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Table 3 Accuracy 1 of prediction of seven linear methods in seven training scenarios for line B2

From: Genomic prediction based on data from three layer lines: a comparison between linear methods

 

Training dataset

Model

B1

B2

W1

B1 + B2

B1 + W1

B2 + W1

B1 + B2 + W1

BLUP2

-

0.220

-

-

-

-

-

GBLUP_VR

0.123

0.301

0.123

0.303

0.173

0.332

0.343

GBLUP_%id

0.147

0.329

0.136

0.336

0.198

0.352

0.376

RRBLUP

0.129

0.359

0.142

0.373

0.176

0.369

0.390

RRPCA

0.143

0.448

0.109

0.476

0.185

0.463

0.494

BSSVS

0.118

0.316

0.112

0.327

0.150

0.346

0.356

BayesC

0.111

0.338

0.106

0.318

0.139

0.354

0.357

  1. BLUP: conventional BLUP using a pedigree based relationship matrix; G-BLUP: Genome-enabled Best Linear Unbiased Prediction (G-BLUP); RRBLUP: Ridge Regression BLUP; RRPCA: Ridge Regression with PCA reduction; BayesSSVS: Bayesian Stochastic Search Variable Selection; BayesC; 1approximated SE of the accuracies of the genomic prediction models ranged from 0.097-0.102; 2for BLUP, only the analysis including the line itself was performed, because there are no pedigree relations between lines.