Dear all,

 

We have some arrays in which a large proportion of the spots are expected to
be differentially expressed.  I would therefore like to normalize using some
control spots that we put on the array.

 

I tried up-weighting these spots, as per an example in the Limma users
guide.  However, when I perform the normalization it pushes all of the spots
to have M values extremely close to zero.  Am I doing something wrong?
When I look at the MAplot before normalization (even after loess) the
control spots have a slightly negative M (-0.5).  

 

See my script below.

 

Thanks

 

>>>>>>>>>>>>>>>>>>>>>> 

library(limma)

targets<-readTargets("VCMeOHTargets.txt")

RG<-read.maimages(targets$FileName,source='genepix',wt.fun=wtflags(0.1))

RG$genes<-readGAL("Array2(Gal)2008NonDhc.gal")

spottypes<-readSpotTypes("SpotTypes.txt")

RG<-backgroundCorrect(RG,method="normexp")

RG$genes$Status<-controlStatus(spottypes,RG)

w<-modifyWeights(array(1,dim(RG)),RG$genes$Status,c("All","Control"),c(0,2))

MAwi<-normalizeWithinArrays(RG,weights=w)

MAwibtw<-normalizeBetweenArrays(MAwi,method='Aquantile')

design<-c(1,1,-1,-1,1,-1)

fit<-lmFit(MAwibtw,design)

fit<-eBayes(fit)

VCMeOHTop<-topTable(fit,number=10000)

write.table(VCMeOHTop, file="VCMeOHTopnormControlAq.txt",sep="\t") 

plotMA(fit)

 

******************************************
Alison S. Waller  M.A.Sc.
Doctoral Candidate
alison.waller@utoronto.ca <mailto:alison.waller@chem-eng.utoronto.ca> 
416-978-4222 (lab)
Department of Chemical Engineering
Wallberg Building
200 College st.
Toronto, ON
M5S 3E5

  

 


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