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Table 3 Accuracy of predicting phenotype in each successive generation based on training on generation 1 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

Validation generation Method of training in generation 1
PBLUPa BayesBb BayesCb BayesC0 GBLUPc
G2 0.21 0.36 0.34 0.32 0.31
G3 0.02 0.22 0.22 0.17 0.17
G4 0.12 0.32 0.31 0.28 0.28
G5 0.01 0.27 0.25 0.20 0.20
G6 0.12 0.42 0.39 0.35 0.35
G7 −0.05 0.28 0.28 0.21 0.21
G8 0.10 0.35 0.33 0.19 0.20
Averaged 0.07 0.32 0.30 0.25 0.25
  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