# biosigner v1.0.4

## Signature discovery from omics data

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.

## Functions in biosigner

 Name Description getSignatureLs Signatures selected by the models biosign Builds the molecular signature. predict.biosign Predict method for 'biosign' signature objects plot.biosign Plot method for 'biosign' signature objects diaplasma Analysis of plasma from diabetic patients by LC-HRMS biosign-class Class "biosign" getAccuracyMN Accuracies of the full model and the models restricted to the signatures show.biosign Show method for 'biosign' signature objects No Results!