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.
Highlights
Genetic analysis of rare variants is considered to be one of the most important components to compensate for the current deficiency of genetic variation, which has not yet been explained [1]
In terms of power performance, multi-gene region analysis has a comparative advantage in rare variants multi-gene regions, and the power of the Step method is the best in four simulated gene regions
Combined with the previous simulation of the functional linear model (FLM) method, it has a good performance when the gene sub-region in the multi-gene regions is of the same type, but the performance is not good when the multi-gene regions are mixed with multiple types of gene regions
Summary
Genetic analysis of rare variants is considered to be one of the most important components to compensate for the current deficiency of genetic variation, which has not yet been explained [1]. Many previous tools and methods are designed for common variants, so there is still a lack of efficient and practical tools for rare variants association analysis. Single-marker association analysis is the most commonly used method of gene association analysis. If this method is directly applied to rare variants, it will be impossible to find loci with a moderate or low gene effect due to the limitations of single-marker association analysis [5,6]. The effect of a locus of a rare variant is small and not detected, and if the single-marker association analysis is used, many valuable association loci will be ignored
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