Explore Workflows

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Graph Name Retrieved From View
workflow graph Alignment without BQSR

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

Path: definitions/subworkflows/sequence_to_bqsr_nonhuman.cwl

Branch/Commit ID: 174f3b239018328cec1d821947438b457552724c
workflow graph Filter single sample sv vcf from depth callers(cnvkit/cnvnator)

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

Path: definitions/subworkflows/sv_depth_caller_filter.cwl

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

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

Path: metadata/chipseq-header.cwl

Branch/Commit ID: a839eb6390974089e1a558c49fc07b4c66c50767
workflow graph Chipseq alignment for nonhuman with qc and creating homer tag directory

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

Path: definitions/pipelines/chipseq_alignment_nonhuman.cwl

Branch/Commit ID: 389f6edccab082d947bee9c032f59dbdf9f7c325
workflow graph pindel parallel workflow

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

Path: definitions/subworkflows/pindel.cwl

Branch/Commit ID: 43c790e2ee6a0f3f42e40fb4d9a9005eb8de747a
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: 9850a859de1f42d3d252c50e15701928856fe774
workflow graph gcaccess_from_list

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

Path: task_types/tt_gcaccess_from_list.cwl

Branch/Commit ID: e2a6cbcc36212433d8fbc804919442787a5e2a49
workflow graph cmsearch-multimodel.cwl

https://github.com/EBI-Metagenomics/ebi-metagenomics-cwl.git

Path: workflows/cmsearch-multimodel.cwl

Branch/Commit ID: 7bb76f33bf40b5cd2604001cac46f967a209c47f
workflow graph final-workflow.cwl

https://github.com/NAL-i5K/Organism_Onboarding.git

Path: final-workflow.cwl

Branch/Commit ID: 0b58c250e8ab7c5efae29443f08ea74316127041
workflow graph readme-genePrediction-workflow.cwl

https://github.com/NAL-i5K/Organism_Onboarding.git

Path: flow_create_readme/readme-genePrediction-workflow.cwl

Branch/Commit ID: 7198756b4b1519d102178042924671bd677e9b17