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

2008; Oxford University Press; Volume: 24; Issue: 16 Linguagem: Inglês

10.1093/bioinformatics/btn315

1367-4811

Scott F. Saccone, Nancy L. Saccone, Gary E. Swan, Pamela A. F. Madden, Alison Goate, John P. Rice, Laura J. Bierut,

Genetic Mapping and Diversity in Plants and Animals

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.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.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.Supplementary data are available at Bioinformatics online.