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Table 4 Accuracy and bias of predicted GBVs evaluated with cross-validation in Data I

From: A Bayesian method and its variational approximation for prediction of genomic breeding values in multiple traits

Method

  

Trait A

Trait B

Trait C

MCBayes

π = 0

r TBV,pGBV

0.832 ± 0.039

0.611 ± 0.095

0.501 ± 0.083

  

b TBV,pGBV

1.016 ± 0.022

1.072 ± 0.231

1.052 ± 0.341

  

r y,pGBV

0.741 ± 0.037

0.191 ± 0.045

0.160 ± 0.050

  

b y,pGBV

1.013 ± 0.015

1.062 ± 0.125

1.039 ± 0.130

 

0 < π <1

r TBV,pGBV

0.791 ± 0.048

0.603 ± 0.112

0.390 ± 0.127

  

b TBV,pGBV

1.132 ± 0.064

1.210 ± 0.303

1.180 ± 0.379

  

r y,pGBV

0.705 ± 0.045

0.191 ± 0.046

0.121 ± 0.060

  

b y,pGBV

1.131 ± 0.065

1.210 ± 0.170

1.119 ± 0.373

varBayes

π = 0

r TBV,pGBV

0.813 ± 0.049

0.620 ± 0.108

0.470 ± 0.118

  

b TBV,pGBV

1.080 ± 0.048

0.994 ± 0.157

0.963 ± 0.201

  

r y,pGBV

0.722 ± 0.047

0.187 ± 0.056

0.143 ± 0.058

  

b y,pGBV

1.072 ± 0.049

0.945 ± 0.195

0.931 ± 0.289

 

0 < π <1

r TBV,pGBV

0.779 ± 0.059

0.593 ± 0.111

0.423 ± 0.123

  

b TBV,pGBV

0.944 ± 0.040

0.816 ± 0.139

0.662 ± 0.153

  

r y,pGBV

0.690 ± 0.056

0.180 ± 0.055

0.125 ± 0.062

  

b y,pGBV

0.935 ± 0.039

0.787 ± 0.166

0.626 ± 0.255

single-trait

π = 0

r TBV,pGBV

0.826 ± 0.040

0.515 ± 0.073

0.505 ± 0.074

(MCBayes)

 

b TBV,pGBV

0.997 ± 0.023

1.073 ± 0.270

1.030 ± 0.303

  

r y,pGBV

0.735 ± 0.039

0.159 ± 0.045

0.162 ± 0.044

  

b y,pGBV

0.993 ± 0.012

1.071 ± 0.162

1.055 ± 0.222

 

0 < π <1

r TBV,pGBV

0.821 ± 0.039

0.531 ± 0.099

0.522 ± 0.094

  

b TBV,pGBV

1.131 ± 0.046

1.265 ± 0.555

1.192 ± 0.405

  

r y,pGBV

0.731 ± 0.037

0.164 ± 0.051

0.164 ± 0.048

  

b y,pGBV

1.127 ± 0.043

1.249 ± 0.482

1.205 ± 0.457

  1. Averages and standard errors evaluated with 10- fold cross-validation are listed based on 100 replicates of simulated data in Data I are listed for prediction accuracy, rpGBV,TBV, and bias, bpGBV,TBV, as well as correlation between phenotypic value and predicted GBV, ry,pGBV, and regression of phenotypic value on predicted GBV, by,pGBV , of each trait. For the settings of prior probability that a SNP has zero effect, π, see Table1.