We recently received a dataset of 48 rat samples on 6 Agilent G3 GEx Rat V2 chips. I have no experience with Agilent arrays so I’m really struggling with this one.
A couple of questions I was hoping someone could help me with:
1) This dataset contains samples from 3 different tissues that were randomized across all chips. I was wondering whether it is ok to read in all the data in at once and then normalize or whether it would be better to normalize per tissue? If that is even ok to do so..
2) I had some issues reading in the datasets that were provided to me so I used the command below to read in the files but I’m not sure if this is ok:
targets <- readTargets("targets.txt", row.names="FileName") x <- read.maimages(targets$FileName, source="agilent", columns=list(R="F635 Median", Rb="B635 Median"), annotation=c("Row","Column","ID","Name"))
3) The chip contains ERCC spike in probes but I’m not sure how to handle these in the analysis. I tried to analyze the data using commands below
bc<-backgroundCorrect.matrix(x, method="normexp") E <- normalizeBetweenArrays(bc, method="quantile") ct <- factor(targets$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")
But I guess that is not the correct way to do so because the spike ins turned up being differentially expressed.. Can anyone help me on this? Thanks so much..