Hi,

I have a question about my agilent microarray data.

It includes  before & after infection data of the same individuals and also replicates of non-infected other individuals as a kind of  control to these infected ones . There are 15 individuals and thus 30 microarray files. I am using "limma" package to read and normalize them. However, i have doubts if i should use the codes below to identifiy genes differently expressed, because when i cluster the datasets, the replicates do not group together:

RG_2= backgroundCorrect(z, method="minimum")
MA.exp= normalizeBetweenArrays(RG_2)
MA.exp_log= log(MA.exp$E)

SibShip = factor(targets_paired$SibShip)
Treat = factor(targets_paired$Treatment, levels=c("Not Inf.","Infected"))
design = model.matrix(~SibShip+Treat)
fit = lmFit(MA.exp_log, design)
fit = eBayes(fit)
topTable(fit, coef="TreatInfected")

In this case, should I analyze the data by just grouping as Infected & Non-infected?

Thank you in advance.

According limma, you need to go through one within and between normalization if using two color arrays, or a single normalization if using a single color. You need to provide with this information, and also with the targets definition