Simulation Research on the Methods of Multi-Gene Region Association Analysis Based on a Functional Linear Model

Abstract

Genome-wide association analysis is an important approach to identify genetic variants associated with complex traits. Complex traits are not only affected by single gene loci, but also by the interaction of multiple gene loci. Studies of association between gene regions and quantitative traits are of great significance in revealing the genetic mechanism of biological development. There have been a lot of studies on single-gene region association analysis, but the application of functional linear models in multi-gene region association analysis is still less. In this paper, a functional multi-gene region association analysis test method is proposed based on the functional linear model. From the three directions of common multi-gene region method, multi-gene region weighted method and multi-gene region loci weighted method, that test method is studied combined with computer simulation. The following conclusions are obtained through computer simulation: (a) The functional multi-gene region association analysis test method has higher power than the functional single gene region association analysis test method; (b) The functional multi-gene region weighted method performs better than the common functional multi-gene region method; (c) the functional multi-gene region loci weighted method is the best method for association analysis on three directions of the common multi-gene region method; (d) the performance of the Step method and Multi-gene region loci weighted Step for multi-gene regions is the best in general. Functional multi-gene region association analysis test method can theoretically provide a feasible method for the study of complex traits affected by multiple genes.

Keywords: association analysis; functional linear model; loci weighted; multi-gene regions; region weighted.

Figure 1

The simulation power of gene regions 2, 4, 5, 7, and 10 using the multi-gene region loci weighted method. Scenario I—all effect directions of all associated loci are positive for gene loci; Scenario II—the effect directions of all associated loci are negative for the 4-th and 7-th gene region; Scenario III—choose a gene locus at random and the effect direction of the gene loci is negative for every associated region.

Figure 2

The simulation false positive rates of gene regions 1, 3, 6, 8, and 9 using the multi-gene region loci weighted method. Scenario I—all effect directions of all associated loci are positive for gene loci; Scenario II—the effect directions of all associated loci are negative for the 4-th and 8-th gene region; Scenario III—choose a gene locus at random and the effect direction of the gene loci is negative for every associated region.