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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| Format: | Article |
| Language: | English |
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Nature Portfolio
2021-04-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-021-86871-2 |
| _version_ | 1818851275604754432 |
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| 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 |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-19T07:02:26Z |
| format | Article |
| id | doaj.art-5f8b3d59af3b4b1abef36aa8d8305e0e |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-12-19T07:02:26Z |
| publishDate | 2021-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-5f8b3d59af3b4b1abef36aa8d8305e0e2022-12-21T20:31:22ZengNature PortfolioScientific Reports2045-23222021-04-011111810.1038/s41598-021-86871-2Family-based gene-environment interaction using sequence kernel association test (FGE-SKAT) for complex quantitative traitsChao-Yu Guo0Reng-Hong Wang1Hsin-Chou Yang2Division of Biostatistics, Department of Medicine, Institute of Public Health, School of Medicine, National Yang-Ming UniversityDivision of Biostatistics, Department of Medicine, Institute of Public Health, School of Medicine, National Yang-Ming UniversityInstitute of Statistical Science, Academia SinicaAbstract 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.https://doi.org/10.1038/s41598-021-86871-2 |
| spellingShingle | 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 Scientific Reports |
| title | 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_short | 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 |
| url | https://doi.org/10.1038/s41598-021-86871-2 |
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