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1 October 2008 Linear Models for Analysis of Multiple Single Nucleotide Polymorphisms with Quantitative Traits in Unrelated Individuals
Jian-Feng Meng, Tasha E. Fingerlin
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Abstract

Population-based genetic association studies are increasingly used to explore the association between genetic polymorphisms and outcomes such as disease-status and disease-related quantitative traits. Because multiple polymorphisms are typically available, there are several statistical analysis strategies that might be appropriate depending on the goal of the study. In this paper, we compare several linear model parameterizations that might be used to perform a test of association between a genomic region defined by multiple SNPs and a quantitative trait. We compare via simulation the type I error and power of the omnibus F-test to detect association. As expected, there is no one most powerful test across the genetic models we considered, although tests based on simple parameterizations that do not rely on phase information can be as powerful as more complicated haplotype-based tests even when it is a haplotype that is truly associated with the trait.

© Finnish Zoological and Botanical Publishing Board 2008
Jian-Feng Meng and Tasha E. Fingerlin "Linear Models for Analysis of Multiple Single Nucleotide Polymorphisms with Quantitative Traits in Unrelated Individuals," Annales Zoologici Fennici 45(5), 429-440, (1 October 2008). https://doi.org/10.5735/086.045.0506
Received: 30 November 2007; Accepted: 1 June 2008; Published: 1 October 2008
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