[BioC] RMA verse GCRMA

[Wolfgang Huber]

Hi Fangxin,

do you expect that 100% of the genes that are assayed by your chips are 
expressed all the time in the system you are investigating? (you never 
told us which chips and which plant or animal)

And if not - say if only 50% of genes are expressed, then the data for 
the remaining 50% should just be pure noise and there is no reason why 
intensities from RMA and GCRMA should be correlated.

I think you have just learned something about your measurement 
instrument (and this has little to do with normalization methods).

   Best wishes
   Wolfgang

Fangxin Hong wrote:
> Hi list;
> I met a strange problem regarding the normalization methods,
> 
> For an experiment with 24 arrays (time order), I normalized the data by
> both RMA and GCRMA. Then I tested the correlation between the normalized
> data for each gene. Surprisingly, I found that about 25% genes with
> correlation less than 0.7 between value normalized by RMA and GCRMA, and
> only less than 50% genes have correlation >0.9. I studies the profile of
> some genes, they look quite different under two methods.
> 
> 
> Anybody met this problem before?  Which method we should trust? Any
> comments/idea is appreciated. Or is it possible that I did something
> wrong, I couldn't find it myself.


-------------------------------------
Wolfgang Huber
European Bioinformatics Institute
European Molecular Biology Laboratory
Cambridge CB10 1SD
England
Phone: +44 1223 494642
Fax:   +44 1223 494486
Http:  www.ebi.ac.uk/huber