Explore Workflows

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Graph Name Retrieved From View
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
workflow graph dynresreq-workflow-inputdefault.cwl

https://github.com/common-workflow-language/cwl-v1.1.git

Path: tests/dynresreq-workflow-inputdefault.cwl

Branch/Commit ID: 368b562a1449e8cd39ae8b7f05926b2bfb9b22df
workflow graph Alignment without BQSR

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

Path: definitions/subworkflows/sequence_to_bqsr_mouse.cwl

Branch/Commit ID: 74647cc0f1abac4ee22950cfa89c44cf2ca3cffd
workflow graph Motif Finding with HOMER with target and background regions from peaks

Motif Finding with HOMER with target and background regions from peaks --------------------------------------------------- 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-peak.cwl

Branch/Commit ID: 2f0db4b3c515f91c5cfda19c78cf90d339390986
workflow graph count-lines9-wf-noET.cwl

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

Path: v1.0/v1.0/count-lines9-wf-noET.cwl

Branch/Commit ID: e67f19d8a713759d761ecad050966d1eb043b85c
workflow graph Detect DoCM variants

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

Path: docm/germline_workflow.cwl

Branch/Commit ID: ab3cc1f460146c60d7de417508f0c1ea70506e6a
workflow graph FASTQ to BQSR

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

Path: definitions/subworkflows/fastq_to_bqsr.cwl

Branch/Commit ID: 00df82a529a58d362158110581e1daa28b4d7ecb