normalization on microarray
Can someone help me on normalization of microarray. My output before using a limma packages are below. However, I don't know how to perform using normalizeWithinArrays() if the class of the data is a matrix format. Also, what command I should use to find out how many genes going up in siMLL2 at padj < 0.1 and abs(logFC)>1?
> head(selExpr,5)
GSM921888 GSM921889 GSM921890 GSM921891
OR4F17 24.3536 24.6945 18.6882 20.6363
LOC100134822 2004.2300 1959.5600 1590.9400 1534.8100
OR4F29 40.3611 42.6291 48.8858 32.3297
LOC100287934 286.6540 253.0200 320.1410 275.0030
FAM87A 172.6980 182.9510 210.9790 226.7940
samples <- as.factor(c("scr", "scr", "siMLL2", "siMLL2")) #convert into factors
design<-model.matrix(~0+samples) #set up the experimental design
colnames(design)<-levels(samples)
fit<-lmFit(selExpr,design)
contrast.matrix<-makeContrasts(siMLL2 - scr, levels=design)
fits<-contrasts.fit(fit,contrast.matrix)
ebfit<-eBayes(fits)
topTable(ebfit,number=50,coef=1)
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Those values are already normalized. You can even analyze them directly from GEO (click on the GEO2R link on GEO), which can also show you the script it uses. Anyway, just download the .CEL files if you want to analyze things yourself. You have MUCH better control of things that way.
Thanks Ryan. How do I know if the data is already normalized? Do you know if there is a command after
I'm guessing that you downloaded the series matrix file and clicking on one of the individual samples would show you that the values are already normalized (it explicitly says that). topTable returns a dataframe, so just
with(tt, which(padj<0.1 & abs(logFC)>1))wherettis the output from topTable.