Package: Geneclassifiers (version 1.0.0)

Abstract

Combining gene expression profiling data with survival data has led to the development of robust outcome predictors (gene classifiers).This package provides a method for running gene classifiers generating patient specific predictive outcomes. This package is intended to support and enable research. The workflow is illustrated in Figure 1. The raw gene expression data obtained by microarray experiments is normalized using existing techniques (independent of this package). The choice of normalization method is dictated by the classifier. Some classifiers were developed using MAS5.0. In that case, the data to be classified should be normalized using MAS5.0. Normalization is followed by preprocessing (this package) and generating scores/classifications (this package). This package is suitable only for datasets of at least 20 patients.

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Cite this paper

@inproceedings{Kuiper2017PackageG, title={Package: Geneclassifiers (version 1.0.0)}, author={Ruurd Kuiper}, year={2017} }