[BioC] Data analysis

[Jason Skelton]

Hi

I have a question about data analysis after normalisation
I have normalised in limma and applied the generalized least squares 
linear models to my data with very nice results!

My experiment is a Three sample experiment
(Three different treatments)compared to a commmon reference.
The Three samples have six slides per experiment, 3 in one dye 
orientation and 3 dye swapped to give 18 slides in total.
I have approx 3500 genes in duplicate on my array at present.

Currently I have normalised all three sets of data seperately but would 
like to be able to compare the three data sets.
I was thinking of using the mva functions like dist/hclust etc.

My questions:
Is this the best way of comparing this data or are there other/better 
methods that could be used that anyone has had experience with.

e.g. similar to the two-sample experiment example in limma user guide
where results from the  linear model and ebayes are displayed with a 
heatmap ?
(sorry I'm presuming that this is the kind of thing I should be doing ?)

Also I'm presuming the data I want to use for these methods are the 
normalised $M values ? OR do I want to use the results from 
gls.series/lm.series and ebayes for a 3 sample comparison ?

please could someone give me an example of the best method they 
recommend with some commands that I could try using...

Thanks very much to anyone who can help

Jason


-- 
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Jason Skelton
Pathogen Microarrays
Wellcome Trust Sanger Institute
Hinxton
Cambridge
CB10 1SA

Tel +44(0)1223 834244 Ext 7123
Fax +44(0)1223 494919