Maximum Likelihood Analysis of Rare Binary Traits under Different Modes of Inheritance
AUTOR(ES)
Thaller, G.
RESUMO
Maximum likelihood methodology was applied to determine the mode of inheritance of rare binary traits with data structures typical for swine populations. The genetic models considered included a monogenic, a digenic, a polygenic, and three mixed polygenic and major gene models. The main emphasis was on the detection of major genes acting on a polygenic background. Deterministic algorithms were employed to integrate and maximize likelihoods. A simulation study was conducted to evaluate model selection and parameter estimation. Three designs were simulated that differed in the number of sires/number of dams within sires (10/10, 30/30, 100/30). Major gene effects of at least one SD of the liability were detected with satisfactory power under the mixed model of inheritance, except for the smallest design. Parameter estimates were empirically unbiased with acceptable standard errors, except for the smallest design, and allowed to distinguish clearly between the genetic models. Distributions of the likelihood ratio statistic were evaluated empirically, because asymptotic theory did not hold. For each simulation model, the Average Information Criterion was computed for all models of analysis. The model with the smallest value was chosen as the best model and was equal to the true model in almost every case studied.
ACESSO AO ARTIGO
http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1207442Documentos Relacionados
- Using rare mutations to estimate population divergence times: A maximum likelihood approach
- Maximum Likelihood Analysis of Population Differences in Allelic Frequencies
- Evolutionary analysis of apolipoprotein E by Maximum Likelihood and complex network methods
- Maximum Likelihood Estimation of Population Parameters
- Bayesian and maximum likelihood phylogenetic analyses of protein sequence data under relative branch-length differences and model violation