# Preprocess data set with various methods
esets <- list()
print("fRPA")
library(RPA)
# hgu133a.rpa.priors
load("~/Rpackages/RPA/github/RPA/OnlineLearning/HGU133A-RPA-priors.RData")
esets$fRPA <- exprs(frpa(abatch, probe.parameters = hgu133a.rpa.priors))
colnames(esets$fRPA) <- gsub(".CEL", "", colnames(esets$fRPA))
colnames(esets$fRPA) <- gsub(".gz", "", colnames(esets$fRPA))
print("RPA")
library(RPA)
esets$RPA <- exprs(rpa(abatch))
colnames(esets$RPA) <- gsub(".CEL", "", colnames(esets$RPA))
print("fRMA")
library(frma)
esets$fRMA <- exprs(frma(abatch))
print("RMA")
esets$RMA <- exprs(rma(abatch))
#print("MAS")
esets$MAS <- log2(exprs(mas5(abatch)))
# Test
#hgu133afrmavecs
eset.frma <- frma(abatch, input.vecs = hgu133afrmavecs)
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