國家衛生研究院 NHRI:Item 3990099045/12233
English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 12145/12927 (94%)
造訪人次 : 916647      線上人數 : 1492
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    主頁登入上傳說明關於NHRI管理 到手機版
    請使用永久網址來引用或連結此文件: http://ir.nhri.org.tw/handle/3990099045/12233


    題名: Rare variant association tests for pleiotropy in longitudinal family studies
    作者: Yu, J;Chiu, Y
    貢獻者: Institute of Population Health Sciences
    摘要: Abundant pleiotropy has been observed in many complex traits or disease. When pleiotropy exists, testing rare variants for multiple phenotypes simultaneously is often more powerful than for single phenotype through borrowing additional information from cross-phenotype correlation. Likewise, identifying rare variants associated with repeated phenotypic measurements in longitudinal studies can also have greater statistical power than that in a cross-sectional study. On the other hand, functional rare variants are often enriched in family-based designs. Longitudinal familybased designs therefore provide valuable opportunities to increase statistical power on identifying pleiotropic rare variants associated with multiple phenotypes. In addition, identi fi cation of pleiotropic variants is helpful for elucidating shared pathogenesis of multiple phenotypes. However, statistical tests for pleiotropic rare variants detection in longitudinal family studies remain fairly limited. We extended pedigree-based burden and kernel association tests to longitudinal studies with multiple phenotypes. Generalized estimating equation (GEE) approaches were used to account for the correlations from multiple phenotypes at individual time points as well as the complex correlations between repeated measures of the same phenotype (serial correlations) and between individuals within the same family (familial correlations). Extensive simulation studies were conducted to evaluate performance of the proposed tests under various con fi gurations. The proposed tests were illustrated by a real data example. Both simulation study and data example suggested that incorporating multiple phenotypes can increase statistical power of the proposed tests on rare variant detection. (This study has been supported by grants from Ministry of Science and Technology (MOST105-2314-B-400-017) and National Health Research Institutes in Taiwan (PH-104~106-PP-04).)
    日期: 2018-10
    關聯: European Journal of Human Genetics. 2018 Oct;26(Suppl.):782.
    Link to: https://doi.org/10.1038/s41431-018-0247-7
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=1018-4813&DestApp=IC2JCR
    Cited Times(WOS): https://www.webofscience.com/wos/woscc/full-record/WOS:000489312606303
    顯示於類別:[其他] 會議論文/會議摘要

    文件中的檔案:

    檔案 描述 大小格式瀏覽次數
    ISI000489312606303.pdf129KbAdobe PDF220檢視/開啟


    在NHRI中所有的資料項目都受到原著作權保護.

    TAIR相關文章

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