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Table 4 Accuracy of predicting phenotype in each successive generation when using only the marker effect estimates from the top genomic 1 Mb window based on training in generation 1 for 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
BayesBa BayesCa BayesC0 GBLUPb
G2 0.25 0.23 −0.06 −0.03
G3 0.23 0.19 0.08 0.08
G4 0.27 0.26 −0.03 −0.10
G5 0.29 0.28 −0.13 −0.15
G6 0.31 0.30 0.11 0.13
G7 0.30 0.29 −0.03 −0.02
G8 0.34 0.34 0.00 0.00
Average 0.28 0.27 −0.01 −0.01
  1. a Mixture models assumed the fraction of SNP with 0 effect (π) of 0.99
  2. b GBLUP was fitted as BayesC0 with genetic and residual scale factors having 100 df