Estimated marginal posterior mean for variance components and major gene parameters of ln(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.