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Family-based association analysis with ordered categorical phenotypes, covariates and interactions

Baksh, M. F., Balding, D. J., Vyse, T. J. and Whittaker, J. C. (2007) Family-based association analysis with ordered categorical phenotypes, covariates and interactions. Genetic Epidemiology, 31 (1). pp. 1-8. ISSN 0741-0395

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To link to this article DOI: 10.1002/gepi.20183

Abstract/Summary

Genetic association analyses of family-based studies with ordered categorical phenotypes are often conducted using methods either for quantitative or for binary traits, which can lead to suboptimal analyses. Here we present an alternative likelihood-based method of analysis for single nucleotide polymorphism (SNP) genotypes and ordered categorical phenotypes in nuclear families of any size. Our approach, which extends our previous work for binary phenotypes, permits straightforward inclusion of covariate, gene-gene and gene-covariate interaction terms in the likelihood, incorporates a simple model for ascertainment and allows for family-specific effects in the hypothesis test. Additionally, our method produces interpretable parameter estimates and valid confidence intervals. We assess the proposed method using simulated data, and apply it to a polymorphism in the c-reactive protein (CRP) gene typed in families collected to investigate human systemic lupus erythematosus. By including sex interactions in the analysis, we show that the polymorphism is associated with anti-nuclear autoantibody (ANA) production in females, while there appears to be no effect in males.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical and Physical Sciences > Department of Mathematics and Statistics
Faculty of Science > School of Mathematical and Physical Sciences > Department of Mathematics and Statistics > Applied Statistics
Faculty of Life Sciences > School of Biological Sciences > Biomedical Sciences
Faculty of Life Sciences > School of Biological Sciences > Environmental Biology
Faculty of Life Sciences > School of Psychology and Clinical Language Sciences > Department of Clinical Language Sciences
ID Code:7244
Publisher:Wiley-Blackwell

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