[BioC] chips A,B and C

[Park, Richard]

Hi Nicolas, 
Yes, I agree with Jim, since the 3 chips are testing different sets of genes, it is not necessarily that important to normalize everything together, since expression values in microarrray's are relative. But I can see the need of normalizing everything together if you are trying to link pathways and gene information from all 3 types of mouse chips together? Or trying to perform some sort of clustering or linkage analysis with all of the information? 

The simplest thing is probably performing rma on each chip separately, b/c of how the functions are dealt with in bioconductor and conduct analysis on each of set of chips. But if you really wanted to see everything together, you could probably get the expression values out of rma (you can play w/ the settings of rma) and then after you have the expression values for each probe you can then combine the sets of a,b,and c and then perform a normalization technique to make the different sets comparable. 

HTH, 
Richard Park 


-----Original Message-----
From: Antille,Nicolas,LAUSANNE,NRC-BAS
[mailto:nicolas.antille at rdls.nestle.com]
Sent: Monday, June 16, 2003 8:39 AM
To: 'bioconductor at stat.math.ethz.ch'
Subject: [BioC] chips A,B and C


I'm currently working on an experiment involving chips MG_U74Av2,
MG_U74Bv2 and MG_U74Cv2. The RMA normalization treats every
types of chips separately (only one .CDF file is required). Thus, I
need to perform RMA three times and the result is certainly  
different from the one I would obtained performing RMA on all
data simultaneously (especially for quantile normalization).

Has someone already meet this problem? Are the results between
the two methodolgies very different? More generally, do we observe
differences between chips A, B and C (expression level, variability,...)?

Thank you very much for your response!

Regards

Nicolas

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