Explore Workflows

Remove reads from fasta files based on sequence stats. Return fasta files with reads passed and reads removed.

https://github.com/MG-RAST/pipeline.git

Path: CWL/Workflows/preprocess-fasta.workflow.cwl

Branch/Commit ID: 932da3abed7166bd5a962871386ba2c31d47b85c

Single-cell Differential Expression =================================== Runs differential expression analysis for a subset of cells between two selected conditions.

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

Path: workflows/sc_diff_expr.cwl

Branch/Commit ID: bf80c9339d81a78aefb8de661bff998ed86e836e

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

Path: definitions/subworkflows/molecular_alignment.cwl

Branch/Commit ID: 5be54bf09092c53e6c7797a875f64a360d511d7f

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

Path: definitions/subworkflows/fp_filter.cwl

Branch/Commit ID: 5cb188131f786ed33156e2f0e3dd63ab9c04245d

Simulation steps pipeline

https://github.com/ILIAD-ocean-twin/application_package.git

Path: workflow_in_workflow/original.cwl

Branch/Commit ID: bdc301ea10f1a16e8db894c6a6115c829484f80e

Packed ID: main_pipeline

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

Path: task_types/tt_bact_get_kmer_reference.cwl

Branch/Commit ID: 205f4ceb47ba7537a6923d2dfb03668317c2fd89

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: 462f6015c9268a4205b6e81de018a470b8a4a153

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

Path: cwltool/schemas/v1.0/v1.0/count-lines8-wf.cwl

Branch/Commit ID: 280a852e74aec08cf79687e8004e17b1ab464534

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: bf80c9339d81a78aefb8de661bff998ed86e836e

Runs ChIP-Seq BioWardrobe basic analysis with single-end data file.

https://github.com/Barski-lab/workflows.git

Path: workflows/chipseq-se.cwl

Branch/Commit ID: 812b0ff40dda18ab7a9a872ff13a577be8531ba6