KMgene: a unified R package for gene-based association analysis for complex traits

Area of Science:

• Genetics
• Statistical Genetics
• Bioinformatics

Background:

• Gene-based association studies are crucial for understanding complex traits.
• Existing methods may not adequately handle familial, multivariate, or longitudinal data.
• Kernel machine regression offers a flexible framework for genetic association analysis.

Purpose of the Study:

• To introduce KMgene, an R package for gene-based association tests.
• To implement kernel machine regression within a generalized linear mixed model framework.
• To provide a tool for analyzing complex trait data in genetic studies.

Main Methods:

• Development of the KMgene R package.
• Application of kernel machine (KM) regression.
• Utilizing a generalized linear mixed model (GLMM) framework.
• Extensive simulation studies for performance evaluation.

Main Results:

• The KMgene package provides a valid approach for gene-based association tests.
• The implemented methods are suitable for familial, multivariate, and longitudinal traits.
• Simulation results demonstrate the reliability of the KMgene package.

Conclusions:

• KMgene offers a robust computational tool for genetic association studies.
• The package facilitates the analysis of complex genetic architectures.
• It supports advanced statistical modeling for trait analysis.