Publications
Found 100 results
Filters: Author is Andres Legarra [Clear All Filters]
Behavior of the Linear Regression method to estimate bias and accuracies with correct and incorrect genetic evaluation models. J Dairy Sci. 2020;103(1):529-544. doi:10.3168/jds.2019-16603.
. Effects of ignoring inbreeding in model-based accuracy for BLUP and SSGBLUP. J Anim Breed Genet. 2020. doi:10.1111/jbg.12470.
. Alternative SNP weighting for single-step genomic best linear unbiased predictor evaluation of stature in US Holsteins in the presence of selected sequence variants. J Dairy Sci. 2019;102(11):10012-10019. doi:10.3168/jds.2019-16262.
. Dissecting total genetic variance into additive and dominance components of purebred and crossbred pig traits. Animal. 2019;13(11):2429-2439. doi:10.1017/S1751731119001046.
. Frequentist p-values for large-scale-single step genome-wide association, with an application to birth weight in American Angus cattle. Genet Sel Evol. 2019;51(1):28. doi:10.1186/s12711-019-0469-3.
. Inbreeding and effective population size in French dairy sheep: Comparison between genomic and pedigree estimates. J Dairy Sci. 2019;102(5):4227-4237. doi:10.3168/jds.2018-15405.
. Modeling missing pedigree in single-step genomic BLUP. J Dairy Sci. 2019;102(3):2336-2346. doi:10.3168/jds.2018-15434.
. Dominance and epistatic genetic variances for litter size in pigs using genomic models. Genet Sel Evol. 2018;50(1):71. doi:10.1186/s12711-018-0437-3.
. Genomic Model with Correlation Between Additive and Dominance Effects. Genetics. 2018;209(3):711-723. doi:10.1534/genetics.118.301015.
. Genomic selection models for directional dominance: an example for litter size in pigs. Genet Sel Evol. 2018;50(1):1. doi:10.1186/s12711-018-0374-1.
. GWAS by GBLUP: Single and Multimarker EMMAX and Bayes Factors, with an Example in Detection of a Major Gene for Horse Gait. G3 (Bethesda). 2018;8(7):2301-2308. doi:10.1534/g3.118.200336.
. Non-additive Effects in Genomic Selection. Front Genet. 2018;9:78. doi:10.3389/fgene.2018.00078.
. Semi-parametric estimates of population accuracy and bias of predictions of breeding values and future phenotypes using the LR method. Genet Sel Evol. 2018;50(1):53. doi:10.1186/s12711-018-0426-6.
. Erratum to: Incorporation of causative quantitative trait nucleotides in single-step GBLUP. Genet Sel Evol. 2017;49(1):65. doi:10.1186/s12711-017-0341-2.
. Estimates of the actual relationship between half-sibs in a pig population. J Anim Breed Genet. 2017;134(2):109-118. doi:10.1111/jbg.12236.
Evaluating Sequence-Based Genomic Prediction with an Efficient New Simulator. Genetics. 2017;205(2):939-953. doi:10.1534/genetics.116.194878.
. A fast indirect method to compute functions of genomic relationships concerning genotyped and ungenotyped individuals, for diversity management. Genet Sel Evol. 2017;49(1):87. doi:10.1186/s12711-017-0363-9.
. Genetic Variation in the Social Environment Contributes to Health and Disease. PLoS Genet. 2017;13(1):e1006498. doi:10.1371/journal.pgen.1006498.
Incorporation of causative quantitative trait nucleotides in single-step GBLUP. Genet Sel Evol. 2017;49(1):59. doi:10.1186/s12711-017-0335-0.
. 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.
. Invited review: efficient computation strategies in genomic selection. Animal. 2017;11(5):731-736. doi:10.1017/S1751731116002366.
. Orthogonal estimates of variances for additive, dominance, and epistatic effects in populations. Genetics. 2017;206(3):1297-1307.
. 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.
. 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.
. Single-Step Genomic and Pedigree Genotype x Environment Interaction Models for Predicting Wheat Lines in International Environments. Plant Genome. 2017;10(2):Non paginé.