cv.stsvm: Cross validation for smoothed t-statistic to select...

In netClass: netClass: An R Package for Network-Based Biomarker Discovery

Description

Cross validation for smoothed t-statistic to select significant top ranked differential expressed genes

Usage

cv.stsvm(x=x, x.mi=NULL,y=y, folds=5,Gsub=matrix(1,100,100),op.method=c("pt","spb"), 
		repeats=3, parallel=FALSE, cores=2,DEBUG=TRUE, pt.pvalue=0.05,op=0.85,
		aa=1000,a=1,p=2,allF=TRUE, seed=1234,Cs=10^c(-3:3))

Arguments

x	A p x n matrix of expression measurements with p samples and n genes.
x.mi	A p x m matrix of expression measurements with p samples and m miRNAs.
y	A factor of length p comprising the class labels.
folds	Folds number of folds to perform
Gsub	An adjacency matrix that represents the underlying biological network.
op.method	Method for selecet optimal feature subgoups: pt is permutation test, sp is span bound.
repeats	Number of how often to repeat the x-fold cross-validation
parallel	Use parallel computing or not
cores	Number of cores will used when parallel is TRUE
DEBUG	Show debugging information in screen more or less.
pt.pvalue	Cut off p-value of permutation test
op	Optimal on top op
aa	permutation test steps for permutation test (pt); low bounds top op
a	constant value of random walk kernel
p	random walk step(s) of random walk kernel
allF	Using all features (TRUE) or only these genes mapped to prior information (FALSE).
seed	seed for random sampling.
Cs	Soft-margin tuning parameter of the SVM. Defaults to 10^c(-3:3).

Value

a LIST for Cross-Validation results

auc	The AUC values of each test fold
fits	The tranined models for traning folds
feat	The feature selected by each by the fits
labels	the original lables for training

Author(s)

Yupeng Cun [e-mail]

References

Yupeng Cun, Holger Frohlich (2013) Network and Data Integration for Biomarker Signature Discovery via Network Smoothed T-Statistics. PLoS ONE 8(9): e73074.

Examples

library(netClass)
data(expr)
data(ad.matrix)
x <- expr$genes
y <- expr$y

r.stsvm <- cv.stsvm(x=x[,1:500],x.mi=NULL,y=y,folds=3,Gsub=ad.matrix,op.method="pt",
				repeats=1, parallel=FALSE, cores=2,DEBUG=TRUE,pt.pvalue=0.05,op=0.9,
				aa=5,a=1,p=2,allF=TRUE, seed=1234,Cs=10^(-3:3))

netClass documentation built on May 29, 2017, 7:18 p.m.