IDEAS home Printed from https://ideas.repec.org/a/bpj/sagmbi/v9y2010i1n32.html
   My bibliography  Save this article

Mapping Quantitative Trait Loci in a Non-Equilibrium Population

Author

Listed:
  • Wu Song

    (St. Jude Children’s Research Hospital and Beijing Forestry University)

  • Yang Jie

    (St. Jude Children’s Research Hospital)

  • Wu Rongling

    (Beijing Forestry University)

Abstract

The genetic control of a complex trait can be studied by testing and mapping the genotypes of the underlying quantitative trait loci (QTLs) through their associations with observable marker genotypes. All existing statistical methods for QTL mapping assume an equilibrium population, allowing marker-QTL associations to be simply described at the gametic level. However, many mapping populations in practice may deviate from equilibrium; thus, gametic associations cannot reflect marker-QTL associations at the genotype level. We develop a robust model for mapping QTLs in a non-equilibrium natural population in which individuals are not necessarily randomly mating due to various evolutionary forces. Without use of Hardy-Weinberg equilibrium, the new model founds marker-QTL associations directly on the genotypes, specified by a group of disequilibrium parameters. Simulation studies were performed to test the statistical properties of the model, which suggests that the new model covers current mapping models and can be safely used for any data set.

Suggested Citation

  • Wu Song & Yang Jie & Wu Rongling, 2010. "Mapping Quantitative Trait Loci in a Non-Equilibrium Population," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 9(1), pages 1-21, August.
    • Handle: RePEc:bpj:sagmbi:v:9:y:2010:i:1:n:32
    DOI: 10.2202/1544-6115.1578
    as

    Download full text from publisher

    File URL: https://doi.org/10.2202/1544-6115.1578
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.2202/1544-6115.1578?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.

    References listed on IDEAS

    as
    1. Lin, D.Y. & Zeng, D., 2006. "Likelihood-Based Inference on Haplotype Effects in Genetic Association Studies," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 89-104, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jinbo Chen & Dongyu Lin & Hagit Hochner, 2012. "Semiparametric Maximum Likelihood Methods for Analyzing Genetic and Environmental Effects with Case-Control Mother–Child Pair Data," Biometrics, The International Biometric Society, vol. 68(3), pages 869-877, September.
    2. Jinbo Chen & Carmen Rodriguez, 2007. "Conditional Likelihood Methods for Haplotype-Based Association Analysis Using Matched Case–Control Data," Biometrics, The International Biometric Society, vol. 63(4), pages 1099-1107, December.
    3. Iryna Lobach & Raymond J. Carroll & Christine Spinka & Mitchell H. Gail & Nilanjan Chatterjee, 2008. "Haplotype‐Based Regression Analysis and Inference of Case–Control Studies with Unphased Genotypes and Measurement Errors in Environmental Exposures," Biometrics, The International Biometric Society, vol. 64(3), pages 673-684, September.
    4. French Benjamin & Lumley Thomas & Cappola Thomas P. & Mitra Nandita, 2012. "Non-Iterative, Regression-Based Estimation of Haplotype Associations with Censored Survival Outcomes," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(3), pages 1-24, February.
    5. Yulia V. Marchenko & Raymond K. Carroll & Danyu Y. Lin & Christopher I. Amos & Roberto G. Gutierrez, 2008. "Semiparametric analysis of case–control genetic data in the presence of environmental factors," Stata Journal, StataCorp LP, vol. 8(3), pages 305-333, September.
    6. Sinha Samiran & Gruber Stephen B & Mukherjee Bhramar & Rennert Gad, 2008. "Inference of the Haplotype Effect in a Matched Case-Control Study Using Unphased Genotype Data," The International Journal of Biostatistics, De Gruyter, vol. 4(1), pages 1-28, May.
    7. X. Li & B. N. Thomas & S. M. Rich & D. Ecker & J. K. Tumwine & A. S. Foulkes, 2009. "Estimating and testing haplotype–trait associations in non‐diploid populations," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 58(5), pages 663-678, December.
    8. Hua Yun Chen & Daniel E. Rader & Mingyao Li, 2015. "Likelihood Inferences on Semiparametric Odds Ratio Model," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(511), pages 1125-1135, September.
    9. Tianying Wang & Alex Asher, 2021. "Improved Semiparametric Analysis of Polygenic Gene–Environment Interactions in Case–Control Studies," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 13(3), pages 386-401, December.
    10. Bhramar Mukherjee & Nilanjan Chatterjee, 2008. "Exploiting Gene‐Environment Independence for Analysis of Case–Control Studies: An Empirical Bayes‐Type Shrinkage Estimator to Trade‐Off between Bias and Efficiency," Biometrics, The International Biometric Society, vol. 64(3), pages 685-694, September.
    11. Thomas H. Scheike & Torben Martinussen & Jeremy D. Silver, 2010. "Estimating Haplotype Effects for Survival Data," Biometrics, The International Biometric Society, vol. 66(3), pages 705-715, September.

    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:9:y:2010:i:1:n:32. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc 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 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.