Skip to main content

Advertisement

Table 7 Accuracy (acc) and regression (reg) in the prediction of phenotypes

From: Using the realized relationship matrix to disentangle confounding factors for the estimation of genetic variance components of complex traits

Trait Model 1 Model 2 Model 3 Model 4
  acc reg acc reg acc reg acc reg
  prediction within full-sib families  
FDC 0.21 1.03 0.26 0.94 0.28 0.87 0.35 0.87
  (0.04) (0.4) (0.04) (0.16) (0.05) (0.19) (0.03) (0.08)
REP 0.44 1.01 0.51 0.99 0.52 0.95 0.52 0.93
  (0.02) (0.10) (0.02) (0.07) (0.02) (0.06) (0.02) (0.07)
WT 0.54 1 0.57 0.97 0.57 0.95 0.56 0.93
  (0.03) (0.13) (0.03) (0.06) (0.03) (0.09) (0.04) (0.1)
CC 0.54 0.97 0.65 0.97 0.69 0.93 0.87 0.99
  (0.02) (0.06) (0.01) (0.05) (0.01) (0.05) (0.03) (0.02)
prediction across full-sib families
FDC -0.02 -0.53 0.16 0.89 0.19 0.84 0.29 0.85
  (0.04) (1.94) (0.04) (0.23) (0.07) (0.27) (0.05) (0.08)
REP 0.12 0.83 0.31 0.81 0.36 0.8 0.35 0.75
  (0.05) (0.4) (0.04) (0.15) (0.05) (0.14) (0.04) (0.13)
WT 0.18 0.97 0.3 0.97 0.3 0.87 0.28 0.76
  (0.04) (0.28) (0.03) (0.13) (0.04) (0.2) (0.06) (0.23)
CC 0.17 0.85 0.46 0.9 0.53 0.8 0.78 0.95
  (0.04) (0.2) (0.07) (0.17) (0.09) (0.17) (0.09) (0.13)
  1. The average of correlations of actual and predicted phenotypes (standard deviations), and regression of the true phenotypes on predicted phenotypes (standard deviations) over 10 replicates when using model 1, 2, 3 and 4 for the traits