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Table 3 Correlations between genomic breeding values and breeding values from different low SNP-density approaches (and change in correlation compared to original full marker model), where all SNP effects are estimated in the same high SNP-density training set, for t530 and t600.

From: Genomic breeding value prediction using three Bayesian methods and application to reduced density marker panels

  

t530

  

t600

 

Scenario

Bayes-A

Student-t

Lasso

Bayes-A

Student-t

Lasso

EVEN_19

0.255

0.142

0.195

-0.128

0.098

0.173

 

(-0.418)

(-0.846)

(-0.594)

(-0.532)

(-0.622)

(-0.564)

EVEN_38

0.481

0.494

0.528

0.469

0.485

0.522

 

(-0.192)

(-0.249)

(-0.242)

(-0.180)

(-0.235)

(-0.215)

EVEN_76

0.490

0.544

0.586

0.472

0.532

0.584

 

(-0.183)

(-0.246)

(-0.192)

(-0.130)

(-0.188)

(-0.153)

SIG_19

0.663

0.699

0.709

0.669

0.692

0.709

 

(-0.010)

(-0.049)

(-0.037)

(0.025)

(-0.028)

(-0.028)

SIG_38

0.664

0.703

0.713

0.669

0.707

0.721

 

(-0.009)

(-0.049)

(-0.033)

(0.029)

(-0.013)

(-0.016)

SIG_76

0.667

0.709

0.711

0.672

0.712

0.729

 

(-0.006)

(-0.046)

(-0.027)

(0.035)

(-0.008)

(-0.008)

EVEN_GP_19

0.937

0.967

0.980

0.928

0.967

0.978

 

(0.264)

(0.210)

(0.231)

(0.293)

(0.247)

(0.241)

EVEN_GP_38

0.733

0.785

0.861

0.736

0.789

0.862

 

(0.060)

(0.018)

(-0.049)

(0.111)

(0.069)

(0.125)

EVEN_GP_76

0.733

0.786

0.854

0.736

0.789

0.856

 

(0.060)

(0.018)

(-0.050)

(0.112)

(0.069)

(0.119)

SIG_GP_19

0.674

0.730

0.802

0.675

0.735

0.798

 

(0.001)

(0.043)

(-0.006)

(0.056)

(0.015)

(0.061)

SIG_GP_38

0.673

0.728

0.783

0.675

0.731

0.791

 

(0)

(-0.043)

(-0.008)

(0.054)

(0.011)

(0.054)

SIG_GP_76

0.673

0.724

0.767

0.674

0.729

0.769

 

(0)

(-0.044)

(-0.012)

(0.050)

(0.009)

(0.032)