[BioC] Unequally spaced replicates in limma

[michael watson (IAH-C)]

Thanks Gordon

Actually when I did this, I got some odd results.

If I ran lmFit(), eBayes() and topTable() on my data set on a per-spot
basis, I found ~800 SPOTS with a p-value <= 0.05.  Now most of my genes
are replicated in duplicate on the arrays (within-array replicates) and
when I averaged over those replicates, and used that data to feed into
lmFit(), eBayes() and topTable() I got ~1100 GENES with a p-value
<=0.05.  

Does this suggest that after averaging over replicate spots, the
measurements for my genes are more tightly distributed than the
individual spots were..?

Cheers
Mick

-----Original Message-----
From: Gordon K Smyth [mailto:smyth at wehi.EDU.AU] 
Sent: 01 September 2004 23:12
To: michael watson (IAH-C)
Cc: bioconductor at stat.math.ethz.ch
Subject: Re: [BioC] Unequally spaced replicates in limma


> Hi
>
> As I have varying numbers of replicates, and they are not regularly 
> spaced on the array, and given that I would like a list of 
> differentially expressed genes which is averaged over replicates,

I assume that these are within-array replicates.

> I
> assume the best thing to do is normalise my data, and then average 
> over replicates in the MAList object, and then pass the averaged data 
> to
> lmFit() etc?

Yes, you could do that.  It does raise subtle issues though concerning
how the variance of the averages depends on the number of replicates.
You might like to compute weights based on the number of replicates for
each probe and pass that to lmFit also.

Gordon

> Is that right?
>
> Cheers
> Mick