[BioC] quantile normalization of one dataset to another
Ben Bolstad
bmb at bmbolstad.com
Wed May 23 02:30:54 CEST 2007
Ignoring the wisdom, or otherwise, of seeking to do a normalization like
this there is code for doing this using affyPLM. The following code
implements a quantile normalization procedure which determines a target
distribution from one dataset and applies it to another:
library(affyPLM)
X.to.determine.normalization <- matrix(rnorm(1000),100,10)
Y.to.normalize <- matrix(rexp(10000),1000,10)
target <- normalize.quantiles.determine.target(X.to.determine.normalization,1000)
Y.normalized <- normalize.quantiles.use.target(Y.to.normalize,target)
boxplot(as.data.frame(X.to.determine.normalization))
boxplot(as.data.frame(Y.to.normalize))
boxplot(as.data.frame(Y.normalized))
On Tue, 2007-05-22 at 15:17 +0100, 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
>
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