[BioC] LIMMA_Agilent

Gordon K Smyth smyth at wehi.EDU.AU
Thu Apr 24 03:50:23 CEST 2008



On Thu, 24 Apr 2008, Abhilash Venu wrote:

> Hi Gordon,
>
> I am a experimentalist, but not with great statistical knowledge and R
> experiance. Recently we started doing single color experiments using Agilent
> array.
> I think that we does not have any specific function to read the single
> channel data, But as once you suggested I used the dummy values for 'R' and
> 'Rb' and performed furhter normalization by the following commands.
>> txt_files <- dir(pattern=".txt")

This will read files in alphabetical order.  Will this agree with your 
design matrix?  You can specify the order of the files using a targets 
file.

>> RG<-read.maimages(txt_files, columns = list(G = "gMeanSignal", Gb =
> "gBGMeanSignal",
> R="gMedianSignal",Rb="gBGMedianSignal"),
> annotation= c("Row", "Col",
> "ProbeUID","ProbeName", "GeneName",))
>> Rgene<-backgroundCorrect(RG$G,method='normexp')

RG$G-RG$Gb would be more usual.

>> MA<-normalizeBetweenArrays(Rgene$G,method="scale")

method="quantile" would be more usual.

> Is this is fine?
>
> In this case I have three samples which are treated and the other three
> without treatment. I would like to get differentially expressed genes
> between the treated and untreated. In this scenario what should be the best
> way to create a desing matrix for my further analysis.

Same considerations apply as for any single-channel microarray.  See the 
User's Guide for Affymetrix data for example.

Best wishes
Gordon

> Is the following will
> be fine?
> design <- cbind(tx=c(1,1,0,0,0,ntx=c(0,0,1,1,1))
> Is there anything which I should specifically taken care of in these type of
> scenario?
>
> Thanks
> -- 
>
> Regards,
> Abhilash
> Graduate student
> Department of Molecular biology
> IOB



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