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A nested mixture model for genomic prediction using whole-genome SNP genotypes
Genomic prediction exploits single nucleotide polymorphisms (SNPs) across the whole genome for predicting genetic merit of selection candidates. In most models for genomic prediction, e.g. BayesA, B, C, R and GBLUP, independence of SNP effects is assumed. However, SNP effects are expected to be loca...
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| Publié dans: | PLoS One |
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| Auteurs principaux: | , , , |
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
Public Library of Science
2018
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| Sujets: | |
| Accès en ligne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5862491/ https://ncbi.nlm.nih.gov/pubmed/29561877 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0194683 |
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