WritesigFeature: Write the features and sample IDs.
In sigFeature: sigFeature: Significant feature selection using SVM-RFE & t-statistic

Description Usage Arguments Details Value Author(s) References See Also Examples

This function will write the output data produce from the function sigFeatureRanking.enfold.

1	WritesigFeature(results, x, fileName="Result")

`results`	the object produce by the function named sigFeatureRanking.enfold
`x`	n-by-d data matrix to train (n chips/patients, d clones/genes).
`fileName`	name of the output file.

This function will write the variables.

results output file.

Pijush Das <topijush@gmail.comn>, et al.

Becker, N., Werft, W., Toedt, G., Lichter, P. and Benner, A.(2009) PenalizedSVM: a R-package for feature selection SVM classification, Bioinformatics, 25(13),p 1711-1712

predict.penSVM, svm (in package e1071)

#Example for WritesigFeature()
#Data set taken from GSE2280
library(SummarizedExperiment)
data(ExampleRawData, package="sigFeature")

x  <- t(assays(ExampleRawData)$counts)
y  <- colData(ExampleRawData)$sampleLabels


#For 10 fold cross validation.
#results = sigFeature.enfold(x,y,"kfold",10)


#to write the output
#data(results)
#WritesigFeature(results, x)