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Table 2 Simulation results on the basis of model (1).

From: Variable selection for large p small n regression models with incomplete data: Mapping QTL with epistases

Model

Marker(s)

Mean

SE

BF ≥ 1

BF ≥ 3.2

BF ≥ 10

BF ≥ 100

Without Epistases

2–47.8

0.7453

0.1340

94 (5)

93 (5)

92 (5)

90 (3)

 

3–141.5

1.1222

0.231

100 (0)

100 (0)

100 (0)

100 (0)

 

FDR (additive)

--

--

0.0067

0

0

0

With Epistases

2–47.8

0.7610

0.1439

94 (6)

93 (6)

93 (6)

93 (6)

 

3–141.5

1.1316

0.1402

100 (0)

100 (0)

100 (0)

100 (0)

 

(1–24.7, 2–47.8)

1.5607

0.3921

92 (6)

91 (7)

91 (7)

90 (7)

 

(2–47.8, 3–141.5)

1.5558

0.3054

97 (3)

96 (4)

96 (4)

96 (4)

 

(2–133.8, 3–56.7)

-1.6204

0.3875

92 (8)

92 (8)

92 (8)

90 (10)

 

FDR (additive)

--

--

0.0408

0.0333

0.0133

0.0067

 

FDR (epistatic)

--

--

0.4872

0.3251

0.2283

0.1122

  1. Out of 100 simulated data sets, the total numbers of data sets that correctly identify the true additive and interaction effects (in the brackets, their neighboring ones when the true ones are missed) are counted respectively when thresholding the Bayes factor (BF) at different levels. Also listed are the mean and standard error (SE) of the estimated effect sizes.