1. An Association Mapping Framework To Account for Potential Sex Difference in Genetic Architectures
- Author
-
Kang, Eun Yong, Lee, Cue Hyunkyu, Furlotte, Nicholas A, Joo, Jong Wha J, Kostem, Emrah, Zaitlen, Noah, Eskin, Eleazar, and Han, Buhm
- Subjects
Biological Sciences ,Genetics ,Human Genome ,Mental Health ,Algorithms ,Chromosome Mapping ,Computational Biology ,Female ,Genome-Wide Association Study ,Humans ,Male ,Multifactorial Inheritance ,Quantitative Trait Loci ,Sex Characteristics ,Association Mapping ,Genetics of Sex ,Linear Mixed Model ,Meta-Analysis ,Developmental Biology ,Biochemistry and cell biology - Abstract
Over the past few years, genome-wide association studies have identified many trait-associated loci that have different effects on females and males, which increased attention to the genetic architecture differences between the sexes. The between-sex differences in genetic architectures can cause a variety of phenomena such as differences in the effect sizes at trait-associated loci, differences in the magnitudes of polygenic background effects, and differences in the phenotypic variances. However, current association testing approaches for dealing with sex, such as including sex as a covariate, cannot fully account for these phenomena and can be suboptimal in statistical power. We present a novel association mapping framework, MetaSex, that can comprehensively account for the genetic architecture differences between the sexes. Through simulations and applications to real data, we show that our framework has superior performance than previous approaches in association mapping.
- Published
- 2018