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Nucleic Acids Research Advance Access published online on March 16, 2008
Nucleic Acids Research, doi:10.1093/nar/gkn114
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© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Positional gene enrichment analysis of gene sets for high-resolution identification of overrepresented chromosomal regions

Katleen De Preter1,*, Roland Barriot2, Frank Speleman1, Jo Vandesompele1 and Yves Moreau2

1Center for Medical Genetics, Ghent University Hospital, De Pintelaan 185, B-9000 Ghent and 2ESAT-SCD, Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, 3001 Leuven, Belgium

*To whom correspondence should be addressed. Tel: +32 9 3325533; Fax: +32 9 3326549; Email: katleen.depreter{at}ugent.be

Received November 20, 2007. Revised January 25, 2008. Accepted February 19, 2008.

The search for feature enrichment is a widely used method to characterize a set of genes. While several tools have been designed for nominal features such as Gene Ontology annotations or KEGG Pathways, very little has been proposed to tackle numerical features such as the chromosomal positions of genes. For instance, microarray studies typically generate gene lists that are differentially expressed in the sample subgroups under investigation, and when studying diseases caused by genome alterations, it is of great interest to delineate the chromosomal regions that are significantly enriched in these lists. In this article, we present a positional gene enrichment analysis method (PGE) for the identification of chromosomal regions that are significantly enriched in a given set of genes. The strength of our method relies on an original query optimization approach that allows to virtually consider all the possible chromosomal regions for enrichment, and on the multiple testing correction which discriminates truly enriched regions versus those that can occur by chance. We have developed a Web tool implementing this method applied to the human genome (http://www.esat.kuleuven.be/~bioiuser/pge). We validated PGE on published lists of differentially expressed genes. These analyses showed significant overrepresentation of known aberrant chromosomal regions.

The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors.


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