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Bioinformatics Advance Access originally published online on January 27, 2005
Bioinformatics 2005 21(9):1971-1978; doi:10.1093/bioinformatics/bti292
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© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oupjournals.org

Molecular decomposition of complex clinical phenotypes using biologically structured analysis of microarray data

Claudio Lottaz * and Rainer Spang

Max Planck Institute for Molecular Genetics and Berlin Center for Genome Based Bioinformatics Ihnestrasse 73, D-14195 Berlin, Germany

*To whom correspondence should be addressed.

Motivation: Today, the characterization of clinical phenotypes by gene-expression patterns is widely used in clinical research. If the investigated phenotype is complex from the molecular point of view, new challanges arise and these have not been adressed systematically. For instance, the same clinical phenotype can be caused by various molecular disorders, such that one observes different characteristic expression patterns in different patients.

Results: In this paper we describe a novel algorithm called Structured Analysis of Microarrays (StAM), which accounts for molecular heterogeneity of complex clinical phenotypes. Our algorithm goes beyond established methodology in several aspects: in addition to the expression data, it exploits functional annotations from the Gene Ontology database to build biologically focussed classifiers. These are used to uncover potential molecular disease subentities and associate them to biological processes without compromising overall prediction accuracy.

Availability: Bioconductor compliant R package

Contact: Claudio.Lottaz{at}molgen.mpg.de

Supplementary information: Complete analyses are available at http://compdiag.molgen.mpg.de/supplements/lottaz05


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