ArticleBMC genomics2019
Bias in estimates of variance components in populations undergoing genomic selection: a simulation study.
Article in BMC genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Impact of Model Parameterisation and Variance Component Estimates on Genomic Predictions of Carcass Traits in Montana Composite Cattle.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2026Article
- Genetic Parameter Estimation for Pregnancy Loss and Their Association With Reproductive and Growth Traits in Brahman Cattle Under Extensive Tropical Conditions.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2026Article
- Article
- Estimation of (co)variance components for very large datasets and complex single-step genomic models.Genetics, selection, evolution : GSE · 2025Article
- Genotype-by-environment interaction with high-dimensional environmental data: an example in pigs.Genetics, selection, evolution : GSE · 2025Article
- Estimation of heritabilities and genetic correlations by time slices using predictivity in large genomic models.Genetics · 2025Article
- A computationally efficient algorithm to leverage average information REML for (co)variance component estimation in the genomic era.Genetics, selection, evolution : GSE · 2024Article
- Genetic Variance Estimation over Time in Broiler Breeding Programmes for Growth and Reproductive Traits.Animals : an open access journal from MDPI · 2023Article
- Selective genotyping strategies for a sib test scheme of a broiler breeder program.Genetics, selection, evolution : GSE · 2023Article
- The impact of genotyping strategies and statistical models on accuracy of genomic prediction for survival in pigs.Journal of animal science and biotechnology · 2023Article
- Impact of genomic preselection on subsequent genetic evaluations with ssGBLUP using real data from pigs.Genetics, selection, evolution : GSE · 2022Article
- Genomic Analysis, Progress and Future Perspectives in Dairy Cattle Selection: A Review.Animals : an open access journal from MDPI · 2021Review
- Current status of genomic evaluation.Journal of animal science · 2020Review
- Variance estimates are similar using pedigree or genomic relationships with or without the use of metafounders or the algorithm for proven and young animals1.Journal of animal science · 2020Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
backgroundAfter the extensive implementation of genomic selection (GS), the choice of the statistical model and data used to estimate variance components (VCs) remains unclear. A primary concern is that VCs estimated from a traditional pedigree-based animal model (P-AM) will be biased due to ignoring the impact of GS. The objectives of this study were to examine the effects of GS on estimates of VC in the analysis of different sets of phenotypes and to investigate VC estimation using different methods. Data were simulated to resemble the Danish Jersey population. The simulation included three phases: (1) a historical phase; (2) 20 years of conventional breeding; and (3) 15 years of GS. The three scenarios based on different sets of phenotypes for VC estimation were as follows: (1) Pheno
resultsIn general, both the ssGBLUP and ssBR models with all the phenotypic and genotypic information (Pheno
conclusionsThe results show that neither of the single-step models (ssGBLUP and ssBR) can precisely estimate the VCs for populations undergoing GS. Overall, the best solution for obtaining unbiased estimates of VCs is to use P-AM with phenotypes from the conventional phase or phenotypes from both the conventional and GS phases.
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Registered trials
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