Explore Workflows

https://github.com/yyoshiaki/VIRTUS.git

Path: workflow/download_gtf.cwl

Branch/Commit ID: 49687daefb8ae715386f722702755ffaa49283e6

Workflow runs [Bowtie](http://bowtie-bio.sourceforge.net/tutorial.shtml) v1.2.0 (12/30/2016) to build indices for reference genome provided in a single FASTA file as fasta_file input. Generated indices are saved in a folder with the name that corresponds to the input genome

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

Path: workflows/bowtie-index.cwl

Branch/Commit ID: 104059e07a2964673e21d371763e33c0afeb2d03

STARR-seq pipeline - reads: PE

https://github.com/alexbarrera/GGR-cwl.git

Path: v1.0/STARR-seq_pipeline/pipeline-pe-umis.cwl

Branch/Commit ID: 1a0dd34d59ec983d1f7ad77bff35da2f016e3134

https://github.com/uc-cdis/genomel_pipelines.git

Path: genomel/genomel_cohort_freebayes.cwl

Branch/Commit ID: c661469505c606e1353f23c21a6654724a9d8d63

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

Path: definitions/subworkflows/molecular_qc.cwl

Branch/Commit ID: 7638b3075863ae8172f4adaec82fb2eb8e80d3d5

The main workflow that: produces two reproducible peaks via IDR given two eCLIP samples (1 input, 1 IP each). runs the 'rescue ratio' statistic runs the 'consistency ratio' statistic

https://github.com/YeoLab/merge_peaks.git

Path: cwl/wf_full_IDR_pipeline_2inputs_scatter.cwl

Branch/Commit ID: aedc0a14d4ba109ee65678a3201a52c5bb6ad473

https://github.com/inab/Wetlab2Variations.git

Path: cwl-workflows/workflows/workflow.cwl

Branch/Commit ID: 31348ed533961f84cf348bf1af660ad9de6f870c

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: 104059e07a2964673e21d371763e33c0afeb2d03

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

Path: bacterial_orthology/wf_bacterial_orthology_conditional.cwl

Branch/Commit ID: e2a6cbcc36212433d8fbc804919442787a5e2a49

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

Path: definitions/pipelines/germline_wgs.cwl

Branch/Commit ID: 7638b3075863ae8172f4adaec82fb2eb8e80d3d5