IDEAS home Printed from https://ideas.repec.org/a/bpj/sagmbi/v11y2012i6p1-25n1.html
   My bibliography  Save this article

A maximum likelihood approach to functional mapping of longitudinal binary traits

Author

Listed:
  • Wang Chenguang

    (Beijing Forestry University and Johns Hopkins University - Sidney Kimmel Comprehensive Cancer Center)

  • Li Hongying

    (University of California at San Diego)

  • Wang Zhong

    (Beijing Forestry University and The Pennsylvania State University - Center for Statistical Genetics)

  • Wang Yaqun

    (The Pennsylvania State University - Center for Statistical Genetics)

  • Wang Ningtao

    (The Pennsylvania State University - Center for Statistical Genetics)

  • Wang Zuoheng

    (Yale University - Division of Biostatistics)

  • Wu Rongling

    (Beijing Forestry University and The Pennsylvania State University)

Abstract

Despite their importance in biology and biomedicine, genetic mapping of binary traits that change over time has not been well explored. In this article, we develop a statistical model for mapping quantitative trait loci (QTLs) that govern longitudinal responses of binary traits. The model is constructed within the maximum likelihood framework by which the association between binary responses is modeled in terms of conditional log odds-ratios. With this parameterization, the maximum likelihood estimates (MLEs) of marginal mean parameters are robust to the misspecification of time dependence. We implement an iterative procedures to obtain the MLEs of QTL genotype-specific parameters that define longitudinal binary responses. The usefulness of the model was validated by analyzing a real example in rice. Simulation studies were performed to investigate the statistical properties of the model, showing that the model has power to identify and map specific QTLs responsible for the temporal pattern of binary traits.

Suggested Citation

  • Wang Chenguang & Li Hongying & Wang Zhong & Wang Yaqun & Wang Ningtao & Wang Zuoheng & Wu Rongling, 2012. "A maximum likelihood approach to functional mapping of longitudinal binary traits," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(6), pages 1-25, November.
    • Handle: RePEc:bpj:sagmbi:v:11:y:2012:i:6:p:1-25:n:1
    DOI: 10.1515/1544-6115.1675
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/1544-6115.1675
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.1515/1544-6115.1675?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bpj:sagmbi:v:11:y:2012:i:6:p:1-25:n:1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.