• Beaumont, M. A., and B. Rannala. 2004. The Bayesian revolution in genetics. Nat. Rev. Genet. 5:251261.
  • Blouin, M. S. 2003. DNA-based methods for pedigree reconstruction and kinship analysis in natural populations. Trends Ecol. Evol. 18:503511.
  • Damgaard, L. H. 2007. How to use WinBUGS to draw inferences in animal models. J. Anim. Sci. 85:13631368.
  • Gelfand, A. E., and A. F. M. Smith. 1990. Sampling-based approaches to calculating marginal densities. J. Am. Stat. Ass. 85:398409.
  • Gelman, A. 2006. Prior distributions for variance parameters in hierarchical models. Bay. Anal. 1:515534.
  • Geman, S., and D. Geman. 1984. Stochastic relaxation, Gibbs distributions and Bayesian restoration of images. IEEE Trans. Patt. Anal. Mach. Intell. 6:721741.
  • Falconer, D. S., and T. F. C. Mackay. 1996. Introduction to quantitative genetics. Longman, New York .
  • Gilks, W. R., S. Richardson, and D. J. Spiegelhalter. 1996. Markov chain Monte Carlo in practice. Chapman & Hall /CRC, London , UK .
  • Henderson, C.R. 1976. A simple method for computing the inverse of a numerator relationship matrix used in prediction of breeding values. Biometrics 32:6983.
  • Kass, R.E., B. P. Carlin, A. Gelman, and R. Neal. 1998. Markov Chain Monte Carlo in practice: a roundtable discussion. Am. Stat. 52:93100.
  • Lin, S. 1999. Monte Carlo Bayesian methods for quantitative traits. Comp. Stat. Data Anal. 31:89108.
  • Lunn, D.J., A. Thomas, N. Best, and D. Spiegelhalter. 2000. WinBUGS – a Bayesian modelling framework: concepts, structure, and extensibility. Stat. Comp. 10:325337.
  • Lynch, M., and B. Walsh. 1998. Genetics and analysis of quantitative traits. Sinauer Associates, Sunderland , MA .
  • Misztal, I., S. Tsuruta, T. Strabel, B. Auvray, T. Druet, and D. H. Lee. 2002. BLUPF90 and related programs (BGF90). Proceedings of 7th world congress of genetics applied to livestock production. Montpellier , France . Communication No. 28-07.
  • O'Hara, R. B., J. M. Cano, O. Ovaskainen, C. Teplitsky, and J. S. Alho. 2008. Bayesian approaches in evolutionary quantitative genetics. J. Evol. Biol. 21:949957.
  • Sorensen, D., and D. Gianola. 2002. Likelihood, Bayesian and MCMC methods in quantitative genetics. Springer-Verlag, New York .
  • Sorensen, D. A., C. S. Wang, J. Jensen, and D. Gianola. 1994. Bayesian analysis of genetic change due to selection using Gibbs sampling. Genet. Sel. Evol. 26:333360.
  • Van Tassel, C. P., and L. D. Van Vleck. 1996. Multiple-trait Gibbs sampler for animal models: flexible programs for Bayesian and likelihood-based (co)variance component inference. J. Anim. Sci. 74:25862597.
  • Waldmann, P., J. Hallander, F. Hoti, and M. J. Sillanpää. 2008. Efficient Markov chain Monte Carlo implementation of Bayesian analysis of additive and dominance genetic variances in noninbred pedigrees. Genetics 179:11011112.
  • Wang, C. S., J. J. Rutledge, and D. Gianola. 1993. Marginal inference about variance components in a mixed linear model using Gibbs sampling. Genet. Sel. Evol. 21:4162.