[BioC] how to merge replicate spots?

[michael watson (IAH-C)]

If I were doing this, I would use the aggregate function to calculate the mean for each of my genes, and then pass this averaged data as a matrix to lmFit.
 
There shouldn't be too many problems.
 
Why don't you post your full code and any errors?

________________________________

From: bioconductor-bounces at stat.math.ethz.ch on behalf of Barbara Cegielska
Sent: Fri 03/07/2009 8:13 AM
To: bioconductor at stat.math.ethz.ch; r-help-bounces at r-project.org
Subject: [BioC] how to merge replicate spots?



Dear R-Users,

I use home-made spotted arrays and every probe is printed in triplicate. I normalized my data using limma package and I got mean from these three replicates by using duplicateCorrelation function:


design<-modelMatrix(targets, ref="HL60")
duplicateCorrelation(MAl.pAq, design, ndups=3,spacing=1)
corfit <- duplicateCorrelation(MAl.pAq, ndups=3, spacing=1, design)
all.correlations <- tanh(corfit$atanh.correlations)
fit <- lmFit(MAl.pAq, design, ndups=3, spacing=1, correlation=corfit$consensus)
contrast.matrix<-makeContrasts(AML.M2-K,levels=design)
fit2<-contrasts.fit(fit,contrast.matrix)
fit2<-eBayes(fit2)
topTable(fit2,adjust="BH")

However, this function does not change object dimmensions (plot shows all spots, not only mean from all replicates), so I try to use avedups function (a<-avedups(MA.normAq, ndups=3, spacing=1, weights=NULL)), but I have problem with creating fit2, because of differences in dimmentions. I would like to get a topTable object. What shall I do??

Regards,

Barbara Cegielska

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