Explore Workflows

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

Path: definitions/pipelines/germline_exome.cwl

Branch/Commit ID: ddd748516b25256a461ea9277303406fa2759b00

Workflow for running Facets-suite on a set of tumor normal pairs This workflow scatters over all the pairs in the input JSON to run all samples in parallel Input JSON format ----------------- { \"pairs\": [ { \"tumor_bam\": { \"class\": \"File\", \"path\": \"/test_data/bam/Tumor1.rg.md.abra.printreads.bam\" }, \"normal_bam\": { \"class\": \"File\", \"path\": \"/test_data/bam/Normal1.rg.md.abra.printreads.bam\" }, \"pair_maf\": { \"class\": \"File\", \"path\": \"/test_data/bam/Tumor1.Normal1.maf\" }, \"pair_id\": \"Tumor1.Normal1\" }, { \"tumor_bam\": { \"class\": \"File\", \"path\": \"/test_data/bam/Tumor2.rg.md.abra.printreads.bam\" }, \"normal_bam\": { \"class\": \"File\", \"path\": \"/test_data/bam/Normal2.rg.md.abra.printreads.bam\" }, \"pair_maf\": { \"class\": \"File\", \"path\": \"/test_data/bam/Tumor2.Normal2.maf\" }, \"pair_id\": \"Tumor2.Normal2\" } ] } Output format ------------- output └── facets-suite ├── Tumor1.Normal1.arm_level.txt ├── Tumor1.Normal1.gene_level.txt ├── Tumor1.Normal1_hisens.ccf.maf ├── Tumor1.Normal1_hisens.rds ├── Tumor1.Normal1_hisens.seg ├── Tumor1.Normal1_purity.rds ├── Tumor1.Normal1_purity.seg ├── Tumor1.Normal1.qc.txt ├── Tumor1.Normal1.snp_pileup.gz ├── Tumor1.Normal1.txt ├── Tumor2.Normal2.arm_level.txt ├── Tumor2.Normal2.gene_level.txt ├── Tumor2.Normal2_hisens.ccf.maf ├── Tumor2.Normal2_hisens.rds ├── Tumor2.Normal2_hisens.seg ├── Tumor2.Normal2_purity.rds ├── Tumor2.Normal2_purity.seg ├── Tumor2.Normal2.qc.txt ├── Tumor2.Normal2.snp_pileup.gz ├── Tumor2.Normal2.txt └── logs ├── success └── failed

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

Path: cwl/facets-workflow.cwl

Branch/Commit ID: 2a88d5c2d139ff817b21b480ccf9c1cd7139b00c

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

Path: task_types/tt_cache_asnb_entries.cwl

Branch/Commit ID: ea8c2aea64cab2241e02f4cb60ca9ca7593dfa58

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

Path: tests/wf/mut2.cwl

Branch/Commit ID: 7dec97bb8f0bc2d9e9eb710faf41f2e98cc7cdda

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

Path: definitions/pipelines/detect_variants_wgs.cwl

Branch/Commit ID: 00df82a529a58d362158110581e1daa28b4d7ecb

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

Path: definitions/pipelines/somatic_exome.cwl

Branch/Commit ID: 86fbeb95ef85111f3b4c6bc2bba8f06cef64e157

Single-Cell Differential Abundance Analysis Compares the composition of cell types between two tested conditions

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

Path: workflows/sc-rna-da-cells.cwl

Branch/Commit ID: b4d578c2ba4713a5a22163d9f8c7105acda1f22e

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

Path: definitions/subworkflows/varscan.cwl

Branch/Commit ID: 86fbeb95ef85111f3b4c6bc2bba8f06cef64e157

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: 7eef0294395d83ff0765fce61726a59d71126422

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

Path: tests/wf/scatterfail.cwl

Branch/Commit ID: 227f35a5ed50c423afba2353871950aa61d58872