Subject: bepress|Life Sciences|Biology | bepress|Life Sciences|Genetics and Genomics|Genetics
A popular strategy (EMMAX) for genome wide association (GWA) analysis fits all marker effects as classical random effects (i.e., Gaussian prior) by which association for the specific marker of interest is inferred by treating its effect as fixed. It seems more statistic... View more
Andrews, D. F., and C. L. Mallows, 1974 Scale mixtures of normal distributions. J R Stat Soc Series B Methodol 36: 99-102.
Bello, N. M., J. P. Steibel and R. J. Tempelman, 2010 Hierarchical Bayesian modeling of random and residual variance-covariance matrices in bivariate mixed effects models. Biom J 52: 297-313.
Bernal Rubio, Y. L., J. L. Gualdron Duarte, R. O. Bates, C. W. Ernst, D. Nonneman et al., 2016 Metaanalysis of genome-wide association from genomic prediction models. Anim. Genet. 47: 36-48.
Calus, M. P., J. Vandenplas and J. Ten Napel, 2015 Ever-growing data sets pose (new) challenges to genomic prediction models. J. Anim. Breed. Genet. 132: 407-408.
Chen, C., and R. J. Tempelman, 2015 An integrated approach to empirical Bayesian whole genome prediction modeling. J. Agric. Biol. Environ. Stat. 20: 491-511.
Colombani, C., A. Legarra, S. Fritz, F. Guillaume, P. Croiseau et al., 2013 Application of Bayesian least absolute shrinkage and selection operator (LASSO) and BayesCpi methods for genomic selection in French Holstein and Montbeliarde breeds. J. Dairy Sci. 96: 575-591.
Cuyabano, B. C., G. Su and M. S. Lund, 2014 Genomic prediction of genetic merit using LD-based haplotypes in the Nordic Holstein population. BMC Genomics 15: 1171.
de Los Campos, G., J. M. Hickey, R. Pong-Wong, H. D. Daetwyler and M. P. Calus, 2013 Wholegenome regression and prediction methods applied to plant and animal breeding. Genetics 193: 327-345.
Dehman, A., C. Ambroise and P. Neuvial, 2015 Performance of a blockwise approach in variable selection using linkage disequilibrium information. BMC Bioinformatics 16: 148.
Dehman, A., and P. Neuvial, 2015 BALD: Blockwise Approach using Linkage Disequilibrium information. R package version 0.2.1.