On Thu, Nov 6, 2008 at 1:56 PM, Rainer Tischler <rainer_t62@yahoo.de> wrote:

> Hi,
>
> I have a microarray data set with additional information on the chromosomal
> location of genes and their GO-groups. I'm looking for a simple way to
> include this annotation data in a supervised microarray analysis (disease
> outcome classification) to improve the prediction accuracy. There appear to
> be two basic strategies:
>
> 1. combine similar genes to gene groups based on the annotation data before
> starting the statistical analysis
> 2. improve the distance measure for feature selection and classification by
> including distance information derived from the annotation data
>
> Is anybody aware of an R-package that implements one of these ideas or is
> there a simply way I could implement this myself (e.g. replacing gene groups
> by a single gene based on the mean or median expression levels - I'm not
> sure whether this would be effective or whether more sophisticated methods
> are already available as R-packages)?
> Currently, I'm using an SVM- and a PAM-classifier for my predictions, thus,
> I hope to find an integrative approach which is compatible with these
> classifiers.
>

Check PGSEA or globaltest; there are likely others.

Sean

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