Similar articles

Abstract: WOMBAT is a software package for quantitative genetic analyses of continuous traits, fitting a linear, mixed model; estimates of covariance components and the resulting genetic parameters are obtained by restricted maximum likelihood. A wide range of models, comprising numerous traits, multiple fixed and random effects, selected genetic covariance structures, random regression models and reduced rank estimation are accommodated. WOMBAT employs up-to-date numerical and computational methods. Together with the use of efficient compilers, this generates fast executable programs, suitable for large scale analyses. Use of WOMBAT is illustrated for a bivariate analysis. The package consists of the executable program, available for LINUX and WINDOWS environments, manual and a set of worked example, and can be downloaded free of charge from http://agbu.une.edu.au/~kmeyer/wombat.html

[1] Dennis, J.E., Schnabel, R.B., 1996. Numerical Methods for Unconstrained Optimization and Nonlinear Equations. SIAM Classics in Applied Mathematics. Society for Industrial and Applied Mathematics, Philadelphia.

[2] Gilmour, A.R., Gogel, D.J., Cullis, B.R., Thompson, R., 2006. ASReml User Guide Release 2.0. VSN International Ltd., Hemel Hempstead, HP1 1ES, U., p.342.

[3] Karypis, G., Kumar, V., 1998. METIS, a Software Package for Partitioning Unstructured Graphs, Partitioning Meshes, and Computing Fill-in Reducing Ordering of Sparse Matrices Version 4.0. Department of Computer Science, University of Minnesota, Minneapolis, p.44.

[4] Kovacs, M.A., Groeneveld, E., 2003. VCE-5 User’s Guide and Reference Manual, Version 5.1. Institute of Animal Husbandry and Animal Behaviour, Federal Research Center of Agriculture, Mariensee, Germany, p.68.

[5] Liu, C., Rubin, D.B., Wu, Y.N., 1998. Parameter expansions to accelerate EM: the PX-EM algorithm. Biometrika, 85(4):755-770.

[6] Madsen, P., Jensen, J., 2006. A User’s Guide to DMU: A Package for Analyzing Multivariate Mixed Models, Version 6. Danish Institute of Agricultural Sciences, Dept. of Animal Breeding and Genetics, Research Centre Foulum, 8830 Tjele, Denmark, p.27.

[7] Mäntysaari, E.A., 1999. Derivation of Multiple Trait Reduced Random Regression (RR) Model for the First Lactation Test Day Records of Milk, Protein and Fat. In: 50th Annual Meeting. Europ. Ass. Anim. Prod. Mimeo, p.8.

[8] Meyer, K., 1988. DFREML—a set of programs to estimate variance components under an individual animal model. J. Dairy Sci., 71(Suppl. 2):33-34.

[9] Meyer, K., 1991. Estimating variances and covariances for multivariate animal models by restricted maximum likelihood. Genet. Sel. Evol., 23(1):67-83.

[10] Meyer, K., 2005a. Ordering strategies to reduce computational requirements in variance component estimation. Proc. Ass. Advan. Anim. Breed. Genet., 16:282-285.

[11] Meyer, K., 2005b. Genetic principal components for live ultra-sound scan traits of Angus cattle. Anim. Sci., 81(3):337-345.

[12] Meyer, K., 2007. Multivariate analyses of carcass traits for Angus cattle fitting reduced rank and factor-analytic models. J. Anim. Breed. Genet., 124(2):50-64.

[13] Misztal, I., Perez-Encisco, M., 1993. Sparse matrix inversion for restricted maximum likelihood estimation of variance components by Expectation-Maximization. J. Dairy Sci., 76(5):1479-1483.

[14] Smith, S.P., 1995. Differentiation of the Cholesky algorithm. J. Comp. Graph. Stat., 4(2):134-147.

[15] Thompson, R., Brotherstone, S., White, I.M.S., 2005. Estimation of quantitative genetic parameters. Phil Trans. Roy. Soc. B, 360(1459):1469-1477.

[16] Tier, B., 1990. Computing inbreeding coefficients quickly. Genet. Sel. Evol., 22(4):419-425.