[BioC] Seeking help to remove control spots in single channel normalization

Jenny Drnevich drnevich at illinois.edu
Thu Jan 8 15:38:18 CET 2009


Hi Prashantha,

>Ggene<-backgroundCorrect(RG$G,method='normexp')    #I referred this command
>in mail list
>
>Ggene variable will not have RG$genes information (i.e. gene list info). If
>I get RG$genes information in next steps (after inter array normalization)
>then only it is possible to remove control spots.
>
>So, now my question is If I use directly RG in my background correction (for
>example: Ggene<-backgroundCorrect(RG,method='normexp')), will it create any
>problem? In this case, RG$G-RG$Gb and RG$R-RG$Rb will be done right? So,
>analysis is meaningful right?

If you give backgroundCorrect() only RG$G, it doesn't have RG$Gb for 
the background correction at all; I don't remember all of the details 
of the normexp method, but I thought it did use the background 
values. If so, your command is not doing what you thought it would be 
doing. The backgroundCorrect() function was meant to directly work on 
RGList objects, so I'm not sure why you thought it might not work 
correctly if you give it RG.

HTH,
Jenny


>If you make me clear in this I think I will not have any further problem in
>removing Control spots after inter array normalization. Sorry for making you
>to write me again.
>
>Regards,
>
>Prashantha
>
>-----Original Message-----
>From: Leon Yee [mailto:yee.leon at gmail.com]
>Sent: Monday, January 05, 2009 6:37 PM
>To: Prashantha Hebbar Kiradi [MU-MLSC]
>Cc: bioconductor at stat.math.ethz.ch
>Subject: Re: [BioC] Seeking help to remove control spots in single channel
>normalization
>
>Hi,
>
>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,
> >> library(limma)
> >> target<-readTargets("/home/mlscrh2/MData/target.txt")
> >> RG<-read.maimages(target$FileName, source="agilent",
>path="/home/mlscrh2/PrakrathiData", columns = list(G="gMeanSignal",
>Gb="gBGMeanSignal",R="gMedianSignal",Rb="gBGMedianSignal"),annotation=
>c("Row", "Col", "ProbeUID","ProbeName", "GeneName"))
> >> Ggene<-backgroundCorrect(RG$G,method='normexp')
> >> 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.
>
>HTH
>
>Leon
>
>
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Jenny Drnevich, Ph.D.

Functional Genomics Bioinformatics Specialist
W.M. Keck Center for Comparative and Functional Genomics
Roy J. Carver Biotechnology Center
University of Illinois, Urbana-Champaign

330 ERML
1201 W. Gregory Dr.
Urbana, IL 61801
USA

ph: 217-244-7355
fax: 217-265-5066
e-mail: drnevich at illinois.edu



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