[BioC] Am I using limma incorrectly?

[michael watson (IAH-C)]

I have a data set which pretty much duplicates the experimental design
of one of the limma examples, so I am using that with great results :-D

There is one difference though - the limma example has no duplicate
spots, whereas my design does.  So I did two runs of limma, one to find
differentially expressed spots, the other to find differentially
expressed genes (I assume limma would take the duplicates into question
and do some averaging).

The code I used was almost identical.  For the spots:

> design <- c(1,-1,1,-1)
> fit <- lmFit(MAptnorm, design)
> fit <- eBayes(fit)
> topTable(fit,number=10,adjust="fdr")

And for the genes:

> design <- c(1,-1,1,-1)
> fit <- lmFit(MAptnorm, design, ndups=2)
> fit <- eBayes(fit)
> topTable(fit,number=10,adjust="fdr")

Note the only difference is the "ndups=2" bit.  Now, for differentially
regulated spots, I was lucky, lots of spots came up and mostly the two
duplicates were side by side.  One gene's duplicate spots were first and
third in the top ten with M values of -5.4 - result!

Now, when I did the second run, with "ndups=2", the results changed
completely.  Something must have gone wrong, my top gene has an M value
of -0.8, it's not the same gene as before, and more's the point,
topTable still lists BOTH duplicate spots.

My only conclusion from this is that I am using limma incorrectly.
But... How?

Mick