Family-based gene-environment interaction using sequence kernel association test (FGE-SKAT) for complex quantitative traits

Abstract After the genome-wide association studies (GWAS) era, whole-genome sequencing is highly engaged in identifying the association of complex traits with rare variations. A score-based variance-component test has been proposed to identify common and rare genetic variants associated with complex...

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Autores principales:	Chao-Yu Guo, Reng-Hong Wang, Hsin-Chou Yang
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/5f8b3d59af3b4b1abef36aa8d8305e0e
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spelling	oai:doaj.org-article:5f8b3d59af3b4b1abef36aa8d8305e0e2021-12-02T13:26:28ZFamily-based gene-environment interaction using sequence kernel association test (FGE-SKAT) for complex quantitative traits10.1038/s41598-021-86871-22045-2322https://doaj.org/article/5f8b3d59af3b4b1abef36aa8d8305e0e2021-04-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-86871-2https://doaj.org/toc/2045-2322Abstract After the genome-wide association studies (GWAS) era, whole-genome sequencing is highly engaged in identifying the association of complex traits with rare variations. A score-based variance-component test has been proposed to identify common and rare genetic variants associated with complex traits while quickly adjusting for covariates. Such kernel score statistic allows for familial dependencies and adjusts for random confounding effects. However, the etiology of complex traits may involve the effects of genetic and environmental factors and the complex interactions between genes and the environment. Therefore, in this research, a novel method is proposed to detect gene and gene-environment interactions in a complex family-based association study with various correlated structures. We also developed an R function for the Fast Gene-Environment Sequence Kernel Association Test (FGE-SKAT), which is freely available as supplementary material for easy GWAS implementation to unveil such family-based joint effects. Simulation studies confirmed the validity of the new strategy and the superior statistical power. The FGE-SKAT was applied to the whole genome sequence data provided by Genetic Analysis Workshop 18 (GAW18) and discovered concordant and discordant regions compared to the methods without considering gene by environment interactions.Chao-Yu GuoReng-Hong WangHsin-Chou YangNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-8 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Chao-Yu Guo Reng-Hong Wang Hsin-Chou Yang Family-based gene-environment interaction using sequence kernel association test (FGE-SKAT) for complex quantitative traits
description	Abstract After the genome-wide association studies (GWAS) era, whole-genome sequencing is highly engaged in identifying the association of complex traits with rare variations. A score-based variance-component test has been proposed to identify common and rare genetic variants associated with complex traits while quickly adjusting for covariates. Such kernel score statistic allows for familial dependencies and adjusts for random confounding effects. However, the etiology of complex traits may involve the effects of genetic and environmental factors and the complex interactions between genes and the environment. Therefore, in this research, a novel method is proposed to detect gene and gene-environment interactions in a complex family-based association study with various correlated structures. We also developed an R function for the Fast Gene-Environment Sequence Kernel Association Test (FGE-SKAT), which is freely available as supplementary material for easy GWAS implementation to unveil such family-based joint effects. Simulation studies confirmed the validity of the new strategy and the superior statistical power. The FGE-SKAT was applied to the whole genome sequence data provided by Genetic Analysis Workshop 18 (GAW18) and discovered concordant and discordant regions compared to the methods without considering gene by environment interactions.
format	article
author	Chao-Yu Guo Reng-Hong Wang Hsin-Chou Yang
author_facet	Chao-Yu Guo Reng-Hong Wang Hsin-Chou Yang
author_sort	Chao-Yu Guo
title	Family-based gene-environment interaction using sequence kernel association test (FGE-SKAT) for complex quantitative traits
title_short	Family-based gene-environment interaction using sequence kernel association test (FGE-SKAT) for complex quantitative traits
title_full	Family-based gene-environment interaction using sequence kernel association test (FGE-SKAT) for complex quantitative traits
title_fullStr	Family-based gene-environment interaction using sequence kernel association test (FGE-SKAT) for complex quantitative traits
title_full_unstemmed	Family-based gene-environment interaction using sequence kernel association test (FGE-SKAT) for complex quantitative traits
title_sort	family-based gene-environment interaction using sequence kernel association test (fge-skat) for complex quantitative traits
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/5f8b3d59af3b4b1abef36aa8d8305e0e
work_keys_str_mv	AT chaoyuguo familybasedgeneenvironmentinteractionusingsequencekernelassociationtestfgeskatforcomplexquantitativetraits AT renghongwang familybasedgeneenvironmentinteractionusingsequencekernelassociationtestfgeskatforcomplexquantitativetraits AT hsinchouyang familybasedgeneenvironmentinteractionusingsequencekernelassociationtestfgeskatforcomplexquantitativetraits
_version_	1718393033030893568

Family-based gene-environment interaction using sequence kernel association test (FGE-SKAT) for complex quantitative traits

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