ArticleJournal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie2022
Accuracy of genomic prediction of maternal traits in pigs using Bayesian variable selection methods.
Article in Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 8 citations in OpenAlex.
- Establishment and validation of porcine embryo genomic selection system through SCNT technique.Journal of animal science and biotechnology · 2026Article
- Genomic Selection for Milk Yield and Milk Composition Traits in Dairy Goats Using Machine Learning and Prior-Information Models.Animals : an open access journal from MDPI · 2026Article
- Impact of QTL number, heritability and reference population size on the benefit of machine learning models over GBLUP in genomic prediction.Genetics, selection, evolution : GSE · 2026Article
- Review
- A Comparative Study of Optimizing Genomic Prediction Accuracy in Commercial Pigs.Animals : an open access journal from MDPI · 2025Article
- Progress in serology and molecular biology of equine parasite diagnosis: sustainable control strategies.Frontiers in veterinary science · 2025Review
- Transgenerational epigenetic heritability for growth, body composition, and reproductive traits in Landrace pigs.Frontiers in genetics · 2024Article
- Accuracy of genomic prediction of maternal traits in pigs using Bayesian variable selection methods.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2022Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
The aim of this study was to compare three methods of genomic prediction: GBLUP, BayesC and BayesGC for genomic prediction of six maternal traits in Landrace sows using a panel of 660 K SNPs. The effects of different priors for the Bayesian methods were also investigated. GBLUP does not take the genetic architecture into account as all SNPs are assumed to have equally sized effects and relies heavily on the relationships between the animals for accurate predictions. Bayesian approaches rely on both fitting SNPs that describe relationships between animals in addition to fitting single SNP effects directly. Both the relationship between the animals and single SNP effects are important for accurate predictions. Maternal traits in sows are often more difficult to record and have lower heritabilities. BayesGC was generally the method with the higher accuracy, although its accuracy was for some traits matched by that of GBLUP and for others by that of BayesC. For piglet mortality within 3 weeks, BayesGC achieved up to 9.2% higher accuracy. For many of the traits, however, the methods did not show significant differences in accuracies.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.