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Summary of contributions to GAW15 Group 13: candidate gene association studies
Author(s) -
de Andrade Mariza,
Allen Andrew S.
Publication year - 2007
Publication title -
genetic epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.301
H-Index - 98
eISSN - 1098-2272
pISSN - 0741-0395
DOI - 10.1002/gepi.20287
Subject(s) - single nucleotide polymorphism , linkage disequilibrium , haplotype , covariate , quantitative trait locus , snp , tag snp , genetic association , logistic regression , locus (genetics) , biology , genetics , genotype , gene , computer science , machine learning
Here we summarize the contributions to Group 13 of the Genetic Analysis Workshop 15 held in St. Pete Beach, Florida, on November 12–14, 2006. The focus of this group was to identify candidate genes associated with rheumatoid arthritis or surrogate outcomes. The association methods proposed in this group were diverse, from better known approaches, such as logistic regression for single nucleotide polymorphism (SNP) analysis and haplotype sharing tests to methods less familiar to genetic epidemiologists, such as machine learning and visualization methods. The majority of papers analyzed Genetic Analysis Workshop 15 Problems 2 (rheumatoid arthritis data) and 3 (simulated data). The highlighted points of this group analyses were: (1) haplotype‐based statistics can be more powerful than single SNP analysis for risk‐locus localization; (2) considering linkage disequilibrium block structure in haplotype analysis may reduce the likelihood of false‐positive results; and (3) visual representation of genetic models for continuous covariates may help identify SNPs associated with the underlying quantitative trait loci. Genet. Epidemiol . 31 (Suppl 1):S110–S117, 2007. © 2007 Wiley‐Liss, Inc.