Development of Novel Analytic Methods for Improved Gene Mapping of Complex Human Traits Open Access
Broadaway, Kelsy Alaine (2015)
Published
Abstract
Discovering the genetic contributors to complex human traits and diseases is a central goal in genetic epidemiology. Although tremendous advancements in high-throughput genotyping and sequencing technology have allowed genetic analyses on a scale undreamt of just 15 years ago, most genetic contributors to complex trait variation remain hidden. By using population genetics theory, we can create new analytic approaches that make better use of the wealth of genetic data that are now available to us. This dissertation investigates three such analytic approaches, with each employing a powerful and flexible high-dimensional modeling kernel framework for inference. This type of approach is valuable in genetic analyses because it allows simultaneous consideration of multiple genetic variants and multiple phenotypes within a single analysis. While there are already several kernel approaches implemented for genetic studies of complex traits, this dissertation introduces three new kernel methods with each method probing a different type of hypothesis. Specifically, I develop kernel methods in which gene-environment interaction effects on complex traits are suspected, kernel methods for detecting cross-phenotype effects when pleiotropy is suspected, and kernel methods for analysis of multivariate questionnaire data that are being used as a proxy for an underlying phenotype. In subsequent chapters we derive these three methods, and then conduct in-depth simulations to illustrate the statistical validity and power of the approaches compared with existing methods. For each method, we then used our approaches to analyze real genetic data from existing complex-trait studies. We found that each of our approaches offers more power than the corresponding competing methods across a broad range of analyses. The power of our three approaches indicates that they might be useful in elucidating the complicated genetic underpinnings of human traits and disease.
Table of Contents
Chapter 1. Introduction
1.1. Gene Mapping of Complex Traits
1.2. Neo-Darwinian Model of Genetic Variation
1.2.I. Exploring the Neo-Darwinian Hypothesis
1.2.II. Effects of Gene-Environment Interactions
1.2.III. Imperfect Phenotyping
1.3. Infinitesimal Model of Genetic Variation
1.3.I. Ramifications of the Infinitesimal Model: Pleiotropy
1.4. Scope of Thesis
Chapter 2. Kernel Approach for Modeling Interaction Effects in Genetic Association Studies of Complex Quantitative Traits
2.1. Abstract
2.2. Text
2.3. Tables
2.5. Figure Legends
2.6. Figures
2.7. Supplementary Figure Legends
2.8. Supplementary Figures
Chapter 3. A Statistical Approach for Testing Cross-Phenotype Effects of Rare Variants
3.1. Abstract
3.2. Text
3.3. Tables
3.5. Figure Legends
3.6. Figures
3.7. Supplementary Figure Legends
3.8. Supplementary Figures
3.9. Supplementary Tables
Chapter 4. A Statistical Approach for Genetic Association Testing of Symptom and Questionnaire Data
4.1. Abstract
4.2. Text
4.3. Tables
4.5. Figure Legends
4.6. Figures
Chapter 5. Discussion
References
About this Dissertation
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