Display Settings:

Format

Send to:

Choose Destination
    Genetics. 2008 Aug;179(4):2275-89. Epub 2008 Aug 9.

    Bayesian quantitative trait loci mapping for multiple traits.

    Source

    Departments of Biostatistics, Section on Statistical Genetics, University of Alabama, Birmingham, AL 35294, USA.

    Abstract

    Most quantitative trait loci (QTL) mapping experiments typically collect phenotypic data on multiple correlated complex traits. However, there is a lack of a comprehensive genomewide mapping strategy for correlated traits in the literature. We develop Bayesian multiple-QTL mapping methods for correlated continuous traits using two multivariate models: one that assumes the same genetic model for all traits, the traditional multivariate model, and the other known as the seemingly unrelated regression (SUR) model that allows different genetic models for different traits. We develop computationally efficient Markov chain Monte Carlo (MCMC) algorithms for performing joint analysis. We conduct extensive simulation studies to assess the performance of the proposed methods and to compare with the conventional single-trait model. Our methods have been implemented in the freely available package R/qtlbim (http://www.qtlbim.org), which greatly facilitates the general usage of the Bayesian methodology for unraveling the genetic architecture of complex traits.

    PMID:
    18689903
    [PubMed - indexed for MEDLINE]
    PMCID:
    PMC2516097
    Free PMC Article

    Images from this publication.See all images (6) Free text

    F igure  1.—
    F igure  3.—
    F igure  5.—
    F igure  2.—
    F igure  4.—
    F igure  6.—

      Supplemental Content

      Icon for HighWire Press Icon for PubMed Central

      Save items

      loading

      Recent activity

      Your browsing activity is empty.

      Activity recording is turned off.

      Turn recording back on

      See more...
      Write to the Help Desk