Abstract
Analytical models usually assume an additive sex effect by treating it as a covariate to identify genetic associations with sex-influenced traits. Their underlying assumptions are violated by ignoring interactions of sex with genetic factors and heterogeneous genetic effects by sex. Methods to deal with the problems are compared and discussed in this article. Especially, heterogeneity of genetic variance by sex can be assessed employing a mixed model with genetic relationship matrix constructed from genome-wide nucleotide variant information. Estimating genetic architecture of each sex would help understand different prevalence, course, and severity of complex diseases between women and men in the era of personalized medicine.
Keywords: Complex trait, Genetic heterogeneity, Genetic relationship matrix, Genetic variance, Genome-wide association study, Mixed model.
Current Genomics
Title:Analytical Models For Genetics of Human Traits Influenced By Sex
Volume: 17 Issue: 5
Author(s): Chaeyoung Lee
Affiliation:
Keywords: Complex trait, Genetic heterogeneity, Genetic relationship matrix, Genetic variance, Genome-wide association study, Mixed model.
Abstract: Analytical models usually assume an additive sex effect by treating it as a covariate to identify genetic associations with sex-influenced traits. Their underlying assumptions are violated by ignoring interactions of sex with genetic factors and heterogeneous genetic effects by sex. Methods to deal with the problems are compared and discussed in this article. Especially, heterogeneity of genetic variance by sex can be assessed employing a mixed model with genetic relationship matrix constructed from genome-wide nucleotide variant information. Estimating genetic architecture of each sex would help understand different prevalence, course, and severity of complex diseases between women and men in the era of personalized medicine.
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Cite this article as:
Lee Chaeyoung, Analytical Models For Genetics of Human Traits Influenced By Sex, Current Genomics 2016; 17 (5) . https://dx.doi.org/10.2174/1389202917666160420142601
DOI https://dx.doi.org/10.2174/1389202917666160420142601 |
Print ISSN 1389-2029 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5488 |
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