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Threshold-free high-power methods for the ontological analysis of genome-wide gene-expression studies

Björn Nilsson1 email, Petra Håkansson1,2 email, Mikael Johansson2 email, Sven Nelander3 email and Thoas Fioretos1 email

1Department of Clinical Genetics, Lund University Hospital, SE-221 85 Lund, Sweden

2Department of Automatic Control, Royal Institute of Technology, SE-100 44 Stockholm, Sweden

3Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, NY 10021, USA

author email corresponding author email

Genome Biology 2007, 8:R74doi:10.1186/gb-2007-8-5-r74

Published: 8 May 2007

Subject areas: Bioinformatics, Genome studies

Abstract

Ontological analysis facilitates the interpretation of microarray data. Here we describe new ontological analysis methods which, unlike existing approaches, are threshold-free and statistically powerful. We perform extensive evaluations and introduce a new concept, detection spectra, to characterize methods. We show that different ontological analysis methods exhibit distinct detection spectra, and that it is critical to account for this diversity. Our results argue strongly against the continued use of existing methods, and provide directions towards an enhanced approach.


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