[BioC] quantile normalization

[Laurent Gautier]

On Tue, Jun 03, 2003 at 05:54:47PM +0100, Martino Barenco wrote:
> Hi,
> 
> My understanding of quantile normalization is that values for several 
> data sets are ranked, then the average per rank is taken and is 
> reattributed to each data set according to the original rank (hope this 
> makes sense). My question is: how does one deal when ties occur?
> - One possibility would be to force a tied value to be greater than the 
> other (using the "order" command instead of "rank"). Even though it 
> would not make a huge difference it is a bit arbitrary.
> - Another possibility is to "force" the ties across all data sets, 
> quite arbitrary as well.
> - or maybe a combination of both, but it looks like a nightmare to 
> program!

I am not too sure either about the practical importance
for real life data (althought ties should be around for Affymetrix chips
-- chips like U95 have roughly 400 kiloprobes and the intensity range
is often [0.0, 30000.0] with a large number of low intensities). 
(note: the package affy has more than one 'quantiles-based' normalization
method; by alphabetic order: "qspline", "quantiles", "quantiles.robust")


> 
> So, what should be done? Also, is there a method such as "normalize" 
> that acts on exprSet rather than AffyBatch?

Not yet (but long running thoughts about unifying normalization methods
had a ray of hope, very recently)... In the meanwhile, you can hack your
own in a wink (look at the vignette 'affy: custom processing methods').
 
> 
> Thanks
> 
> Martino
> ---------------------------------------
> Martino Barenco
> CoMPLEX
> 4, Stephenson Way
> London NW1 2HE
> Tel.: +44 20 7679 5088
> Fax.: +44 20 7383 5519
> Email: m.barenco at ucl.ac.uk
> 
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Laurent Gautier			CBS, Building 208, DTU
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