A new Bayesian automatic model selection approach for mapping quantitative trait loci under variance component model

Genetica ◽  
2008 ◽  
Vol 135 (3) ◽  
pp. 429-437 ◽  
Author(s):  
Ming Fang ◽  
Dan Jiang ◽  
Huijiang Gao ◽  
Dongxiao Sun ◽  
Runqing Yang ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Model Selection ◽  
Quantitative Trait ◽  
Variance Component ◽  
Component Model ◽  
Variance Component Model ◽  
Automatic Model Selection ◽  
Model Selection Approach ◽  
Selection Approach ◽  
Trait Loci

scholarly journals Genome-wide evaluation for quantitative trait loci under the variance component model

Genetica ◽  
2010 ◽  
Vol 138 (9-10) ◽  
pp. 1099-1109 ◽  
Author(s):  
Lide Han ◽  
Shizhong Xu
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Variance Component ◽  
Component Model ◽  
Variance Component Model ◽  
Genome Wide ◽  
Trait Loci

scholarly journals A Model Selection Approach for Expression Quantitative Trait Loci (eQTL) Mapping

Genetics ◽  
2010 ◽  
Vol 187 (2) ◽  
pp. 611-621 ◽  
Author(s):  
Ping Wang ◽  
John A. Dawson ◽  
Mark P. Keller ◽  
Brian S. Yandell ◽  
Nancy A. Thornberry ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Model Selection ◽  
Quantitative Trait ◽  
Expression Quantitative Trait Loci ◽  
Eqtl Mapping ◽  
Model Selection Approach ◽  
Selection Approach ◽  
Trait Loci

scholarly journals An Efficient Bayesian Model Selection Approach for Interacting Quantitative Trait Loci Models With Many Effects

Genetics ◽  
2007 ◽  
Vol 176 (3) ◽  
pp. 1865-1877 ◽  
Author(s):  
Nengjun Yi ◽  
Daniel Shriner ◽  
Samprit Banerjee ◽  
Tapan Mehta ◽  
Daniel Pomp ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Model Selection ◽  
Quantitative Trait ◽  
Bayesian Model ◽  
Bayesian Model Selection ◽  
Model Selection Approach ◽  
Selection Approach ◽  
Trait Loci ◽  
Bayesian Model Selection Approach

scholarly journals A Model Selection Approach for the Identification of Quantitative Trait Loci in Experimental Crosses, Allowing Epistasis

Genetics ◽  
2008 ◽  
Vol 181 (3) ◽  
pp. 1077-1086 ◽  
Author(s):  
Ani Manichaikul ◽  
Jee Young Moon ◽  
Śaunak Sen ◽  
Brian S. Yandell ◽  
Karl W. Broman
Keyword(s):  
Quantitative Trait Loci ◽  
Model Selection ◽  
Quantitative Trait ◽  
Model Selection Approach ◽  
Selection Approach ◽  
Trait Loci ◽  
Experimental Crosses

scholarly journals Bayesian Mapping of Quantitative Trait Loci Under the Identity-by-Descent-Based Variance Component Model

Genetics ◽  
2000 ◽  
Vol 156 (1) ◽  
pp. 411-422 ◽  
Author(s):  
Nengjun Yi ◽  
Shizhong Xu
Keyword(s):  
Quantitative Trait Loci ◽  
Posterior Distribution ◽  
Quantitative Trait ◽  
Variance Component ◽  
Threshold Model ◽  
Variance Component Model ◽  
Identity By Descent ◽  
Mapping Procedure ◽  
Trait Loci ◽  
Bayesian Mapping

AbstractVariance component analysis of quantitative trait loci (QTL) is an important strategy of genetic mapping for complex traits in humans. The method is robust because it can handle an arbitrary number of alleles with arbitrary modes of gene actions. The variance component method is usually implemented using the proportion of alleles with identity-by-descent (IBD) shared by relatives. As a result, information about marker linkage phases in the parents is not required. The method has been studied extensively under either the maximum-likelihood framework or the sib-pair regression paradigm. However, virtually all investigations are limited to normally distributed traits under a single QTL model. In this study, we develop a Bayes method to map multiple QTL. We also extend the Bayesian mapping procedure to identify QTL responsible for the variation of complex binary diseases in humans under a threshold model. The method can also treat the number of QTL as a parameter and infer its posterior distribution. We use the reversible jump Markov chain Monte Carlo method to infer the posterior distributions of parameters of interest. The Bayesian mapping procedure ends with an estimation of the joint posterior distribution of the number of QTL and the locations and variances of the identified QTL. Utilities of the method are demonstrated using a simulated population consisting of multiple full-sib families.

scholarly journals Bayesian Model Selection for Genome-Wide Epistatic Quantitative Trait Loci Analysis

Genetics ◽  
2005 ◽  
Vol 170 (3) ◽  
pp. 1333-1344 ◽  
Author(s):  
Nengjun Yi ◽  
Brian S. Yandell ◽  
Gary A. Churchill ◽  
David B. Allison ◽  
Eugene J. Eisen ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Model Selection ◽  
Quantitative Trait ◽  
Bayesian Model ◽  
Bayesian Model Selection ◽  
Genome Wide ◽  
Trait Loci ◽  
Selection For

scholarly journals How to deal with genotype uncertainty in variance component quantitative trait loci analyses

2011 ◽  
Vol 93 (5) ◽  
pp. 333-342 ◽  
Author(s):  
XIA SHEN ◽  
LARS RÖNNEGÅRD ◽  
ÖRJAN CARLBORG
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Complex Traits ◽  
Variance Component ◽  
Large Animal ◽  
Trait Loci ◽  
Sib Families ◽  
Variance Component Estimates ◽  
Variance Component Models ◽  
Component Models

SummaryDealing with genotype uncertainty is an ongoing issue in genetic analyses of complex traits. Here we consider genotype uncertainty in quantitative trait loci (QTL) analyses for large crosses in variance component models, where the genetic information is included in identity-by-descent (IBD) matrices. An IBD matrix is one realization from a distribution of potential IBD matrices given available marker information. In QTL analyses, its expectation is normally used resulting in potentially reduced accuracy and loss of power. Previously, IBD distributions have been included in models for small human full-sib families. We develop an Expectation–Maximization (EM) algorithm for estimating a full model based on Monte Carlo imputation for applications in large animal pedigrees. Our simulations show that the bias of variance component estimates using traditional expected IBD matrix can be adjusted by accounting for the distribution and that the calculations are computationally feasible for large pedigrees.

Model selection in irregular problems: Applications to mapping quantitative trait loci

Biometrika ◽  
2004 ◽  
Vol 91 (4) ◽  
pp. 785-800 ◽  
Author(s):  
D. Siegmund
Keyword(s):  
Quantitative Trait Loci ◽  
Model Selection ◽  
Quantitative Trait ◽  
Trait Loci
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