rMisbeta (version 1.0)

performance.eval: This function estimates the different performance indices like, TPR,TNR,FPR,FNR,AUC etc. for number of top genes

Description

This function estimates the different performance indeces,like TPR,TNR,FPR,FNR,AUC etc. to asses the performance of the method

Usage

performance.eval(PostP, de.true, TopG, decreasing = TRUE)

Arguments

PostP

p-values should be given to identify the different performance index.

de.true

The true DE information should be given to calculates the performance index.

TopG

How many Top DE genes will be used to calculate the performance indices.

decreasing

Is the p-values decreasing or increasing order.

Value

The following performance indices are produced by performance.eval():

TP

Number of True positive.

TN

Number of True negative.

FP

Number of False positive.

FN

Number of False negative.

R1

Specificity.

TPR

True positive rate.

TNR

True negative rate.

FPR

False positive rate.

FNR

False negative rate.

FDR

False discovery rate.

ER

Error rate.

AUC2

Area under the curve of ROC.

pAUC2

Partial Area under the curve of ROC with FDR controlled at 0.2.

Examples

# NOT RUN {
# Performance evaluation in presence of outliers and missing values
nG=1000
n1=n2=5
pde=0.1
Simdat=Sim2Group(nG,n1,n2,var0=0.1,pde=0.1) 
xx=Simdat$outmat
TrueDE=Simdat$DEtrue
MisOutdat<-OutMisDat(xx,pctOut=0.1,pctMis=0.1)
misdat_zero<-MisOutdat
misdat_zero[is.na(misdat_zero)]<-0
cl=rep(c(1,2),each=n1)

res=remat(MisOutdat,cl)
up_mat<-res$remat


pTtest_zero<-pTtest_beta<-NULL
for (j1 in 1:dim(xx)[1])
{
DataYY <- data.frame(YY =misdat_zero[j1,], FactorLevels = factor(cl))
DataYY2 <- data.frame(YY2=up_mat[j1,], FactorLevels2 = factor(cl))
pTtest_zero[j1] <-  t.test(YY~FactorLevels,data=DataYY, paired=FALSE)[[3]]
pTtest_beta[j1] <-  t.test(YY2~FactorLevels2,data=DataYY2, paired=FALSE)[[3]]
} 

TopDEn<-seq(nG*pde/10, pde*nG, length=10)

performance_zero<-performance.eval(pTtest_zero,TrueDE,TopDEn,decreasing=FALSE);
performance_beta<-performance.eval(pTtest_beta,TrueDE,TopDEn,decreasing=FALSE);
plot(performance_zero$FPR,performance_zero$TPR,type="o",  
xlab="False Positive Rate",ylab="True Positive Rate",ylim=c(0,1))
points(performance_beta$FPR,performance_beta$TPR,type="o",col=2)
legend("bottomright", c('t_test_zero','t_test_rMisbeta'),lwd=1,cex=0.8,col=c(1,2))
# }