[BioC] Combining old Affy arrays for limma

[James Perkins]

Apologies if this topic has already come up (I suspect it has!), I did 
try searching the mailing list but to no avail;

I am combining some old affy datasets from 2002, which I have obtained 
via GEO. They are of the "Gene Expression Data Matrix" format; i.e. each 
array has been background processed, summarised etc. However no 
differential expression has been undertaken.

The datasets are of the "RGU-34" type, so there are 3 arrays with 8,000 
features, RGU34A, RGU34B and RGU34C respectively. I want to combine this 
data with some more recent data from RAT2302 arrays. I understand I can 
combine the identifiers using some spreadsheets downloaded from the 
affymetrix website.

However my problem is how I work out differential expression for 
comparison. Is it correct to combine the Gene Expression Data matrices 
for A B and C to make big esets of (8,000 * 3 =) 24,000 identifiers, and 
then use these in Limma to work out differential expression? Or would it 
be better to treat the arrays separately, then combine the results, 
ordering by p-value.

The reason I want to combine the 3 RGU arrays is because I wish to 
(amongst other things) perform category analysis to make a comparison 
between the old data and the new data.

Any information on the best way to combine these arrays would be much 
appreciated.

Kindest regards,

James Perkins