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Graph Name Retrieved From View
workflow graph alignment for nonhuman with qc

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

Path: definitions/pipelines/alignment_wgs_nonhuman.cwl

Branch/Commit ID: 174f3b239018328cec1d821947438b457552724c
workflow graph Build Bismark indices

Copy fasta_file file to the folder and run run bismark_genome_preparation script to prepare indices for Bismark Methylation Analysis. Bowtie2 aligner is used by default. The name of the output indices folder is equal to the genome input.

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

Path: workflows/bismark-index.cwl

Branch/Commit ID: 3d280a2a4b4f1560f56991086f712fa22ddc3364
workflow graph consensus_maf.cwl

Workflow to merge a large number of maf files into a single consensus maf file for use with GetBaseCountsMultiSample

https://github.com/mskcc/pluto-cwl.git

Path: cwl/consensus_maf.cwl

Branch/Commit ID: 5cad957fec135aa55ca8d588372db0557ca1cad5
workflow graph BwaAligner_1_0_0.cwl

https://github.com/PMCC-BioinformaticsCore/janis-pipelines.git

Path: janis_pipelines/wgs_somatic/cwl/tools/BwaAligner_1_0_0.cwl

Branch/Commit ID: ccca639fe0b3a8104ff9fcfa285f1134706032b8
workflow graph Apply filters to VCF file

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

Path: definitions/subworkflows/filter_vcf_mouse.cwl

Branch/Commit ID: 0805e8e0d358136468e0a9f49e06005e41965adc
workflow graph Subworkflow to allow calling different SV callers which require bam files as inputs

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

Path: definitions/subworkflows/single_sample_sv_callers.cwl

Branch/Commit ID: a59a803e1809a8fbfabca6b8962a8ad66dd01f1d
workflow graph portal-workflow.cwl

https://github.com/mskcc/pluto-cwl.git

Path: cwl/portal-workflow.cwl

Branch/Commit ID: 45604eaeea15030c7302941c761464ce392abf74
workflow graph facets-suite-workflow.cwl

Workflow for running the facets suite workflow on a single tumor normal pair Includes handling of errors in case execution fails for the sample pair

https://github.com/mskcc/pluto-cwl.git

Path: cwl/facets-suite-workflow.cwl

Branch/Commit ID: 45604eaeea15030c7302941c761464ce392abf74
workflow graph GAT - Genomic Association Tester

GAT: Genomic Association Tester ============================================== A common question in genomic analysis is whether two sets of genomic intervals overlap significantly. This question arises, for example, in the interpretation of ChIP-Seq or RNA-Seq data. The Genomic Association Tester (GAT) is a tool for computing the significance of overlap between multiple sets of genomic intervals. GAT estimates significance based on simulation. Gat implemements a sampling algorithm. Given a chromosome (workspace) and segments of interest, for example from a ChIP-Seq experiment, gat creates randomized version of the segments of interest falling into the workspace. These sampled segments are then compared to existing genomic annotations. The sampling method is conceptually simple. Randomized samples of the segments of interest are created in a two-step procedure. Firstly, a segment size is selected from to same size distribution as the original segments of interest. Secondly, a random position is assigned to the segment. The sampling stops when exactly the same number of nucleotides have been sampled. To improve the speed of sampling, segment overlap is not resolved until the very end of the sampling procedure. Conflicts are then resolved by randomly removing and re-sampling segments until a covering set has been achieved. Because the size of randomized segments is derived from the observed segment size distribution of the segments of interest, the actual segment sizes in the sampled segments are usually not exactly identical to the ones in the segments of interest. This is in contrast to a sampling method that permutes segment positions within the workspace.

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

Path: workflows/gat-run.cwl

Branch/Commit ID: c9e7f3de7f6ba38ee663bd3f9649e8d7dbac0c86
workflow graph Motif Finding with HOMER with custom background regions

Motif Finding with HOMER with custom 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. 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-bg.cwl

Branch/Commit ID: 60854b5d299df91e135e05d02f4be61f6a310fbc