[BioC] Normalization Strategies for Cross-species Comparisons

Wolfgang Huber huber at ebi.ac.uk
Fri Jan 27 19:39:35 CET 2006

Hi John,

I think the best would be joint statistical model (eg linear model on 
log intensities) that incorporates both the usual normalization effect, 
the species effect, the chiptype effect, and whatever biological effect 
you might be looking for.

If you can't do that, I'd try both: gcRMA to normalize the entire 
collection of arrays as a single set; apply gc RMA separately to
each set of chips. After appropriate subsequent analysis for diff. 
expressed genes, the results shoulnd't differ much.

There are some further thoughts about this here: 

  Best wishes

Cornell, John E wrote:
> Hi Folks:
> We have affy chips from human tissues (hgu133A chip) and tissues from a
> mouse model (MOE403A chip).  The objective of this experiment is to
> compare expression levels across species.  My primary question for the
> group is, "What is the best strategy for normalizing the arrays?"
> Should we use gc RMA to normalize the entire collection of arrays (human
> and mouse) as a single set; or, should we apply gc RMA separately to
> each set of chips?  What do you suggest?
> Cheers,
> John E. Cornell, Ph.D.
> Associate Professor
> Center for Epidemiology and Biostatistics
> 	[[alternative HTML version deleted]]
> _______________________________________________
> Bioconductor mailing list
> Bioconductor at stat.math.ethz.ch
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Best regards

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

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