“Noisy beets”: impact of phenotyping errors on genomic predictions for binary traits in Beta vulgaris

BACKGROUND: Noise (errors) in scientific data is endemic and may have a detrimental effect on statistical analyses and experimental results. The effects of noisy data have been assessed in genome-wide association studies for case-control experiments in human medicine. Little is known, however, on th...

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Detalles Bibliográficos
Autores principales: Biscarini, Filippo, Nazzicari, Nelson, Broccanello, Chiara, Stevanato, Piergiorgio, Marini, Simone
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Methodology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4949885/
https://www.ncbi.nlm.nih.gov/pubmed/27437026
http://dx.doi.org/10.1186/s13007-016-0136-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4949885/
https://www.ncbi.nlm.nih.gov/pubmed/27437026
http://dx.doi.org/10.1186/s13007-016-0136-4

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