Hello! Recently, we performed a study using Agilent's single color, 40K mouse arrays but the follow-up experiments were performed using Agilent's newer 60K mouse arrays. I checked and these arrays only share about 12,000 probes. I want to compare the intensities from the 60K array to the 40K array but am not sure how to properly normalize and background correct the data. Has anyone attempted this before and have some advice to offer on the subject? My strategy now is pasted below. Thank you in advanced! Jason # Load the 60K array data G_60 <- read.maimages(targets_60,path="../data/",source="agilent.median", green.only=T); G_60 <- backgroundCorrect(G_60, method="normexp", offset=1); # Load the 40K array data G_40 <- read.maimages(targets_40,path="../../Microarray Data/Data/Rename Files/",source="agilent.median", green.only=T); G_40 <- backgroundCorrect(G_40, method="normexp", offset=1); # Combine Data and keep probes common to both arrays. This only selects the first instances of probe i from the 40K array in the 60K array idx<- match(G_40$genes$ProbeName,G_60$genes$ProbeName); Expr<-cbind(G_40$E[!is.na(idx),],G_60$E[idx[!is.na(idx)],]) genes<-cbind(G_60$genes[idx[!is.na(idx)],]) G<-G_40; G$E<-Expr; G$genes<-genes; G$targets<-targets; G <- normalizeBetweenArrays(G, method="quantile"); G <- avereps(G, ID=G$genes$ProbeName); [[alternative HTML version deleted]]