A Monte Carlo method for Bayesian analysis of linkage between single markers and quantitative trait loci. II. A simulation study

1996 ◽  
Vol 93 (7) ◽  
pp. 1167-1174 ◽  
Author(s):  
G. Thaller ◽  
I. Hoeschele
Keyword(s):  
Monte Carlo ◽  
Quantitative Trait Loci ◽  
Monte Carlo Method ◽  
Bayesian Analysis ◽  
Simulation Study ◽  
Quantitative Trait ◽  
Trait Loci

scholarly journals On the Detection of Imprinted Quantitative Trait Loci in Experimental Crosses of Outbred Species

Genetics ◽  
2002 ◽  
Vol 161 (2) ◽  
pp. 931-938
Author(s):  
Dirk-Jan de Koning ◽  
Henk Bovenhuis ◽  
Johan A M van Arendonk
Keyword(s):  
Quantitative Trait Loci ◽  
Simulation Study ◽  
Quantitative Trait ◽  
Statistical Properties ◽  
Imprinted Genes ◽  
Quantitative Genetic ◽  
Trait Loci ◽  
Experimental Crosses

Abstract In this article, the quantitative genetic aspects of imprinted genes and statistical properties of methods to detect imprinted QTL are studied. Different models to detect imprinted QTL and to distinguish between imprinted and Mendelian QTL were compared in a simulation study. Mendelian and imprinted QTL were simulated in an F2 design and analyzed under Mendelian and imprinting models. Mode of expression was evaluated against the H0 of a Mendelian QTL as well as the H0 of an imprinted QTL. It was shown that imprinted QTL might remain undetected when analyzing the genome with Mendelian models only. Compared to testing against a Mendelian QTL, using the H0 of an imprinted QTL gave a higher proportion of correctly identified imprinted QTL, but also gave a higher proportion of false inference of imprinting for Mendelian QTL. When QTL were segregating in the founder lines, spurious detection of imprinting became more prominent under both tests, especially for designs with a small number of F1 sires.

scholarly journals Mapping-Linked Quantitative Trait Loci Using Bayesian Analysis and Markov Chain Monte Carlo Algorithms

Genetics ◽  
1997 ◽  
Vol 146 (2) ◽  
pp. 735-743 ◽  
Author(s):  
Pekka Uimari ◽  
Ina Hoeschele
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Markov Chain Monte Carlo ◽  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Allele Frequencies ◽  
Mcmc Methods ◽  
Substitution Effects ◽  
Indicator Variable ◽  
Trait Loci

A Bayesian method for mapping linked quantitative trait loci (QTL) using multiple linked genetic markers is presented. Parameter estimation and hypothesis testing was implemented via Markov chain Monte Carlo (MCMC) algorithms. Parameters included were allele frequencies and substitution effects for two biallelic QTL, map positions of the QTL and markers, allele frequencies of the markers, and polygenic and residual variances. Missing data were polygenic effects and multi-locus marker-QTL genotypes. Three different MCMC schemes for testing the presence of a single or two linked QTL on the chromosome were compared. The first approach includes a model indicator variable representing two unlinked QTL affecting the trait, one linked and one unlinked QTL, or both QTL linked with the markers. The second approach incorporates an indicator variable for each QTL into the model for phenotype, allowing or not allowing for a substitution effect of a QTL on phenotype, and the third approach is based on model determination by reversible jump MCMC. Methods were evaluated empirically by analyzing simulated granddaughter designs. All methods identified correctly a second, linked QTL and did not reject the one-QTL model when there was only a single QTL and no additional or an unlinked QTL.

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