Found 106 results
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Forneris NS, Vitezica ZG, Legarra A, Perez-Enciso M. Influence of epistasis on response to genomic selection using complete sequence data. Genet Sel Evol. 2017;49(1):66. doi:10.1186/s12711-017-0340-3.
Misztal I, Legarra A. Invited review: efficient computation strategies in genomic selection. Animal. 2017;11(5):731-736. doi:10.1017/S1751731116002366.
Vitezica ZG, Legarra A, Toro MA, Varona L. Orthogonal estimates of variances for additive, dominance, and epistatic effects in populations. Genetics. 2017;206(3):1297-1307.
Fernández EN, Legarra A, Martínez R, Sánchez JP, Baselga M. Pedigree-based estimation of covariance between dominance deviations and additive genetic effects in closed rabbit lines considering inbreeding and using a computationally simpler equivalent model. J Anim Breed Genet. 2017;134(3):184-195. doi:10.1111/jbg.12267.
Fernández EN, Sánchez JP, Martínez R, Legarra A, Baselga M. Role of inbreeding depression, non-inbred dominance deviations and random year-season effect in genetic trends for prolificacy in closed rabbit lines. J Anim Breed Genet. 2017;134(6):441-452. doi:10.1111/jbg.12284.
Perez-Rodriguez P, Crossa J, Rutkoski J, et al. Single-Step Genomic and Pedigree Genotype x Environment Interaction Models for Predicting Wheat Lines in International Environments. Plant Genome. 2017;10(2):Non paginé.
Pérez-Rodríguez P, Crossa J, Rutkoski J, et al. Single-Step Genomic and Pedigree Genotype × Environment Interaction Models for Predicting Wheat Lines in International Environments. Plant Genome. 2017;10(2). doi:10.3835/plantgenome2016.09.0089.
Masuda Y, Misztal I, Legarra A, et al. Technical note: Avoiding the direct inversion of the numerator relationship matrix for genotyped animals in single-step genomic best linear unbiased prediction solved with the preconditioned conjugate gradient. J Anim Sci. 2017;95(1):49-52. doi:10.2527/jas.2016.0699.
Xiang T, Christensen OF, Legarra A. Technical note: Genomic evaluation for crossbred performance in a single-step approach with metafounders. J Anim Sci. 2017;95(4):1472-1480. doi:10.2527/jas.2016.1155.
Xiang T, Nielsen B, Su G, Legarra A, Christensen OF. Application of single-step genomic evaluation for crossbred performance in pig. J Anim Sci. 2016;94(3):936-48. doi:10.2527/jas.2015-9930.
Pérez-Enciso M, Legarra A. A combined coalescence gene-dropping tool for evaluating genomic selection in complex scenarios (ms2gs). J Anim Breed Genet. 2016;133(2):85-91. doi:10.1111/jbg.12200.
Legarra A. Comparing estimates of genetic variance across different relationship models. Theor Popul Biol. 2016;107:26-30. doi:10.1016/j.tpb.2015.08.005.
Pocrnic I, Lourenco DAL, Masuda Y, Legarra A, Misztal I. The Dimensionality of Genomic Information and Its Effect on Genomic Prediction. Genetics. 2016;203(1):573-81. doi:10.1534/genetics.116.187013.
Vitezica ZG, Varona L, Elsen J-M, Misztal I, Herring W, Legarra A. Genomic BLUP including additive and dominant variation in purebreds and F1 crossbreds, with an application in pigs. Genet Sel Evol. 2016;48(1):6. doi:10.1186/s12711-016-0185-1.
Xiang T, Christensen OF, Vitezica ZG, Legarra A. Genomic evaluation by including dominance effects and inbreeding depression for purebred and crossbred performance with an application in pigs. Genetics Selection Evolution. 2016;48(92):1-14.
Astruc JM, Baloche G, Buisson D, et al. Genomic selection in French dairy sheep. INRA Productions Animales. 2016;29(1):41-55.
Astruc JM, Baloche G, Buisson D, et al. La sélection génomique des ovins laitiers en France. INRA Productions Animales. 2016;29(1):41-56.
Tusell L, Gilbert H, Riquet J, Mercat MJ, Legarra A, C. L. Pedigree and genomic evaluation of pigs using a terminal-cross model. Genetics Selection Evolution. 2016;48(32):1-12.
Zhang X, Lourenco D, Aguilar I, Legarra A, Misztal I. Weighting Strategies for Single-Step Genomic BLUP: An Iterative Approach for Accurate Calculation of GEBV and GWAS. Front Genet. 2016;7:151. doi:10.3389/fgene.2016.00151.