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Table 5 Estimates of substitution effects and regression coefficients for predicting generation 8 phenotypes from training in ancestral generations (G1 to G7) for SNP rs14491030 using BayesB or a single SNP model in ASReml

From: Mixture models detect large effect QTL better than GBLUP and result in more accurate and persistent predictions

Training generation BayesBa Single SNP animal modelb
Effect Regressionc Effect Regressionc
G1-G7 2.55 1.55 3.05 1.53
G1 0.51 2.51 2.62 1.78
G2 1.13 4.05 2.64 1.77
G3 1.54 2.98 2.83 1.65
G4 2.64 1.77 2.96 1.58
G5 1.69 2.72 3.29 1.42
G6 1.51 2.33 4.05 1.15
G7 0.46 1.74 3.81 1.23
Averaged 1.50 2.46 3.16 1.51
  1. aThe effect of the most significant marker in the 1 Mb window with the largest variance
  2. bMost significant marker fitted as a fixed effect in an animal model using ASReml
  3. cRegression of hatch-adjusted phenotype on predicted merit using the estimate of the SNP effect
  4. dAverage of the 7 individual generation results