[BioC] Paired two-color design

[January Weiner]

Dear Gordon, thank you for your answer.

Gordon K Smyth wrote:
> I would analyse it like this:

That makes totally sense; however, I have one more question (sorry!
and thank you for your patience).

In the meanwhile, I have taken an alternative approach, as described
in the second part of the chapter on technical replicates in the limma
guide (http://bioconductor.org/packages/release/bioc/vignettes/limma/inst/doc/usersguide.pdf,
page 42): fit for each biological replicate separately, then create a
contrast corresponding to the average of these and subtract the
control:

design <- cbind(  ctrl= c( 1, -1, rep( 0, 6 ) ), e1= c( 0, 0, 1, -1,
rep( 0, 4 ) ), e2= c( rep( 0, 4 ), 1, -1, 0, 0 ), e3= c( rep( 0, 6 ),
1, -1 ) )
cmtx <- makeContrasts( "(e1+e2+e3)/3 - ctrl", levels= design )
fit <- lmFit( MA, design ) ; fit <- contrast.fit( fit, cmtx ) ; fit <-
eBayes( fit )

If I understand the text of the limma guide, these are alternative
approaches and should give at least similar results.

And yes, the estimated logFC are exactly the same. However, the
p-values are much different. Using duplicateCorrelation causes a bunch
of genes to become statistically non-significant (not the other way
round). Either duplicateCorrelation is less sensitive or more
specific, and I wonder which is the case. Unfortunately, this bunch of
genes changes the results of the functional analysis.

Also, maybe I'm lost, but after reading and thinking I don't see why I
can't use intraspotCorrelation here. I'm not saying I can, in fact
this gives me vastly different results I don't really trust (given the
later results of the functional analysis), but I just don't see the
problem, since the correlations are calculated within the arrays. I
got quite used to apply that, since often I'm confronted with the
following problem:

Cy3 Cy5
A0  B0
B0  A0
A1  B1
B1  A1

where the job is to compare A1 with A0 and B1 with B0. (the dye swaps
are technical replicates). I think that this is an unconnected design,
and there is no way of doing that with a normal model, so that the
channels should be analysed separately.

kind regards,

j.


-- 
-------- Dr. January Weiner 3 --------------------------------------