Estimated marginal posterior mean for variance components and major gene parameters of <i>ln</i>(SI) using polygenic and mixed inheritance models in Bayesian segregation analysis¹.

1Bayesian segregation analysis of ln(SI) performed with software iBay version 1.46 [20]. The Gibbs sampler had these characteristics: number of iterations per chain = 1,200,000; burn-in period = 600,000; thinning = 10,000; collected samples per chain = 60; total chains = 20; and total collected samples = 1,200. 2Model parameters: error variance ; polygenic variance ; major gene variance ; major gene additive effect ; major gene dominance effect ; is frequency of spleen size-decreasing allele A1; is the polygenic model heritability ; and transmission probabilities defined as the probability that a parent with any of the three genotypes transmits the allele to its offspring. 3loge of the marginal density under the fitted model Hi. 4Bayes factor BF(H2; H1) = p(y/H2)/p(y/H1) is the ratio of the marginal likelihood under one model to the marginal likelihood under a second model, and H1 and H2 are the two competing models. 5Value between squared brackets indicates the parameter was fixed to the value shown.