Adjusting for Spatial Effects in Genomic Prediction Academic Article

abstract

• This paper investigates the problem of adjusting for spatial effects in genomic prediction. Despite being seldomly considered in genomic prediction, spatial effects often affect phenotypic measurements of plants. We consider a Gaussian random field model with an additive covariance structure that incorporates genotype effects, spatial effects and subpopulation effects. An empirical study shows the existence of spatial effects and heterogeneity across different subpopulation families, while simulations illustrate the improvement in selecting genotypically superior plants by adjusting for spatial effects in genomic prediction.

authors

• Wong, Raymond Ka Wai

published proceedings

• JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS

altmetric score

• 1.5

author list (cited authors)

• Mao, X., Dutta, S., Wong, R., & Nettleton, D.

citation count

• 9

complete list of authors

• Mao, Xiaojun||Dutta, Somak||Wong, Raymond KW||Nettleton, Dan

publication date

• December 2020

publisher

• Springer Nature  Publisher

published in

• Journal of Agricultural, Biological, and Environmental Statistics  Journal

keywords

• Gaussian Random Field
• Genomic Prediction
• Spatial Effects
• Subpopulation Effects

Digital Object Identifier (DOI)

• 10.1007/s13253-020-00396-1

start page

• 699

end page

• 718

volume

• 25

issue

• 4

URL

• http://dx.doi.org/10.1007/s13253-020-00396-1