library(ALL)
library(limma)
data(ALL)
ALL.pdat <- pData(ALL)
date.cr.chr <- as.character(ALL.pdat$date.cr)
diag.chr <- as.character(ALL.pdat$diagnosis)
date.cr.t <- strptime(date.cr.chr,"%m/%d/%Y")
diag.t <- strptime(diag.chr,"%m/%d/%Y")
days2remiss <- as.numeric(date.cr.t - diag.t)
ALL.exprs <- exprs(ALL)[,!is.na(days2remiss)]
days2remiss <- days2remiss[!is.na(days2remiss)]
design.matrix <- cbind(rep(1,length(days2remiss)),days2remiss)


best.gene.crossv<-function(i.xval){
ALL.exprs.train <- ALL.exprs[,xval.grps!=i.xval]
design.matrix.train <- design.matrix[xval.grps!=i.xval,]
d2r.fit.train <- lmFit(ALL.exprs.train,design.matrix.train)
best.gene <- row.names(topTable(eBayes(d2r.fit.train),"days2remiss"))[1]
return(best.gene)
}

run.best.gene.crossv<-function(n.xval){
  xval.grps <- sample((1:dim(ALL.exprs)[2])%%n.xval+1)
  res<-sapply(1:n.xval, best.gene.crossv)
  return(res)
}

N.reps<-5
n.xval<-5
best.crossv.res<-replicate(N.reps, run.best.gene.crossv(n.xval))