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→Microarray Analysis
eset.norm <- normalize.ExpressionSet.quantiles(eset) #normalize expression set by quantile method
pData(eset) #to see phenotype annotation data
design <- =model.matrix(~-1+factor(c(1,1,1,1,1,1,1,02,02,02,02,02,02,0,0))2,eset2) #set design matirxcolnames(design) <- c("resistantobese","sensitivelean") # give names to the treatment groups
design #check the design matrix
fit <- lmFit(eset.norm,design) #Fit data to linear modelcont.matrix <- makeContrasts(Obese.vs.Lean=obese-lean, levels=design)fit.normcont <- contrasts.fit(fit, cont.matrix)fit.cont.eb <- eBayes(fit.norm) #Empirical Bayeswrite.csv(fit.normcont.eb, file="filename.csv") #write to CSV file
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