Explore Workflows

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

Graph Name Retrieved From View
workflow graph Apply filters to VCF file

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

Path: definitions/subworkflows/filter_vcf_nonhuman.cwl

Branch/Commit ID: 2e0562a5c3cd7aac24af4c622a5ae68a7fb23a71
workflow graph advanced-header.cwl

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

Path: metadata/advanced-header.cwl

Branch/Commit ID: 60854b5d299df91e135e05d02f4be61f6a310fbc
workflow graph blastp_wnode_naming

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

Path: task_types/tt_blastp_wnode_naming.cwl

Branch/Commit ID: b38b0070edf910984f29a4a495b5dfa525b8b305
workflow graph WGS QC workflow

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

Path: definitions/subworkflows/qc_wgs.cwl

Branch/Commit ID: 457e101e3fb87e7fd792357afce00ed8ccbfbcdb
workflow graph Seed Protein Alignments

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

Path: protein_alignment/wf_seed_1.cwl

Branch/Commit ID: b38b0070edf910984f29a4a495b5dfa525b8b305
workflow graph Motif Finding with HOMER with random background regions

Motif Finding with HOMER with random 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. Here is how we generate background for Motifs Analysis ------------------------------------- 1. Take input file with regions in a form of “chr\" “start\" “end\" 2. Sort and remove duplicates from this regions file 3. Extend each region in 20Kb into both directions 4. Merge all overlapped extended regions 5. Subtract not extended regions from the extended ones 6. Randomly distribute not extended regions within the regions that we got as a result of the previous step 7. Get fasta file from these randomly distributed regions (from the previous step). Use it as background 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.cwl

Branch/Commit ID: 10ce6e113f749c7bd725e426445220c3bdc5ddf1
workflow graph spurious_annot pass2

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

Path: spurious_annot/wf_spurious_annot_pass2.cwl

Branch/Commit ID: b38b0070edf910984f29a4a495b5dfa525b8b305
workflow graph gathered exome alignment and somatic variant detection for cle purpose

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

Path: definitions/pipelines/somatic_exome_cle_gathered.cwl

Branch/Commit ID: f0cdc773e31e4aa116838e8aba4954c31bd3d68b
workflow graph tt_hmmsearch_wnode.cwl

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

Path: task_types/tt_hmmsearch_wnode.cwl

Branch/Commit ID: b38b0070edf910984f29a4a495b5dfa525b8b305
workflow graph cram_to_bam workflow

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

Path: definitions/subworkflows/cram_to_bam_and_index.cwl

Branch/Commit ID: 3a822294da63b4e19446a285e2fef075e23cf3d0