IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this article or follow this journal

Parametric and semiparametric methods for mapping quantitative trait loci

  • Cheng, Jung-Yu
  • Tzeng, Shinn-Jia
Registered author(s):

    Most statistical methods for mapping quantitative trait loci (QTLs) have been extensively developed for normally distributed and completely observed phenotypes. A survival model such as Cox's proportional hazards model, or an accelerated failure time model, is the natural choice for regressing a phenotype onto a maker-type when the primary phenotype belongs to failure time. This study proposes parametric and semiparametric methods based on accelerated failure time models for interval mapping. In the parametric model, the EM algorithm (expectation maximization algorithm) is adopted to estimate regression parameters and search the entire chromosome for QTL. In the semiparametric model, the error distribution is left unspecified, and a rank-based inference is developed for the effect and location of QTL. Simulated data are used to compare the mapping performance of the semiparametric methodology with that of the parametric method, which separately selects the correct and incorrect error distribution. Analytical results reveal that the parametric estimators may be more efficient in determining the effect and location of QTL, but have obvious bias when selecting the incorrect error distribution. In contrast, the semiparametric inference is robust to the error distribution.

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL: http://www.sciencedirect.com/science/article/B6V8V-4T9M5YF-2/2/9e6c0653e25e8218067da67b1c9d6856
    Download Restriction: Full text for ScienceDirect subscribers only.

    As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

    Article provided by Elsevier in its journal Computational Statistics & Data Analysis.

    Volume (Year): 53 (2009)
    Issue (Month): 5 (March)
    Pages: 1843-1849

    as
    in new window

    Handle: RePEc:eee:csdana:v:53:y:2009:i:5:p:1843-1849
    Contact details of provider: Web page: http://www.elsevier.com/locate/csda

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

    as in new window
    1. Guoqing Diao & D. Y. Lin, 2005. "Semiparametric Methods for Mapping Quantitative Trait Loci with Censored Data," Biometrics, The International Biometric Society, vol. 61(3), pages 789-798, 09.
    2. Mai Zhou, 2005. "Empirical likelihood analysis of the rank estimator for the censored accelerated failure time model," Biometrika, Biometrika Trust, vol. 92(2), pages 492-498, June.
    3. Zhezhen Jin, 2003. "Rank-based inference for the accelerated failure time model," Biometrika, Biometrika Trust, vol. 90(2), pages 341-353, June.
    4. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    Full references (including those not matched with items on IDEAS)

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:53:y:2009:i:5:p:1843-1849. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei)

    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.

    If references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link to it, you can help with 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 profile, as there may be some citations waiting for confirmation.

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

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.