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Table 3 Average Pearson, Kendall and Spearman correlations and mean square error prediction from a 10-fold cross-validation based on the sire-dam double hierarchical generalized linear modela when using pedigree (\({\mathbf{A}}\)) or combined pedigree and genomic relationships (\({\mathbf{H}}\)) and standard or log-transformed phenotypes

From: Estimation of breeding values for uniformity of growth in Atlantic salmon (Salmo salar) using pedigree relationships or single-step genomic evaluation

Transformation

Relationship

Body weight

Uniformity of body weight

Pearson

MSEP

Pearson

Kendall

Spearman

MSEP

Standardized

\({\mathbf{A}}\) matrix

0.3720.013

0.7240.021

0.1920.033

0.1280.021

0.1780.030

0.6250.086

\({\mathbf{H}}\) matrix

0.4430.017

0.6820.021

0.2710.018

0.2170.017

0.3170.025

0.6080.082

Logarithm

\({\mathbf{A}}\) matrix

0.3960.019

0.8230.029

0.3780.032

0.1820.016

0.2630.023

0.9360.085

\({\mathbf{H}}\) matrix

0.4400.016

0.8130.028

0.3830.026

0.2030.014

0.2940.020

0.9440.085

  1. aThe variance components from the sire-dam double hierarchical generalized linear model were converted to the animal double hierarchical generalized linear model and were used in the 10-fold cross-validation. Relationship = relationship matrix, where \({\mathbf{A}}\) refers to pedigree-based relationship matrix and \({\mathbf{H}}\) refers to combined genotyped and non-genotyped relationship matrix. The predictability was calculated as the Pearson, Kendall and Spearman correlations between marked phenotype and predicted breeding value. MSEP was scaled by the phenotypic variance of corresponding traits