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Table 2 Summary of MBV prediction in the training data for five methods obtained by cross-validation

From: A comparison of five methods to predict genomic breeding values of dairy bulls from genome-wide SNP markers

Trait Method MSEP rEBV,MBV bEBV,MBV
ASI FR-LS 1,090 (124.4) 0.53 (0.036) 0.71 (0.048)
  RR-BLUP 712 (93.5) 0.71 (0.017) 1.07 (0.076)
  Bayes-R 714 (95.3) 0.71 (0.016) 1.09 (0.071)
  SVR 700 (92.2) 0.72 (0.017) 1.06 (0.079)
  PLSR 735 (95.4) 0.70 (0.022) 0.93 (0.069)
PPT FR-LS 0.0135 (0.0023) 0.43 (0.089) 0.62 (0.155)
  RR-BLUP 0.0104 (0.0018) 0.56 (0.067) 1.01 (0.104)
  Bayes-R 0.0104 (0.0010) 0.56 (0.067) 1.06 (0.117)
  SVR 0.0100 (0.0010) 0.58 (0.064) 1.01 (0.100)
  PLSR 0.0109 (0.0012) 0.55 (0.061) 0.81 (0.078)
  1. Mean square error (MSEP), correlation (rEBV,MBV) between EBV and MBV, and regression coefficient (bEBV,MBV) of EBV on MBV derived by 5-fold cross-validation of the training data set, standard errors in parentheses; ASI: Australian Selection Index; PPT: protein percentage; FR-LS: fixed regression-least squares; RR-BLUP: random regression-BLUP; Bayes-R: Bayesian regression; SVR: support vector regression; PLSR: partial least squares regression.