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);

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