pamr.fdr {pamr}R Documentation

A function to estimate false discovery rates for the nearest shrunken centroid classifier

Description

A function to estimate false discovery rates for the nearest shrunken centroid classifier

Usage

pamr.fdr(trained.obj, data,  nperms=100, 
 xl.mode=c("regular","firsttime","onetime","lasttime"),xl.time=NULL, xl.prevfit=NULL)

Arguments

trained.obj The result of a call to pamr.train
data Data object; same as the one passed to pamr.train
nperms Number of permutations for estimation of FDRs. Default is 100
xl.mode Used by Excel interface
xl.time Used by Excel interface
xl.prevfit Used by Excel interface

Details

pamr.fdr estimates false discovery rates for a nearest shrunken centroid classifier

Value

A list with components:

results Matrix of estimates FDRs for various various threshold values. Reported are both the median and 90th percentile of the FDR over permutations
pi0 The estimated proportion of genes that are null, i.e. not significantly different

Author(s)

Trevor Hastie,Robert Tibshirani, Balasubramanian Narasimhan, and Gilbert Chu

References

Examples

set.seed(120)
x <- matrix(rnorm(1000*20),ncol=20)
y <- sample(c(1:4),size=20,replace=TRUE)

mydata <- list(x=x,y=factor(y), geneid=as.character(1:nrow(x)), genenames=paste("g",as.character(1:nrow(x)),sep=""),)

mytrain <-   pamr.train(mydata)
myfdr <- pamr.fdr(mytrain, mydata)

[Package pamr version 1.28.0 Index]