1.
Genome Biol
; 4(11): R75, 2003.
Artículo
en Inglés
| MEDLINE
| ID: mdl-14611661
RESUMEN
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.