Dear R-users,

I want to analyse a single channel micro array experiment which looks like
the following:

> targets
  File cellline fenotype
1    A       1        R
2    B       2        R
3    C       3        R
4    D       1        S
5    E       2        S
6    F       3        S

There are three different cell lines, each of which comes in two versions.

Every cell line has  a variant that is resistant to a specific drug and
another variant that is sensitive to this drug.

We treated both variant of the three cell lines with this drug and then
extracted RNA which was then hybridised to a micro array.

The question we want to resolve is: which genes are differentially
regulated between resistant (R) and sensitive (S) versions of these cell
lines.

There is quite some biological variation between the cell lines, so
grouping them by fenotype and then searching for differentially regulated
genes would be a bad idea.

So, the idea is to to construct a model that accounts for this biological
variation between the cell lines and looks which genes are consistently  up
or down regulated between resistant and sensitive versions of these three
cell lines.

I am a bit puzzled on how to setup an appropriate design matrix for this
particular setup.

I have come up with the following code:
> design
  celline fenotR fenotS
1       1      1      0
2       2      1      0
3       3      1      0
4       1      0      1
5       2      0      1
6       3      0      1
attr(,"assign")
[1] 1 2 2
attr(,"contrasts")
attr(,"contrasts")$fenot
[1] "contr.treatment"

>block<-c(1,2,3,1,2,3)
>eset<-exprs(BSData.log2.quantile)
>cor<-duplicateCorrelation(eset, ndups=1, block=block, design=design)
>fit <- lmFit(eset, design, block=block, cor=cor$consensus)
>fit<- eBayes(fit)
>cont.matrix<-makeContrasts(resvssens= fenotR - fenotS, levels=design)
>fit2<-contrasts.fit(fit,cont.matrix)
>fit2<-eBayes(fit2)
>topTable(fit2)

However, this code results in an adj.p-value that is "0.9999541" for every
gene.

Is there a better way to analyse this?

Kind regards,
Steven

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