Dear Rainer, have a look at Claudio Lottaz's stam package: Description: The stam package performs a biologically structured classification of microarray profiles according to clinical phenotypes. GO terms are used to link classification results to biological aspects. We call biologically focused signatures corresponding to these class predictions molecular symptoms. Thus, stam allows for molecular stratification of patients with complex phenotypes according to presence/absence patterns of molecular symptoms. Best wishes Wolfgang -- ---------------------------------------------------- Wolfgang Huber, EMBL-EBI, http://www.ebi.ac.uk/huber Sean Davis ha scritto: > On Thu, Nov 6, 2008 at 1:56 PM, Rainer Tischler <rainer_t62 at="" 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 > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor