[BioC] Unequally spaced replicates in limma

[Elizabeth Brooke-Powell]

Hi Gordon,

Is the solution of sorting the table available in LimmaGUI? Should I resort
the input files to get the replicates taken into account using ndups=2 and
spacing=1? What happens to the replicates if you have no spot weighting, are
they just averaged? 

Thank you for your help,

Liz

------------------------------
Date: Thu, 02 Sep 2004 19:44:34 +1000
From: Gordon Smyth <smyth at wehi.edu.au>
Subject: RE: [BioC] Unequally spaced replicates in limma
To: "michael watson (IAH-C)" <michael.watson at bbsrc.ac.uk>
Cc: bioconductor at stat.math.ethz.ch
Message-ID: <6.0.1.1.1.20040902193610.02984088 at imaphost.wehi.edu.au>
Content-Type: text/plain; charset="us-ascii"; format=flowed

At 07:23 PM 2/09/2004, michael watson (IAH-C) wrote:
>Thanks Gordon
>
>Actually when I did this, I got some odd results.

The results look to me as you would hope for and expect.

>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..?

1. You've reduced the number of genes by half, hence you do only half the 
adjustment for multiple testing, hence you end up with lower p-values.

2. You'd certainly hope that averages are more tightly distributed than the 
individual spots, that's why averaging is a good thing.

If your genes are virtually all in duplicate, and the others have an even 
number of reps, you could sort your MA object by gene ID and then use 
duplicateCorrelation() with ndups=2 and spacing=1.

Gordon

>Cheers
>Mick
>