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Table 5 Regression coefficients of deregressed proofs on genomic predictions based on four datasets a with or without X chromosome markers, using different models b and averaged over 15 traits

From: Genomic relationships based on X chromosome markers and accuracy of genomic predictions with and without X chromosome markers

Datasets G(A) G(A + X) Gc(A + X) G(A) + G(X) G(A) + Pol Gc(A + X) + Pol
54K_real 0.881 0.885 0.885 0.885 0.918 0.919
IMP_test 0.881 0.885 0.885 0.885 0.918 0.919
IMP_0.5ref 0.881 0.886 0.885 0.886 0.920 0.922
LD_real 0.834 0.835 0.837 0.838 0.914 0.915
  1. a54K_real: all animals with marker data from the 54K chip; IMP_test: for the test animals in genomic prediction, the 54K marker data were imputed from LD marker data; IMP_0.5ref: for half (randomly chosen) of the reference animals, the 54K marker data were imputed from LD marker data; LD_real: all animals had LD marker data without extension to the 54K marker data; bG(A): model with a G matrix built using autosomal markers only; G(A + X): model with a G matrix built using all markers and treating X-specific markers as autosomal markers; Gc(A + X): model with a G matrix built using all markers and specifying sex-linked inheritance of X-specific markers; G(A) + G(X): model with an autosome G matrix and an X chromosome G matrix; G(A) + Pol: model G(A) plus a residual polygenic effect; Gc(A + X) + Pol: model Gc(A + X) plus a residual polygenic effect.