[BioC] limma and paired data

[SKALKO at clinic.ub.es]

Dear all,

 

I have a question on a subject that I think was not discussed here
before. 

I am using limma package for the detection of significant differential
expression in an affy experiment:

 

3 "Healthy" (group1) indiv. before treatment and the same indiv. after
treatment (group4)

3 "ill-low"   (group2)    "                "           "
"           "                  (group 5)

2 "ill-high"  (group3)   "                 "           "
"           "                  (group 6)

 

the interest is comparing effects of the treatment (i.e. group4-group1,
group5-group2, etc). I used these commands:

 

>library(affy)

>library(limma)

>library("hgu133a")

>x<-ReadAffy()

 

>eset<-rma(x)

>design <- model.matrix(~ -1+factor(c(1,1,1,2,2,2,3,3,4,4,4,5,5,5,6,6)))

>colnames(design) <-
c("group1","group2","group3","group4","group5","group6")

 

>fit<-lmFit(eset,design)

 

>contrast.matrix <-
makeContrasts(group2-group1,group4-group1,group5-group2,
group6-group3,levels=design)

 

>fit2 <- contrasts.fit(fit, contrast.matrix)

>fit2 <- eBayes(fit2)

 

The question is:  How has to be taken into account that the individuals
are the same before and after the treatment? 

I red about block in lmFit but I am not sure how to do that. Here it
would be some correlation, but no so high as

in the case of  real technical replicates. 

 

Thanking you in advance,

Susana Kalko

 

 


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