Explore Workflows

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

Graph Name Retrieved From View
workflow graph Run tRNAScan

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

Path: bacterial_trna/wf_trnascan.cwl

Branch/Commit ID: 70e530b65b33301032b7510095d89e497bf5e34e

workflow graph Non-Coding Bacterial Genes

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

Path: bacterial_noncoding/wf_bacterial_noncoding.cwl

Branch/Commit ID: 269d656eb8eaa5fc29a5f74cb0aa5756868b46b7

workflow graph Non-Coding Bacterial Genes

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

Path: bacterial_noncoding/wf_bacterial_noncoding.cwl

Branch/Commit ID: 70e530b65b33301032b7510095d89e497bf5e34e

workflow graph preprocess_vcf.cwl

This workflow will perform preprocessing steps on VCFs for the OxoG/Variantbam/Annotation workflow.

https://github.com/baminou/OxoG-Dockstore-Tools.git

Path: preprocess_vcf.cwl

Branch/Commit ID: 9b7fde6e34f632ceb1d0e2b1a5799a6f722688c5

workflow graph kmer_top_n_extract

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

Path: task_types/tt_kmer_top_n_extract.cwl

Branch/Commit ID: 0932e4d778ea981cdc19702eab7fc8d572fe8216

workflow graph collate_unique_rRNA_headers.cwl

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

Path: tools/collate_unique_rRNA_headers.cwl

Branch/Commit ID: e1b0fceb0efce1b787b5782408cdf6f163b8ff56

workflow graph Find reads with predicted coding sequences above 60 AA in length

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

Path: workflows/orf_prediction.cwl

Branch/Commit ID: 712de5a25d08e359f831f60d1aedd0f3fd1ca32d

workflow graph protein_extract

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

Path: progs/protein_extract.cwl

Branch/Commit ID: c402e1347732654dfd716767c95a67a72366a4ab

workflow graph tt_hmmsearch_wnode.cwl

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

Path: task_types/tt_hmmsearch_wnode.cwl

Branch/Commit ID: c402e1347732654dfd716767c95a67a72366a4ab

workflow graph wf_makeblastdb.cwl

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

Path: amr_finder/wf_makeblastdb.cwl

Branch/Commit ID: 567a2d3c57f22f6954416c2e48d630cccf0b0cdd