Systematic biological prioritization after a genome-wide association study: an application to nicotine dependence.
paper
Primary
Public
Unavailable
- Authors
- Saccone, Scott F; Saccone, Nancy L; Swan, Gary E; Madden, Pamela A F; Goate, Alison M; Rice, John P; Bierut, Laura J
- Year
- 2008
- Journal
- Bioinformatics (Oxford, England)
- PMID
- 18565990
- DOI
- 10.1093/bioinformatics/btn315
- PMCID
- PMC2610477
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. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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