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biosigner (version 1.0.4)

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.

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Version

Version

1.0.4

License

CeCILL

Maintainer

Philippe Rinaudo

Last Published

February 15th, 2017

Functions in biosigner (1.0.4)

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