ArticlePloS one2017
Estimation of genomic prediction accuracy from reference populations with varying degrees of relationship.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.
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Who cites it
48 citing papers in PubMed.
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- Strategic global data integration to improve genomic prediction accuracy in tree breeding programs facing resource limitations, a case study in mango.Horticulture research · 2026Article
- Sharing approaches in predictive genomics across animals, plants and humans.Nature genetics · 2026Review
- Predicting maize hybrid performance with machine learning and a locus-specific weighted degree of dominance transformation.Frontiers in plant science · 2026Article
- Evaluation of genomic breeding values and accuracy for carcass traits in Korean Hanwoo cows using whole-genome SNP chip panels.Mammalian genome : official journal of the International Mammalian Genome Society · 2025Article
- Improving wheat grain yield genomic prediction accuracy using historical data.G3 (Bethesda, Md.) · 2025Article
- Improved genomic prediction accuracy by genetic relatedness using a crossbred pig population.Translational animal science · 2025Article
- Endophenotype 2.0: updated definitions and criteria for endophenotypes of psychiatric disorders, incorporating new technologies and findings.Translational psychiatry · 2024Review
- Validation of cross-progeny variance genomic prediction using simulations and experimental data in winter elite bread wheat.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Review
- Integrative polygenic risk score improves the prediction accuracy of complex traits and diseases.Cell genomics · 2024Article
- Expected values for the accuracy of predicted breeding values accounting for genetic differences between reference and target populations.Genetics, selection, evolution : GSE · 2024Article
- A versatile, fast and unbiased method for estimation of gene-by-environment interaction effects on biobank-scale datasets.Nature communications · 2023Article
- Comparison of accuracy of breeding value for cow from three methods in Hanwoo (Korean cattle) population.Journal of animal science and technology · 2023Article
- Integrative polygenic risk score improves the prediction accuracy of complex traits and diseases.medRxiv : the preprint server for health sciences · 2023Article
- Utilizing Variants Identified with Multiple Genome-Wide Association Study Methods Optimizes Genomic Selection for Growth Traits in Pigs.Animals : an open access journal from MDPI · 2023Article
- An effective hyper-parameter can increase the prediction accuracy in a single-step genetic evaluation.Frontiers in genetics · 2023Article
- Sparse testing using genomic prediction improves selection for breeding targets in elite spring wheat.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Genomic prediction is emerging in a wide range of fields including animal and plant breeding, risk prediction in human precision medicine and forensic. It is desirable to establish a theoretical framework for genomic prediction accuracy when the reference data consists of information sources with varying degrees of relationship to the target individuals. A reference set can contain both close and distant relatives as well as 'unrelated' individuals from the wider population in the genomic prediction. The various sources of information were modeled as different populations with different effective population sizes (Ne). Both the effective number of chromosome segments (Me) and Ne are considered to be a function of the data used for prediction. We validate our theory with analyses of simulated as well as real data, and illustrate that the variation in genomic relationships with the target is a predictor of the information content of the reference set. With a similar amount of data available for each source, we show that close relatives can have a substantially larger effect on genomic prediction accuracy than lesser related individuals. We also illustrate that when prediction relies on closer relatives, there is less improvement in prediction accuracy with an increase in training data or marker panel density. We release software that can estimate the expected prediction accuracy and power when combining different reference sources with various degrees of relationship to the target, which is useful when planning genomic prediction (before or after collecting data) in animal, plant and human genetics.
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