[BioC] quantile normalization of one dataset to another

Claus-Dieter Mayer claus at bioss.ac.uk
Tue May 22 18:22:00 CEST 2007

Hi Daniel!

Even if you had managed to apply a quantile normalization I doubt that 
it would have really solved your problem. Cominbining micorarray results 
from different studies (even if the same platform is used) is a tricky 
thing. A recent publication on this is

<http://www.biomedcentral.com/1471-2105/8/80> Bayesian meta-analysis 
models for microarray data: a comparative study
Erin M Conlon, Joon J Song, Anna Liu
BMC Bioinformatics 2007, 8:80

Hope this helps


Daniel Brewer wrote:
> Just found another complicating factor.  Even though both sets are from
> Affymetrix arrays they are from different types and so have different
> numbers of probes.  Therefore quantile normalisation may not be the way
> forward.  Are there any other cross array normalisation techniques which
> would be suitable, whilst still retaining that one dataset is left
> untouched?
> Dan
> Benilton Carvalho wrote:
>> Assuming that the second dataset is quantile normalized and that its
>> expression matrix is called "expression2", what you want to do is:
>> ref <- sort(expression2[,1])  ## if it is quantile normalized, every
>> column has the same distribution
>> for (i in 1:ncol(expression1))
>>   expression1[order(expression1[,i]),i] <- ref
>> b
>> On May 22, 2007, at 10:17 AM, Daniel Brewer wrote:
>>> Hi,
>>> I have two different datasets which are both originally from the
>>> Affymetrix platform but now I only have the expression matrix.  Both
>>> datasets have an overall different distribution of expression.  What I
>>> would like to do is quantile normalisation on each of the experiments in
>>> one dataset to the quantile curve of the other dataset i.e. I want to
>>> leave the second dataset untouched, but normalise the first to it.  ANy
>>> ideas how to do this?  I looked at normalize.quantiles but it does not
>>> appear to do what I want.
>>> Thanks
>>> Dan
>> -- 
>> Benilton Carvalho
>> PhD Candidate
>> Department of Biostatistics
>> Bloomberg School of Public Health
>> Johns Hopkins University
>> bcarvalh at jhsph.edu

 Dr Claus-D. Mayer                    | http://www.bioss.ac.uk
 Biomathematics & Statistics Scotland | email: claus at bioss.ac.uk
 Rowett Research Institute            | Telephone: +44 (0) 1224 716652
 Aberdeen AB21 9SB, Scotland, UK.     | Fax: +44 (0) 1224 715349

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