POCUS: mining genomic sequence annotation to predict disease genes

Frances S Turner^*, Daniel R Clutterbuck^* and Colin AM Semple

MRC Human Genetics Unit, Crewe Road, Western General Hospital, Edinburgh EH4 2XU, UK

author email corresponding author email* Contributed equally

Genome Biology 2003, 4:R75doi:10.1186/gb-2003-4-11-r75


Published:	10 October 2003

Subject areas: Bioinformatics, Genetics, Medicine

Abstract

Here we present POCUS (prioritization of candidate genes using statistics), a novel computational approach to prioritize candidate disease genes that is based on over-representation of functional annotation between loci for the same disease. We show that POCUS can provide high (up to 81-fold) enrichment of real disease genes in the candidate-gene shortlists it produces compared with the original large sets of positional candidates. In contrast to existing methods, POCUS can also suggest counterintuitive candidates.