Explore Workflows

Example CWL workflow that uses some advanced features

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

Path: cwl/example_workflow.cwl

Branch/Commit ID: 462f6015c9268a4205b6e81de018a470b8a4a153

https://github.com/common-workflow-language/cwl-v1.2.git

Path: tests/count-lines4-wf.cwl

Branch/Commit ID: 31ec48a8d81ef7c1b2c5e9c0a19e7623efe4a1e2

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

Path: definitions/pipelines/rnaseq_star_fusion.cwl

Branch/Commit ID: 9cbf2a483e1b9e4cdb8e2564be27a9e64fc1169e

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

Path: task_types/tt_align_merge_sas.cwl

Branch/Commit ID: e9cc6de8cd1e00345969c646e5e6f27d7d10420f

https://github.com/common-workflow-language/cwl-v1.2.git

Path: tests/io-file-default-wf.cwl

Branch/Commit ID: 31ec48a8d81ef7c1b2c5e9c0a19e7623efe4a1e2

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: 261c0232a7a40880f2480b811ed2d7e89c463869

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

Path: tests/wf/cache_test_workflow.cwl

Branch/Commit ID: b82ce7ae901a54c7a062fd5eefd8d5ceb5a4d684

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

Path: definitions/subworkflows/duplex_alignment.cwl

Branch/Commit ID: 4aba7c6591c2f1ebd827a36d325a58738c429bea

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

Path: definitions/subworkflows/bgzip_and_index.cwl

Branch/Commit ID: 5cb188131f786ed33156e2f0e3dd63ab9c04245d

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

Path: definitions/subworkflows/gatk_haplotypecaller_iterator.cwl

Branch/Commit ID: 4a04ad33e311c5e647cef848b74034477cb3c47e