國家衛生研究院 NHRI:Item 3990099045/1721
English  |  正體中文  |  简体中文  |  Items with full text/Total items : 12145/12927 (94%)
Visitors : 908391      Online Users : 1007
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
    Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer Goto mobile version


    Please use this identifier to cite or link to this item: http://ir.nhri.org.tw/handle/3990099045/1721


    Title: Incorporation of covariates into multipoint linkage disequilibrium mapping in case-control studies
    Authors: Chiu, YF;Liang, KY;Chuang, LM;Beaty, TH
    Contributors: Division of Biostatistics and Bioinformatics
    Abstract: Case-control designs are commonly adopted in genetic epidemiological studies because they are cost effective and offer powerful tests for genetic and environmental risk factors, as well as their interactions. Previously, we proposed an association mapping approach to estimate the position of an unobserved disease locus as well as measuring its genetic effect on risk. The method provides a confidence interval for the estimated map position to help narrow the chromosomal region potentially harboring a disease locus. However, concerns often rise about case-control designs including possible false positives or bias due to confounders, heterogeneity or interactions among genes and between genes and environments. In the present work, we extended the multipoint linkage disequilibrium mapping approach for case-control studies to incorporate information about factors influencing the effect of causal genes to improve precision and efficiency of the estimated location. The efficiency, bias and coverage probability of this extended approach for locating a disease locus using case-control data with and without additional information on a covariate were compared through simulation. An example of a case-control study for type 2 diabetes was used to illustrate this extended method. In this study, a strong association between diabetes and a candidate gene, SCL2A10, was detected among nonobese subjects, whereas no evidence of association was found for either obese subjects or the whole sample when obesity was ignored. Simulation studies and these diabetes data both demonstrate how the efficiency of the estimated location of a disease gene can be improved substantially by incorporating information on covariates.
    Keywords: Genetics & Heredity;Public, Environmental & Occupational Health
    Date: 2008-02
    Relation: Genetic Epidemiology. 2008 Feb;32(2):143-151.
    Link to: http://dx.doi.org/10.1002/gepi.20271
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=0741-0395&DestApp=IC2JCR
    Cited Times(WOS): https://www.webofscience.com/wos/woscc/full-record/WOS:000253306500006
    Cited Times(Scopus): http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=39649100659
    Appears in Collections:[Kung-Yee Liang] Periodical Articles
    [Yen-Feng Chiu] Periodical Articles

    Files in This Item:

    File Description SizeFormat
    000253306500006.pdf222KbAdobe PDF988View/Open


    All items in NHRI are protected by copyright, with all rights reserved.

    Related Items in TAIR

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