Explore Workflows

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

Graph Name Retrieved From View
workflow graph pass-unconnected.cwl

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

Path: v1.0/v1.0/pass-unconnected.cwl

Branch/Commit ID: f02557902989c749c9c2187c7045e340e2d76bfc
workflow graph Varscan Workflow

https://github.com/genome/cancer-genomics-workflow.git

Path: varscan/germline_workflow.cwl

Branch/Commit ID: ab3cc1f460146c60d7de417508f0c1ea70506e6a
workflow graph count-lines16-wf.cwl

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

Path: v1.0/v1.0/count-lines16-wf.cwl

Branch/Commit ID: e67f19d8a713759d761ecad050966d1eb043b85c
workflow graph Run pindel on provided region

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

Path: definitions/subworkflows/pindel_region.cwl

Branch/Commit ID: 0b6e8fd8ead7644cf5398395b76af5cf4011686f
workflow graph downsample unaligned BAM and align

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

Path: definitions/subworkflows/downsampled_alignment.cwl

Branch/Commit ID: 9161ef43f7bf0e22b365fde9ec92edcb8601798e
workflow graph downsample unaligned BAM and align

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

Path: definitions/subworkflows/downsampled_alignment.cwl

Branch/Commit ID: 04d21c33a5f2950e86db285fa0a32a6659198d8a
workflow graph kmer_seq_entry_extract_wnode

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

Path: task_types/tt_kmer_seq_entry_extract_wnode.cwl

Branch/Commit ID: 001fab592188cb525afa1c4db6226b833faec106
workflow graph chksum_for_a_corrupted_fastq_file.cwl

https://github.com/cancerit/workflow-seq-import.git

Path: cwls/chksum_for_a_corrupted_fastq_file.cwl

Branch/Commit ID: 084ba4ee91af7bc98abbc6e13c3937cb87f932ae
workflow graph umi molecular alignment workflow

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

Path: definitions/subworkflows/molecular_qc.cwl

Branch/Commit ID: 9161ef43f7bf0e22b365fde9ec92edcb8601798e
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: 2f0db4b3c515f91c5cfda19c78cf90d339390986