biosigner (version 1.0.6)

Signature discovery from omics data

Description

Feature selection is critical in omics data analysis to extract restricted and meaningful molecular signatures from complex and high-dimension data, and to build robust classifiers. This package implements a new method to assess the relevance of the variables for the prediction performances of the classifier. The approach can be run in parallel with the PLS-DA, Random Forest, and SVM binary classifiers. The signatures and the corresponding 'restricted' models are returned, enabling future predictions on new datasets. A Galaxy implementation of the package is available within the Workflow4metabolomics.org online infrastructure for computational metabolomics.

Copy Link

Version

Down Chevron

Version

1.0.6

License

CeCILL

Last Published

June 11th, 2016

Functions in biosigner (1.0.6)