Prediction of Complex Traits: Robust Alternatives to Best Linear Unbiased Prediction.

ABSTRACT: A widely used method for prediction of complex traits in animal and plant breeding is "genomic best linear unbiased prediction" (GBLUP). In a quantitative genetics setting, BLUP is a linear regression of phenotypes on a pedigree or on a genomic relationship matrix, depending on the type of input information available. Normality of the distributions of random effects and of model residuals is not required for BLUP but a Gaussian assumption is made implicitly. A potential downside is that Gaussian linear regressions are sensitive to outliers, genetic or environmental in origin. We present simple (relative to a fully Bayesian analysis) to implement robust alternatives to BLUP using a linear model with residual t or Laplace distributions instead of a Gaussian one, and evaluate the metho

SUBMITTER: Gianola D 

PROVIDER: S-EPMC6008589 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature