Document Detail


Nonparametric modeling of longitudinal covariance structure in functional mapping of quantitative trait loci.
MedLine Citation:
PMID:  19302406     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Estimation of the covariance structure of longitudinal processes is a fundamental prerequisite for the practical deployment of functional mapping designed to study the genetic regulation and network of quantitative variation in dynamic complex traits. We present a nonparametric approach for estimating the covariance structure of a quantitative trait measured repeatedly at a series of time points. Specifically, we adopt Huang et al.'s (2006, Biometrika 93, 85-98) approach of invoking the modified Cholesky decomposition and converting the problem into modeling a sequence of regressions of responses. A regularized covariance estimator is obtained using a normal penalized likelihood with an L(2) penalty. This approach, embedded within a mixture likelihood framework, leads to enhanced accuracy, precision, and flexibility of functional mapping while preserving its biological relevance. Simulation studies are performed to reveal the statistical properties and advantages of the proposed method. A real example from a mouse genome project is analyzed to illustrate the utilization of the methodology. The new method will provide a useful tool for genome-wide scanning for the existence and distribution of quantitative trait loci underlying a dynamic trait important to agriculture, biology, and health sciences.
Authors:
John Stephen Yap; Jianqing Fan; Rongling Wu
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, U.S. Gov't, Non-P.H.S.    
Journal Detail:
Title:  Biometrics     Volume:  65     ISSN:  1541-0420     ISO Abbreviation:  Biometrics     Publication Date:  2009 Dec 
Date Detail:
Created Date:  2009-12-16     Completed Date:  2010-03-04     Revised Date:  2013-06-02    
Medline Journal Info:
Nlm Unique ID:  0370625     Medline TA:  Biometrics     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1068-77     Citation Subset:  IM    
Affiliation:
Department of Statistics, University of Florida, Gainesville, Florida 32611, USA.
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MeSH Terms
Descriptor/Qualifier:
Animals
Biometry / methods*
Chromosome Mapping / statistics & numerical data
Computer Simulation
Databases, Genetic
Female
Genome-Wide Association Study / statistics & numerical data
Likelihood Functions
Male
Mice
Models, Statistical*
Multivariate Analysis
Quantitative Trait Loci*
Statistics, Nonparametric*
Grant Support
ID/Acronym/Agency:
NIGMS-0540745//PHS HHS; R01 GM072611-04/GM/NIGMS NIH HHS; R01-GM072611/GM/NIGMS NIH HHS
Comments/Corrections

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