Hi,

Hope somebody can guide me on this? We recently ran 48 rat samples on 6 Agilent G3 GEx Rat V2 chips. I have no experience with Agilent arrays so I hope somebody can help me with this.

I had some issues reading in the files so I made a .txt file of each separate array/sample. My first question would be whether it is ok to read in all the arrays from the different chips all at once or whether I need to do some preprocessing to get rid of potential differences between the chips?

The samples represent 3 different conditions but also measured in different tissues, equally spread over the 6 chips.

If I read these in all at once, can I just do the standard background correction and normalization as suggested in the limma guidelines?

And also the array contains ERCC spike in probes, how do I handle these?

I was thinking about doing something like below but am not sure at all whether it would be ok to do so.

targets <- readTargets("targets.txt", row.names="FileName")

x <- read.maimages(targets$FileName, source="agilent", columns=list(R="F635 Median", Rb="B635 Median"), annotation=c("Row","Column","ID","Name"))

bc<-backgroundCorrect.matrix(x, method="normexp")

E <- normalizeBetweenArrays(bc, method="quantile")

ct <- factor(targets$Type)

design <- model.matrix(~0+ct)

colnames(design) <- levels(ct)

fit <- lmFit (E,design)

contrasts <- makeContrasts (treatment-control, levels=design)

contrasts.fit <- eBayes(contrasts.fit(fit, contrasts))

summary(decideTests(contrasts.fit, method="global"))

a<-topTable(contrasts.fit, coef=1)

write.table(a, file="treatment-control.txt", sep="\t")

All of your help/suggestions are very much appreciated.

Thanks, Annelies