B
Bruce Tier
Researcher at University of New England (Australia)
Publications - 118
Citations - 3086
Bruce Tier is an academic researcher from University of New England (Australia). The author has contributed to research in topics: Population & Beef cattle. The author has an hindex of 25, co-authored 117 publications receiving 2797 citations. Previous affiliations of Bruce Tier include University of New England (United States) & New South Wales Department of Primary Industries.
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Journal ArticleDOI
A Derivative-Free Approach for Estimating Variance Components in Animal Models by Restricted Maximum Likelihood
Journal ArticleDOI
A Multi-Trait, Meta-analysis for Detecting Pleiotropic Polymorphisms for Stature, Fatness and Reproduction in Beef Cattle
Sunduimijid Bolormaa,Jennie E. Pryce,Antonio Reverter,Yuandan Zhang,William Barendse,Kathryn E. Kemper,Bruce Tier,Keith W. Savin,Ben J. Hayes,Michael E. Goddard +9 more
TL;DR: It is demonstrated that the multi-trait method can be used to increase the power (numbers of SNPs validated in an independent population) of GWAS in a beef cattle data set including 10,191 animals genotyped for 729,068 SNPs with 32 traits recorded, including growth and reproduction traits.
Journal ArticleDOI
A comparison of five methods to predict genomic breeding values of dairy bulls from genome-wide SNP markers
TL;DR: Four methods which use information from all SNP namely RR-BLUP, Bayes-R, PLSR and SVR generate similar accuracies of MBV prediction for genomic selection, and their use in the selection of immediate future generations in dairy cattle will be comparable.
Journal ArticleDOI
A phasing and imputation method for pedigreed populations that results in a single-stage genomic evaluation
John M. Hickey,Brian Kinghorn,Bruce Tier,Julius H. J. van der Werf,Julius H. J. van der Werf,Matthew A Cleveland +5 more
TL;DR: The developed imputation algorithm and software and the resulting single-stage genomic evaluation method provide powerful new ways to exploit imputation and to obtain more accurate genetic evaluations.
Journal ArticleDOI
Accuracy of prediction of genomic breeding values for residual feed intake and carcass and meat quality traits in Bos taurus, Bos indicus, and composite beef cattle.
S. Bolormaa,Jennie E. Pryce,Kathryn E. Kemper,Keith W. Savin,Ben J. Hayes,William Barendse,Yuandan Zhang,Coralie M. Reich,Brett A. Mason,Rowan J. Bunch,Blair E. Harrison,Antonio Reverter,Robert M Herd,Bruce Tier,H. U. Graser,Michael E. Goddard +15 more
TL;DR: In this article, the authors assess the accuracy of genomic predictions for 19 traits including feed efficiency, growth, and carcass and meat quality traits in beef cattle, using two methods of genomic prediction (BayesR and genomic BLUP) either using a common training dataset for all breeds or using a training dataset comprising only animals of the same breed.