Efficient Methods to Compute Genomic Predictions
TLDR
Efficient methods for processing genomic data were developed to increase reliability of estimated breeding values and to estimate thousands of marker effects simultaneously, and a blend of first- and second-order Jacobi iteration using 2 separate relaxation factors converged well for allele frequencies and effects.About:
This article is published in Journal of Dairy Science.The article was published on 2008-11-01 and is currently open access. It has received 4196 citations till now. The article focuses on the topics: Best linear unbiased prediction & Allele frequency.read more
Citations
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Multivariate genomic selection and potential of rapid indirect selection with speed breeding in spring wheat
TL;DR: An efficient breeding strategy is proposed combining SB and multivariate GS using yield-correlated SB traits for yield prediction, and the potential for early indirect SB phenotypic selection for targeted population improvement prior to trials was investigated.
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Technical Note: An R package for fitting Bayesian regularized neural networks with applications in animal breeding
TL;DR: The R package described here (brnn) implements BRNN models and extends these to include both additive and dominance effects and takes advantage of multicore architectures via a parallel computing approach using openMP (Open Multiprocessing) for the computations.
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Accounting for genetic architecture improves sequence based genomic prediction for a Drosophila fitness trait
Ulrike Ober,Wen Huang,Michael M. Magwire,Martin Schlather,Henner Simianer,Trudy F. C. Mackay +5 more
TL;DR: The predictive ability of the genomic best linear unbiased prediction model is markedly improved when it is combined with quantitative trait locus mapping with genomic prediction by only including the top variants associated with main and epistatic effects in the relationship matrix.
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Genome-wide estimates of coancestry, inbreeding and effective population size in the Spanish Holstein population.
Silvia T. Rodríguez-Ramilo,Jesús J. Fernández,Miguel Toro,Delfino Hernández,Beatriz Villanueva +4 more
TL;DR: Genomic estimates of coancestry, inbreeding and effective population size were obtained in the Spanish Holstein population and then compared with pedigree-based estimates, indicating the need of controlling the rate of increase of coANCestry and inbreeding in Holstein selection programmes.
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Accuracy of genotype imputation and genomic predictions in a two-generation farmed Atlantic salmon population using high-density and low-density SNP panels
Grazyella Massako Yoshida,Grazyella Massako Yoshida,Roberto Carvalheiro,Jean P. Lhorente,Katharina Correa,Rene Figueroa,Ross D. Houston,José M. Yáñez +7 more
TL;DR: The high imputation and genomic prediction accuracy suggest that the imputation of genotypes from low density to high density could be a cost-effective strategy for the feasibility of the practical implementation of genomic selection in Atlantic salmon.
References
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Prediction of Total Genetic Value Using Genome-Wide Dense Marker Maps
TL;DR: It was concluded that selection on genetic values predicted from markers could substantially increase the rate of genetic gain in animals and plants, especially if combined with reproductive techniques to shorten the generation interval.
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Coefficients of Inbreeding and Relationship
TL;DR: The importance of having a coefficient by means of which the degree of inbreeding may be expressed has been brought out by Pearl' in a number of papers published between 1913 and 1917.
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Strategy for applying genome-wide selection in dairy cattle.
TL;DR: Genome-wide selection may become a popular tool for genetic improvement in livestock after a strategy that utilizes these advantages was compared with a traditional progeny testing strategy under a typical Canadian-like dairy cattle situation.
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Derivation, calculation, and use of national animal model information.
Paul M. VanRaden,G.R. Wiggans +1 more
TL;DR: New terms and definitions were developed to explain national USDA genetic evaluations computed by an animal model, whereiability is the squared correlation of predicted and true transmitting ability.
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Accuracy of Genomic Selection Using Different Methods to Define Haplotypes
TL;DR: It was concluded that genomic selection is considerably more accurate than traditional selection, especially for a low-heritability trait.