910984f29a4a495b5dfa525b8b305 |
|
|
|
Bacterial Annotation, pass 1, genemark training, by HMMs (first pass)
|
https://github.com/ncbi/pgap.git
Path: bacterial_annot/wf_bacterial_annot_pass1.cwl Branch/Commit ID: b38b0070edf910984f29a4a495b5dfa525b8b305 |
|
|
|
rnaseq-header.cwl
|
https://github.com/datirium/workflows.git
Path: metadata/rnaseq-header.cwl Branch/Commit ID: 10ce6e113f749c7bd725e426445220c3bdc5ddf1 |
|
|
|
sequence (bam or fastqs) to trimmed fastqs and HISAT alignments
|
https://github.com/genome/analysis-workflows.git
Path: definitions/subworkflows/sequence_to_trimmed_fastq_and_hisat_alignments.cwl Branch/Commit ID: b8000c793d6e7ce4d690406c4f914c5c62acd51f |
|
|
|
PGAP Pipeline
PGAP pipeline for external usage, powered via containers |
https://github.com/ncbi/pgap.git
Path: wf_common.cwl Branch/Commit ID: b38b0070edf910984f29a4a495b5dfa525b8b305 |
|
|
|
Motif Finding with HOMER with custom background regions
Motif Finding with HOMER with custom background regions --------------------------------------------------- HOMER contains a novel motif discovery algorithm that was designed for regulatory element analysis in genomics applications (DNA only, no protein). It is a differential motif discovery algorithm, which means that it takes two sets of sequences and tries to identify the regulatory elements that are specifically enriched in on set relative to the other. It uses ZOOPS scoring (zero or one occurrence per sequence) coupled with the hypergeometric enrichment calculations (or binomial) to determine motif enrichment. HOMER also tries its best to account for sequenced bias in the dataset. It was designed with ChIP-Seq and promoter analysis in mind, but can be applied to pretty much any nucleic acids motif finding problem. For more information please refer to: ------------------------------------- [Official documentation](http://homer.ucsd.edu/homer/motif/) |
https://github.com/datirium/workflows.git
Path: workflows/homer-motif-analysis-bg.cwl Branch/Commit ID: 10ce6e113f749c7bd725e426445220c3bdc5ddf1 |
|
|
|
transform_pack.cwl#fastq_clean_se.cwl
|
https://github.com/NCI-GDC/gdc-dnaseq-cwl.git
Path: workflows/bamfastq_align/transform_pack.cwl Branch/Commit ID: 3cb464a3a5c39cc060cd23d9c60918bc9ffb169b Packed ID: fastq_clean_se.cwl |
|
|
|
Get Proteins
|
https://github.com/ncbi/pgap.git
Path: wf_bacterial_prot_src.cwl Branch/Commit ID: b38b0070edf910984f29a4a495b5dfa525b8b305 |
