Nothing
corr.sim.summary <-
function(sim.res.obj, # A simulation result object
ebp.alpha=0.1) # The ebp cut-off
{
k<-length(sim.res.obj)
ngenes<-dim(sim.res.obj$rdist)[1]
pr.reject<-matrix(NA,ngenes,k-6)
true.null<-(sim.res.obj$slope==0)
auc<-fdr<-rep(NA,k-6)
for (i in 1:(k-6))
{
rej<-(sim.res.obj[[6+i]]<=ebp.alpha)
pr.reject[,i]<-rowMeans(rej)
top<-colSums(rej[true.null,])
bot<-colSums(rej)
bot[bot==0]<-1 # If no rejections, define denominator as 1 so that FDR=0 as in Benjamini & Hochberg 1995
fdr[i]<-mean(top/bot)
auc[i]<-compute.sim.auc(sim.res.obj[[6+i]],true.null)
}
obj.names<-names(sim.res.obj)
mtx.names<-as.character(obj.names[6+(1:(k-6))])
names(auc)<-names(fdr)<-mtx.names
colnames(pr.reject)<-mtx.names
gene.lbl0<-matrix(paste(round(sim.res.obj$slope,1),"x + ",sim.res.obj$rdist,"(",sim.res.obj$dist.param1,",",
sim.res.obj$dist.param2,")",sep=""),ncol=dim(sim.res.obj$rdist)[2])
gene.lbl1<-gene.lbl0[,1]
if (dim(sim.res.obj$rdist)[2]>1)
for (i in 2:(dim(sim.res.obj$rdist)[2])) gene.lbl1<-paste(gene.lbl1,gene.lbl0[,i],sep="_")
rownames(pr.reject)<-gene.lbl1
uniq.gene.lbl<-unique(gene.lbl1)
nuniq<-length(uniq.gene.lbl)
pr.rej.summary<-matrix(NA,nuniq,dim(pr.reject)[2])
for (i in 1:nuniq)
{
gene.mtch<-is.element(gene.lbl1,uniq.gene.lbl[i])
nmtch<-sum(gene.mtch)
pr.rj.mtx<-matrix(pr.reject[gene.mtch,],nmtch)
pr.rej.summary[i,]<-colMeans(pr.rj.mtx)
}
if (any(!true.null)) sim.power<-colMeans(pr.reject[!true.null,])
else sim.power<-NA
if (any(true.null)) sim.level<-colMeans(pr.reject[true.null,])
else sim.level<-NA
rownames(pr.rej.summary)<-uniq.gene.lbl
colnames(pr.rej.summary)<-colnames(pr.reject)
res<-list(test.specs=sim.res.obj$test.specs,
ebp.def=sim.res.obj$ebp.def,
rdist=sim.res.obj$rdist,
dist.param1=sim.res.obj$dist.param1,
dist.param2=sim.res.obj$dist.param2,
ebp.alpha=ebp.alpha,pr.reject=pr.reject,
true.null=true.null,pr.rej.summary=pr.rej.summary,
sim.power=sim.power,sim.level=sim.level,sim.fdr=fdr,sim.auc=auc)
return(res)
}
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