title: Threshold-free high-power methods for the ontological analysis of genome-wide gene-expression 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.
authors.affiliation: Department of Clinical Genetics, Lund University Hospital, SE-221 85 Lund, Sweden. bjorn.nilsson@med.lu.se
authors.forename: Björn
authors.initials: B
authors.lastname: Nilsson
authors.forename: Petra
authors.initials: P
authors.lastname: Håkansson
authors.forename: Mikael
authors.initials: M
authors.lastname: Johansson
authors.forename: Sven
authors.initials: S
authors.lastname: Nelander
authors.forename: Thoas
authors.initials: T
authors.lastname: Fioretos
mesh_terms: D000465:Algorithms; D002965:Classification / Q000379:methods; D015972:Gene Expression Regulation, Neoplastic; D016678:Genome; D008722:Methods; D015233:Models, Statistical; D012984:Software