Comparison of REML and Gibbs sampling estimates of multi-trait genetic parameters in Scots pine.
Multi-trait (co)variance estimation is an important topic in plant and animal breeding. In this study we compare estimates obtained with restricted maximum likelihood (REML) and Bayesian Gibbs sampling of simulated data and of three traits (diameter, height and branch angle) from a 26-year-old partial diallel progeny test of Scots pine (Pinus sylvestris L.). Based on the results from the simulated data we can conclude that the REML estimates are accurate but the mode of posterior distributions from the Gibbs sampling can be overestimated depending on the level of the heritability. The mean and median of the posteriors were considerably higher than the expected values of the heritabilities. The confidence intervals calculated with the delta method were biased downwardly. The highest probability density (HPD) interval provides a better interval estimate, but could be slightly biased at the lower level. Similar differences between REML and Gibbs sampling estimates were found for the Scots pine data. We conclude that further simulation studies are needed in order to evaluate the effect of different priors on (co)variance components in the genetic individual model.
Department of Forest Genetics and Plant Physiology, SLU, 901 83, Umeå, Sweden. Patrik.Waldmann@genfys.slu.se
Patrik
P
Waldmann
Tore
T
Ericsson
D000704:Analysis of Variance; D001499:Bayes Theorem; D003198:Computer Simulation; D016001:Confidence Intervals; D006824:Hybridization, Genetic; D016013:Likelihood Functions; D015233:Models, Statistical; D015999:Multivariate Analysis; D041605:Pinus sylvestris / Q000235:genetics*; D019655:Quantitative Trait, Heritable; D012494:Sampling Studies