[BioC] limma_analysis result

[Mark Cowley]

Hi Abhilash,
Your code looks good, except that usually you will want to normalise  
log transformed data. thus try:
> MA<-normalizeBetweenArrays( log2(Rgene$G), method="quantile")

If your logFC ratios still look very high, then try convincing  
yourself of their accuracy by looking at the raw data (RG$R) for some  
of the most differentially expressed genes, and also plot the  
expression values for some of these DE genes.

good luck,
Mark
Peter Wills Bioinformatics Centre
Garvan Institute of Medical Research


On 17/06/2008, at 1:17 AM, Abhilash Venu wrote:

> Hi list,
>
> I am still wonder about the data, which I analyzed by the limma. I  
> accept
> that  I am a biology graduate student, and in the learning stage. I am
> analyzing the single color data, which had been generated by Agilent  
> 4x44k
> platform. With the help of mailing list and limma users guide, I  
> have done
> the following analysis. But logFC gives very high values like 320,  
> 1320 etc.
> I don't know how really the fitting is happening. Can I rely on this  
> result.
> How should I go about it.
> #Reading the data.
>
>> RG<-read.maimages(txt_files, columns = list(G = "gMeanSignal", Gb =
>>
> "gBGMeanSignal",
> R="gMedianSignal",Rb="gBGMedian
>>
>> Signal"),
>> annotation= c("Row", "Col",
>> "ProbeUID","ProbeName", "GeneName",))
>
>
> Rgene<-backgroundCorrect(RG,method='subtract')
>
> #Considering only G as it is single color experiment.
> MA<-normalizeBetweenArrays(Rgene$G,method="quantile")
>
> design <- cbind(norm=1,normvstest=c(1,1,1,1,0,0,0,0))
> fit <- lmFit(MA, design)
> fit <- eBayes(fit)
> topTable(fit, coef="normvstest", adjust="fdr")
> -- 
>
> Regards,
> Abhilash
>
> 	[[alternative HTML version deleted]]
>
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----------------------------------------------------------------------
Mark Cowley, BSc (Bioinformatics)(Hons)

Peter Wills Bioinformatics Centre
Garvan Institute of Medical Research
384 Victoria St 				Tel:  +61 2 9295 8542
Darlinghurst, NSW 2010		Fax:  +61 2 9295 8538
Australia 					email: m.cowley at garvan.org.au
www.garvan.org.au