Explore Workflows

View already parsed workflows here or click here to add your own

Graph Name Retrieved From View
workflow graph HBA_target.cwl

https://git.astron.nl/eosc/prefactor3-cwl.git

Path: workflows/HBA_target.cwl

Branch/Commit ID: 7b6185e2e6f9d36b1987274e82842c82ba6f8342
workflow graph count-lines10-wf.cwl

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

Path: tests/count-lines10-wf.cwl

Branch/Commit ID: 7d7986a6e852ca6e3239c96d3a05dd536c76c903
workflow graph scatter-wf2.cwl

https://github.com/common-workflow-language/cwl-v1.1.git

Path: tests/scatter-wf2.cwl

Branch/Commit ID: 3e90671b25f7840ef2926ad2bacbf447772dda94
workflow graph rnaseq-se-dutp.cwl

Runs RNA-Seq dUTP BioWardrobe basic analysis with strand specific single-end data file.

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

Path: workflows/rnaseq-se-dutp.cwl

Branch/Commit ID: 896422c9ff1995024cb77675edcd4d973ae11f7a
workflow graph bulk scRNA-seq pipeline using Salmon

https://github.com/hubmapconsortium/salmon-rnaseq.git

Path: bulk-pipeline.cwl

Branch/Commit ID: 8af5a1c9c99b06e7024e4ddbf45a15cf07ea9410
workflow graph mut2.cwl

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

Path: tests/wf/mut2.cwl

Branch/Commit ID: 6d8c2a41e2c524e8d746020cc91711ecc3418a23
workflow graph ValidateTelescopeSimulationModel

Validate the telescope simulation model as a whole.

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

Path: workflows/ValidateTelescopeSimulationModel.cwl

Branch/Commit ID: 789752af87eb190387ff2acb4c95c7a5cdb961e7
workflow graph gcaccess_from_list

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

Path: task_types/tt_gcaccess_from_list.cwl

Branch/Commit ID: 4ffbad9ffeab15ec8af5f6f91bd352ef96d1ef77
workflow graph step-valuefrom4-wf.cwl

https://github.com/common-workflow-language/cwl-v1.1.git

Path: tests/step-valuefrom4-wf.cwl

Branch/Commit ID: 3e90671b25f7840ef2926ad2bacbf447772dda94
workflow graph PCA - Principal Component Analysis

Principal Component Analysis -------------- Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables (entities each of which takes on various numerical values) into a set of values of linearly uncorrelated variables called principal components. The calculation is done by a singular value decomposition of the (centered and possibly scaled) data matrix, not by using eigen on the covariance matrix. This is generally the preferred method for numerical accuracy.

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

Path: workflows/pca.cwl

Branch/Commit ID: dda6e8b5ada3f106a2b3bfcc1b151eccf9977726