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

Björn Nilsson1*, Petra Håkansson12, Mikael Johansson2, Sven Nelander3 and Thoas Fioretos1

Author Affiliations

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

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

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

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Genome Biology 2007, 8:R74  doi:10.1186/gb-2007-8-5-r74

Published: 8 May 2007

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.