Nothing
mancie<-function(mat_main,mat_supp,cutoff1=0.5,cutoff2=0)
{
mat_main=as.matrix(mat_main)
mat_supp=as.matrix(mat_supp)
mat_final=mat_main
cat1=cat2=cat3=0
for (i in 1:dim(mat_main)[1]) # expression values are not changed if normalization fails
{
v1=mat_main[i,]
v2=mat_supp[i,]
if (cor(v1,v2)>cutoff1)
{
PCA=prcomp(cbind(v1,v2),.scale=T)$x[,1]
if (cor(PCA,v1)<0) {PCA=-PCA}
cat1=cat1+1
}else if (cor(v1,v2)>cutoff2)
{
PCA=(scale(v1)+cor(v1,v2)*scale(v2))[,1]
cat2=cat2+1
}else
{
PCA=v1
cat3=cat3+1
}
mat_final[i,]=(PCA-mean(PCA))/sd(PCA)*sd(v1)+mean(v1)
}
cat1=cat1/dim(mat_final)[1]
cat2=cat2/dim(mat_final)[1]
cat3=cat3/dim(mat_final)[1]
cat(paste("Percentage of rows with correlation >cutoff1:",cat1,"\n"))
if (cat1<0.1 || cat1>0.9) {warning("Too few or too many rows in this category!")}
cat(paste("Percentage of rows with correlation <=cutoff1 and >cutoff2:",cat2,"\n"))
if (cat2<0.1 || cat2>0.9) {warning("Too few or too many rows in this category!")}
cat(paste("Percentage of rows with correlation <=cutoff2:",cat3,"\n"))
mat_final
}
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