Bayesian analysis of longitudinal traits in the Korea Association Resource (KARE) cohort
DC Field | Value | Language |
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dc.contributor.author | Chung, W. | - |
dc.contributor.author | Hwang, H. | - |
dc.contributor.author | Park, T. | - |
dc.date.accessioned | 2022-07-28T01:40:06Z | - |
dc.date.available | 2022-07-28T01:40:06Z | - |
dc.date.created | 2022-07-28 | - |
dc.date.issued | 2022-06 | - |
dc.identifier.issn | 1598-866X | - |
dc.identifier.uri | http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/42418 | - |
dc.description.abstract | Various methodologies for the genetic analysis of longitudinal data have been proposed and applied to data from large-scale genome-wide association studies (GWAS) to identify single nucleotide polymorphisms (SNPs) associated with traits of interest and to detect SNP-time interactions. We recently proposed a grid-based Bayesian mixed model for longitudinal genetic data and showed that our Bayesian method increased the statistical power compared to the corresponding univariate method and well detected SNP-time interactions. In this paper, we further analyze longitudinal obesity-related traits such as body mass index, hip circumference, waist circumference, and waist-hip ratio from Korea Association Resource data to evaluate the proposed Bayesian method. We first conducted GWAS analyses of cross-sectional traits and combined the results of GWAS analyses through a meta-analysis based on a trajectory model and a random-effects model. We then applied our Bayesian method to a subset of SNPs selected by meta-analysis to further discover SNPs associated with traits of interest and SNP-time interactions. The proposed Bayesian method identified several novel SNPs associated with longitudinal obesity-related traits, and almost 25% of the identified SNPs had significant p-values for SNP-time interactions. © 2022 Korea Genome Organization. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Korea Genome Organization | - |
dc.relation.isPartOf | Genomics and Informatics | - |
dc.title | Bayesian analysis of longitudinal traits in the Korea Association Resource (KARE) cohort | - |
dc.type | Article | - |
dc.identifier.doi | 10.5808/gi.22022 | - |
dc.type.rims | ART | - |
dc.identifier.bibliographicCitation | Genomics and Informatics, v.20, no.2 | - |
dc.description.journalClass | 1 | - |
dc.identifier.scopusid | 2-s2.0-85134342735 | - |
dc.citation.number | 2 | - |
dc.citation.title | Genomics and Informatics | - |
dc.citation.volume | 20 | - |
dc.contributor.affiliatedAuthor | Chung, W. | - |
dc.type.docType | Article | - |
dc.description.isOpenAccess | Y | - |
dc.subject.keywordAuthor | Bayesian mixed model | - |
dc.subject.keywordAuthor | KARE data | - |
dc.subject.keywordAuthor | longitudinal data | - |
dc.subject.keywordAuthor | obesity-related traits | - |
dc.description.journalRegisteredClass | scopus | - |
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