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Analytical Models For Genetics of Human Traits Influenced By Sex
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...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Bentham Science Publishers
2016
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5267469/ https://www.ncbi.nlm.nih.gov/pubmed/28217000 http://dx.doi.org/10.2174/1389202917666160420142601 |
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author | Lee, Chaeyoung |
author_facet | Lee, Chaeyoung |
author_sort | Lee, Chaeyoung |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5267469 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Bentham Science Publishers |
record_format | MEDLINE/PubMed |
spelling | pubmed-52674692017-04-01 Analytical Models For Genetics of Human Traits Influenced By Sex Lee, Chaeyoung Curr Genomics Article 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. Bentham Science Publishers 2016-10 2016-10 /pmc/articles/PMC5267469/ /pubmed/28217000 http://dx.doi.org/10.2174/1389202917666160420142601 Text en ©2016 Bentham Science Publishers https://creativecommons.org/licenses/by-nc/4.0/legalcode This is an open access article licensed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 International Public License (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/legalcode), which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited. |
spellingShingle | Article Lee, Chaeyoung Analytical Models For Genetics of Human Traits Influenced By Sex |
title | Analytical Models For Genetics of Human Traits Influenced By Sex |
title_full | Analytical Models For Genetics of Human Traits Influenced By Sex |
title_fullStr | Analytical Models For Genetics of Human Traits Influenced By Sex |
title_full_unstemmed | Analytical Models For Genetics of Human Traits Influenced By Sex |
title_short | Analytical Models For Genetics of Human Traits Influenced By Sex |
title_sort | analytical models for genetics of human traits influenced by sex |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5267469/ https://www.ncbi.nlm.nih.gov/pubmed/28217000 http://dx.doi.org/10.2174/1389202917666160420142601 |
work_keys_str_mv | AT leechaeyoung analyticalmodelsforgeneticsofhumantraitsinfluencedbysex |