[BioC] Aquantile normalization & transcriptional activity

Gordon Smyth smyth at wehi.edu.au
Sat Mar 12 12:14:43 CET 2005

>Date: Fri, 11 Mar 2005 18:41:52 -0800
>From: Federico Scossa <fscossa at pw.usda.gov>
>Subject: [BioC] Aquantile normalization & transcriptional activity
>To: fscossa at pw.usda.gov
>Cc: bioconductor at stat.math.ethz.ch
>Hi all,
>I have a concern about using Aquantile normalization (limma) in my
>experiment. I hope someone can help me and clarify the issue.... I have
>several timepoints... in particular one of them, as expected, shows a
>global, low trascriptional activity (the tissue at this timepoint is close
>to the "drying stage", so most of the genes are not expressed)...
>so if I apply Aquantile normalization I am going to modify the channel
>densities, so that they can overlap. and this is necessary, as far as I
>understand, because it makes the between-timepoints comparisons possible
>(my design is unconnected). but, in this way, am I introducing some
>artifacts in my low-expression timepoints? I mean, I am forcing  the
>channel intensities to have all the same distribution... but which is the
>assumption of Aquantile ? should the single channel intensities be roughly
>the same before normalization?

You are correct in your suspicion. If one of your samples is expected to 
show systematically lower expression over the whole genome, then the basic 
assumptions behind quantile normalization is invalidated. Your options in 
such a situation are limited. Depending on what is printed on your arrays, 
you could normalize on a subset of control spots which should have nearly 
constant expression. You are going to need some sort of boutique normalization.


>thank you ! any help welcome !

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