Efficient strategies for leave-one-out cross validation for genomic best linear unbiased prediction

BACKGROUND: A random multiple-regression model that simultaneously fit all allele substitution effects for additive markers or haplotypes as uncorrelated random effects was proposed for Best Linear Unbiased Prediction, using whole-genome data. Leave-one-out cross validation can be used to quantify t...

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Detalles Bibliográficos
Autores principales: Cheng, Hao, Garrick, Dorian J., Fernando, Rohan L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Methodology Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5414316/
https://www.ncbi.nlm.nih.gov/pubmed/28469846
http://dx.doi.org/10.1186/s40104-017-0164-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5414316/
https://www.ncbi.nlm.nih.gov/pubmed/28469846
http://dx.doi.org/10.1186/s40104-017-0164-6

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