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Bioinformatics Advance Access published online on January 27, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti292
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Bioinformatics © Oxford University Press 2005; all rights reserved.
Received September 8, 2004
Revised December 16, 2004
Accepted January 25, 2005

Article

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

Claudio Lottaz 1* and Rainer Spang 1

1 Max Planck Institute for Molecular Genetics, Ihnestr. 73, D-14195 Berlin (Germany); Berlin Center for Genome Based Bioinformatics, Ihnestr. 73, D-14195 Berlin (Germany)

* To whom correspondence should be addressed.
Claudio Lottaz, E-mail: Claudio.Lottaz{at}molgen.mpg.de


  Abstract

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 that 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 sub-entities and associate them to biological processes without compromising overall prediction accuracy.

Availability: Bioconductor compliant R package.

Supplementary data: Complete analyses are available at http://compdiag.molgen.mpg.de/supplements/stam1.


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