Systematic biological prioritization after a genome-wide association study: an application to nicotine dependence

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Abstract
Motivation: A challenging problem after a genome-wide association study (GWAS) is to balance the statistical evidence of genotype–phenotype correlation with a priori evidence of biological relevance. Results: We introduce a method for systematically prioritizing single nucleotide polymorphisms (SNPs) for further study after a GWAS. The method combines evidence across multiple domains including statistical evidence of genotype–phenotype correlation, known pathways in the pathologic development of disease, SNP/gene functional properties, comparative genomics, prior evidence of genetic linkage, and linkage disequilibrium. We apply this method to a GWAS of nicotine dependence, and use simulated data to test it on several commercial SNP microarrays. Availability: A comprehensive database of biological prioritization scores for all known SNPs is available at http://zork.wustl.edu/gin. This can be used to prioritize nicotine dependence association studies through a straightforward mathematical formula—no special software is necessary. Contact:ssaccone@wustl.edu Supplementary information: Supplementary data are available at Bioinformatics online.