Association Studies for Quantitative Traits
Momiao Xiong · 2017
This chapter moves association analysis for qualitative traits to association analysis to quantitative traits. Quantitative genetics approaches have broad applications. Quantitative traits may be risk factors for diseases. Therefore, quantitative genetics can serve as a tool to unravel mechanisms of diseases. Quantitative genetics can also be used for animal and plant improvement. Basic concepts, models, and theories for quantitative genetics, such as genetic additive and dominance effects, genetic variance, and linear regression as a major model for genetic studies of a quantitative trait, are first introduced. A simple linear regression model with a single marker and multiple regression model with multiple markers are discussed. However, these classical quantitative genetic models are not suitable for rare variants. To cope with next-generation sequencing data, this chapter moves attention to the gene-based quantitative trait association analysis. Three approaches to gene-based quantitative trait analysis: functional linear models, canonical correlation analysis and kernel approach are discussed. To develop a general framework for quantitative genetic studies, this chapter formulates an association analysis problem as an independent test in a Hilbert space and uses a dependence measure to quantify the level of association of the genetic variant with the quantitative trait.