English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 90704/120752 (75%)
Visitors : 24994127      Online Users : 448
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    政大機構典藏 > 商學院 > 統計學系 > 期刊論文 >  Item 140.119/125126
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/125126

    Title: Semiparametric variance components models for genetic studies with longitudinal phenotypes
    Authors: Wang, Y.
    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 連結: https://doi.org/10.1093/biostatistics/kxr027
    DOI: 10.1093/biostatistics/kxr027
    Appears in Collections:[統計學系] 期刊論文

    Files in This Item:

    File Description SizeFormat
    64.pdf435KbAdobe PDF36View/Open

    All items in 政大典藏 are protected by copyright, with all rights reserved.

    社群 sharing

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback