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Table 2 Accuracy of prediction of phenotypes in generation 8 based on training in all seven previous generations (G1-G7) or any one of the previous 7 generations for pedigree BLUP (PBLUP) and four genomic methods (BayesB, BayesC, BayesC0 and GBLUP)

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

  N Method of training with validation in generation 8
Training   PBLUPa BayesBb BayesCb BayesC0 GBLUPc
G1-G7 1,814 0.27 0.60 0.57 0.50 0.50
G1 295 0.10 0.35 0.33 0.19 0.20
G2 323 0.00 0.36 0.36 0.24 0.24
G3 294 0.02 0.49 0.45 0.28 0.28
G4 360 −0.07 0.40 0.30 0.12 0.12
G5 290 −0.01 0.47 0.38 0.32 0.32
G6 252 0.19 0.49 0.44 0.33 0.34
G7 295 0.22 0.48 0.45 0.37 0.37
Averaged   0.06 0.43 0.39 0.26 0.27
  1. aPedigree-based BLUP
  2. bMixture models assumed the fraction of SNPs with 0 effect (π) of 0.99
  3. cGBLUP was fitted as BayesC0 with genetic and residual scale factors having 100° of freedom
  4. dAverage of the 7 individual generation results