Explore Workflows

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

Path: task_types/tt_format_rrnas_from_seq_entry.cwl

Branch/Commit ID: b4a6e46405c08e0b14ad92f0ab38bcc4a69caa5c

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

Path: definitions/subworkflows/pindel_cat.cwl

Branch/Commit ID: 31602b94b34ff55876147c7299e1bec47e8d1a31

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

Path: task_types/tt_bact_get_kmer_reference.cwl

Branch/Commit ID: f403d9e26d60d3e3591a03077bc9dfa188b1c2bb

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

Path: definitions/subworkflows/docm_germline.cwl

Branch/Commit ID: 293dc7b83639d21a56efff2baf9dfe4e97b9b806

Workflow runs homer-make-tag-directory.cwl tool using scatter for the following inputs - bam_file - fragment_size - total_reads `dotproduct` is used as a `scatterMethod`, so one element will be taken from each array to construct each job: 1) bam_file[0] fragment_size[0] total_reads[0] 2) bam_file[1] fragment_size[1] total_reads[1] ... N) bam_file[N] fragment_size[N] total_reads[N] `bam_file`, `fragment_size` and `total_reads` arrays should have the identical order.

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

Path: tools/heatmap-prepare.cwl

Branch/Commit ID: a0b22644ca178b640fb74849d23b7c631022f0b5

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

Path: definitions/subworkflows/align.cwl

Branch/Commit ID: 3bebaf9b70331de9f4845e2223c55082f5a812fb

Outputs a message using echo

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

Path: tests/wf/hello-workflow.cwl

Branch/Commit ID: fd6e054510e2bb65eed4069a3a88013d7ecbb99c

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

Path: definitions/pipelines/tumor_only_detect_variants.cwl

Branch/Commit ID: 038cb3617a1966a1057386adcde97ce55d9e1139

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: f3e44d3b0f198cf5245c49011124dc3b6c2b06fd

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

Path: task_types/tt_hmmsearch_wnode_plus_qdump.cwl

Branch/Commit ID: f403d9e26d60d3e3591a03077bc9dfa188b1c2bb