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政大典藏 > College of Commerce > Department of Statistics > Periodical Articles > Item 140.119/125126

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/125126

Title:	Semiparametric variance components models for genetic studies with longitudinal phenotypes
Authors:	Wang, Y. 黃佳慧 Huang, C.-H.
Contributors:	統計系
Keywords:	Genome-wide linkage study;Multivariate longitudinal data;Penalized splines;Quantitative trait locus
Date:	2012-07
Issue Date:	2019-08-13 09:19:19 (UTC+8)
Abstract:	In a family-based genetic study such as the Framingham Heart Study (FHS), longitudinal trait measurements are recorded on subjects collected from families. Observations on subjects from the same family are correlated due to shared genetic composition or environmental factors such as diet. The data have a 3-level structure with measurements nested in subjects and subjects nested in families. We propose a semiparametric variance components model to describe phenotype observed at a time point as the sum of a nonparametric population mean function, a nonparametric random quantitative trait locus (QTL) effect, a shared environmental effect, a residual random polygenic effect and measurement error. One feature of the model is that we do not assume a parametric functional form of the age-dependent QTL effect, and we use penalized spline-based method to fit the model. We obtain nonparametric estimation of the QTL heritability defined as the ratio of the QTL variance to the total phenotypic variance. We use simulation studies to investigate performance of the proposed methods and apply these methods to the FHS systolic blood pressure data to estimate age-specific QTL effect at 62cM on chromosome 17.
Relation:	Biostatistics, Vol.13, pp.482-496
Data Type:	article
DOI link:	https://doi.org/10.1093/biostatistics/kxr027
DOI:	10.1093/biostatistics/kxr027
Appears in Collections:	[Department of Statistics] Periodical Articles

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