SPreFuGED (version 1.0)

SPreFu: A function for selecting an optimal predictive function for a given gene expression data.

Description

This function uses the LME model and the estimated data characteristics to predict the accuracy (for binary direct classifiers) or transformed Brier score (for binary probabilistic classifiers) or transformed integrated Brier scores (for survival predictions).

Usage

SPreFu(dataCha, restModel)

Arguments

dataCha

an object returned by estimateDataCha and contains estimates of the data characteristics.

restModel

an object returned by fitLMEModel and contains the fitted LME model to be used for predictions.

Value

A list containing: A list containing:

References

Jong VL, Novianti PW, Roes KCB & Eijkemans MJC. Selecting a classification function for class prediction with gene expression data. Bioinformatics (2016) 32(12): 1814-1822;

See Also

estimateDataCha, fitLMEModel and plotSPreFu

Examples

#Let us consider a single simulated train data as our real-life dataset
myCov<-covMat(pAll=100, lambda=2, corrDE=0.75, sigma=0.25);
myData<-generateGED(covAll=myCov, nTrain=30, nTest=10);
data<-myData[[1]]$trainData;
dataY<-myData[[1]]$trainLabels;
myDataCha<-estimateDataCha(data, dataY);
myFit<-fitLMEModel();  #Takes roughly 250 Sec
myPred<-SPreFu(myDataCha, myFit);