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

摘要

BackgroundNoise (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 the impact of noisy data on genomic predictions, a widely used statistical application in plant and animal breeding.