[BioC] RMA and quantile normalisation
Rafael A. Irizarry
ririzarr at jhsph.edu
Wed Mar 3 16:45:30 MET 2004
from the data i have looked at they are in general not normal. i would
not expect them to be.
there are various reasons to take the log. but to make the
within chip distibution normal is not one of them.
what is close to normal is the distribution of RMA
expression measures of a particular gene across many chips. in your
example:
hist(exprs(eset.rma[10,])
but you'll need 30 or more arrays to see it.
On Wed, 3 Mar 2004 Arne.Muller at aventis.com wrote:
> Sorry, my last posting was incomplete (slipped over the keyboard ...).
>
> I meant that I haven't explored other methods yet, but since the RMA values
> are log2, I thought that I'd get something close to a normal distribution.
> Comapred to a normal distribution I get many low intensity probe sets.
>
> The values are generated like this:
>
> eset.rma <- expresso(cel, bgcorrect.method="rma",
> normalize.method="quantiles", pmcorrect.method="pmonly",
> summary.method="medianpolish")
>
> then:
> hist(exprs(eset.rma[,10]))
>
> kind regards,
>
> Arne
>
> --
> Arne Muller, Ph.D.
> Toxicogenomics, Aventis Pharma
> arne dot muller domain=aventis com
>
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