Ontology type: schema:ScholarlyArticle Open Access: True
2003-11
AUTHORSFrances S Turner, Daniel R Clutterbuck, Colin AM Semple
ABSTRACTHere 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. More... »
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DOIhttp://dx.doi.org/10.1186/gb-2003-4-11-r75
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