[BioC] Seeking help to remove control spots in single channel normalization
yee.leon at gmail.com
Mon Jan 5 14:06:54 CET 2009
Prashantha Hebbar Kiradi [MU-MLSC] wrote:
> Dear Friends,
> I am working on single channel normalization for Agilent 244K chip data using Limma package. I refered the communication happend between Gordon and Abhilash about single channel normalization. I able perform it. But, not able to get the gene list soon after the normalization as we get in dual channel analysis.
> I am able to get the gene list in topTable stage. But I do not want gene list at the end of the analysis. Because I want remove the control spots soon after the normalization as we do for dual color.
> Following are the steps which I followed to perform single channel normalization,
>> RG<-read.maimages(target$FileName, source="agilent", path="/home/mlscrh2/PrakrathiData", columns = list(G="gMeanSignal", Gb="gBGMeanSignal",R="gMedianSignal",Rb="gBGMedianSignal"),annotation= c("Row", "Col", "ProbeUID","ProbeName", "GeneName"))
>> MA.q <- normalizeBetweenArrays(Ggene, method="quantile")
>> design = c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1)
>> fit = lmFit(MA.q,design)> ebFit <- eBayes(fit)
>> a <- topTable(ebFit,genelist = RG$genes,adjust="fdr",n=300000)
> I tried to incorporate genelist in the stage of background correction and normalization, but ends up with an error.
> So can you please suggest me, How to remove control spots soon after normalization in single channel analysis?
The Feature Extraction file of Agilent array will contain a column
called "ControlType", so if you use read.maimages with
annotation= c("Row", "Col", "ProbeUID","ProbeName", "GeneName",
"ControlType"), you can filter out the control spots by "ControlType":
0 means non-control.
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