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Table 4 The mean of true breeding value of the top 1% of animals with the highest total estimated breeding value

From: The impact of genotyping strategies and statistical models on accuracy of genomic prediction for survival in pigs

Trait1

Genotyping scenario2

a4

m4

a + m

LM3

LG

PM

LM

LG

PM

LM

LG

PM

T4/4

G_all

2.355

2.297

2.263

2.143

2.255

2.290

4.498

4.553

4.553

G80_ran

2.236

2.174

2.165

2.061

2.153

2.181

4.297

4.327

4.346

G_alive

2.040

2.038

2.030

2.181

2.270

2.270

4.221

4.308

4.300

G_none

1.299

1.304

1.319

1.284

1.339

1.393

2.583

2.643

2.712

T2/4

G_all

1.138

1.076

1.068

1.982

1.988

1.989

3.121

3.064

3.057

G80_ran

1.094

1.040

1.024

1.892

1.905

1.922

2.985

2.945

2.945

G_alive

1.047

1.013

0.996

1.914

1.883

1.887

2.961

2.896

2.883

G_none

0.743

0.745

0.770

1.169

1.225

1.239

1.912

1.970

2.010

T2/2

G_all

1.263

1.238

1.237

1.184

1.202

1.206

2.447

2.439

2.443

G80_ran

1.181

1.149

1.160

1.134

1.129

1.137

2.315

2.278

2.297

G_alive

1.145

1.139

1.145

1.220

1.208

1.225

2.364

2.346

2.370

G_none

0.864

0.870

0.900

0.700

0.702

0.686

1.564

1.572

1.586

  1. 1T4/4: trait with ha2 = 0.04, hm2 = 0.04 and lit2 = 0.04, T2/4: ha2 = 0.02, hm2 = 0.04 and lit2 = 0.04; T2/2: ha2 = 0.02, hm2 = 0.02 and lit2 = 0.02, in liability scale
  2. 2G_all: all pigs were genotyped; G80_ran: 80% of pigs randomly selected from the whole population were genotyped; G_alive: only alive pigs (80%) were genotyped; G_none: no pig was genotyped
  3. 3LM linear model, LG logit model, PM probit model
  4. 4a: direct additive genetic effect; m: maternal additive genetic effect