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Table 1 True and estimated effects for the simulated data with main effects

From: Empirical Bayesian LASSO-logistic regression for multiple binary trait locus mapping

locus

True β

EBLASSO-NE β ^ s β ^ a

EBLASSO-NEG β ^ s β ^ a

LASSO β ^ s β ^ a

HyperLasso β ^ s β ^ a

BhGLM β ^ s β ^ a

RVM β ^ s β ^ a

Single QTL β ^ s β ^ a

11

1.99

0.76(0.22)

1.61(0.22)

0.51(0.73)

1.67(0.30)

1.50(0.27)

3.87(0.60)

0.67(0.13)

26

1.81

0.54(0.19)

1.23(0.21)

−

0.93(0.38)

1.07(0.28)

1.53(0.47)b

0.73(0.13)

42

−1.28

−0.34(0.17)

−0.72(0.21)b

−

−1.02(0.29)

−0.95(0.24)

−

−

48

−0.91

−0.40(0.19)

−0.82(0.21)

−

−1.12(0.28)b

−0.91(0.23)

−

−

72

1.28

−

−

−

−

−

−

0.77(0.14)

73

1.81

1.37(0.21)

1.91(0.24)

1.03(0.85)

2.37(0.32)

2.16(0.28)

4.73(0.59)

0.80(0.14)

123

0.63

−

−

−

−

−

−

−

127

−0.63

−

−

−

−

−

−

−

161

0.44

0.30(0.15)b

0.59(0.19)b

−

0.82(0.25)b

−

1.15(0.35)

0.57(0.13)

181

0.99

0.38(0.20)b

−

−

−

−

−

1.67(0.18)

182

2.19

1.60(0.29)

2.86(0.31)

1.26(0.86)

3.34(0.38)

−2.73(0.37)

5.01(0.72)

1.89(0.19)

185

1.29

0.36(0.17)b

0.56(0.19)b

0.27(0.43)b

1.00(0.27)b

0.73(0.32)

2.38(0.69)b

1.44(0.16)

221

−0.75

−

−0.36(0.16)b

−

−

−

−

−

243

−0.57

−0.34(0.15)

−0.41(0.16)

−0.26(0.33)

−0.75(0.24)

−0.69(0.20)

−1.74(0.45)

−

262

−1.28

−

−

−

−

−

−

−

268

0.91

−

−

−

−

−

2.90(0.62)

−

270

0.57

−

−

−

−

−

−

−

274

−0.99

−

−

−

−

−

−1.90(0.46)b

−

361

0.41

0.30(0.16)b

0.40(0.16)b

0.15(0.56)b

0.77(0.24)b

−0.72(0.21)b

1.80(0.40)b

−

461

0.51

−

−

−

−

−

−

−

Parameter(s)

λ=0.050

a = 0.01

λ=0.0257

a = 0.1

υ = 10 − 3 τ = 10 − 4

  

b = 6

α=0.05

CPU time(s)

25.56

1.31

1.67

1.90

20.64

54.70

8.84

true/false positive

11/2c

11/1c

6/4c

10/1c

9/0c

17/18c

8/25d

  1. aThe estimated marker effect is denoted by β ^ and the standard deviation is denoted by s β ^ .
  2. bThe estimated marker effect was obtained from a neighboring marker (≤ 20 cM) rather than from the marker with true effect.
  3. cNumber of effects with a p-value ≤ 0.05.
  4. dNumber of effects with a p-value ≤ 1.04×10-4 after Bonferroni correction was applied.