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
