ArticleFrontiers in genetics2022
Exploring the optimal strategy of imputation from SNP array to whole-genome sequencing data in farm animals.
Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Genomic comparison reveals single-nucleotide polymorphic sites and attenuation-associated site combinations specific to Chinese live attenuated varicella-zoster virus vaccines.Human vaccines & immunotherapeutics · 2026Article
- Article
- Local Enrichment of Multi-SNP Markers Improves Genomic Prediction from Low-Density Genotyping in Pacific White Shrimp.International journal of molecular sciences · 2026Article
- Imputation in the Wild: Genome-Wide Robustness and Fine-Scale Limitations of Low-Coverage Genomes in Endangered Species.Molecular ecology resources · 2026Article
- Development and application of a 10 K low-density whole-genome SNP array for chickens.Poultry science · 2026Article
- Low-Coverage Whole-Genome Sequencing (lcWGS) in Cattle: Analysis of Potential and Prospects for Application.Animals : an open access journal from MDPI · 2025Review
- Comparison between SNP array and imputed data to estimate population structure and ROH hotspots in horse breeds.BMC genomics · 2025Article
- High Imputation Accuracy Can Be Achieved Using a Small Reference Panel in a Natural Population With Low Genetic Diversity.Molecular ecology resources · 2025Article
- Mitochondrial sequence variants: testing imputation accuracy and their association with dairy cattle milk traits.Genetics, selection, evolution : GSE · 2024Article
- Use of whole-genome sequence data for fine mapping and genomic prediction of sea louse resistance in Atlantic salmon.Frontiers in genetics · 2024Article
- Improving Genomic Prediction Accuracy in the Chinese Holstein Population by Combining with the Nordic Holstein Reference Population.Animals : an open access journal from MDPI · 2023Article
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5 authors.
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Abstract
Genotype imputation from BeadChip to whole-genome sequencing (WGS) data is a cost-effective method of obtaining genotypes of WGS variants. Beagle, one of the most popular imputation software programs, has been widely used for genotype inference in humans and non-human species. A few studies have systematically and comprehensively compared the performance of beagle versions and parameter settings of farm animals. Here, we investigated the imputation performance of three representative versions of Beagle (Beagle 4.1, Beagle 5.0, and Beagle 5.4), and the effective population size (Ne) parameter setting for three species (cattle, pig, and chicken). Six scenarios were investigated to explore the impact of certain key factors on imputation performance. The results showed that the default Ne (1,000,000) is not suitable for livestock and poultry in small reference or low-density arrays of target panels, with 2.47%-10.45% drops in accuracy. Beagle 5 significantly reduced the computation time (4.66-fold-13.24-fold) without an accuracy loss. In addition, using a large combined-reference panel or high-density chip provides greater imputation accuracy, especially for low minor allele frequency (MAF) variants. Finally, a highly significant correlation in the measures of imputation accuracy can be obtained with an MAF equal to or greater than 0.05.
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