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Table 2 Summary of results for the simulated data with main and epistatic effects

From: Fast empirical Bayesian LASSO for multiple quantitative trait locus mapping

Algorithm

Parametersâ—‡

PE ± STE*

Number of effects†‡

CPU time (mins)

 

(0.001, 0.001)

16.49 ± 0.8908

25/0

13.5

3.4

 

(0.01, 0.01)

15.95 ± 0.7477

28/0

12.46

3.4

 

(0.05, 0.05)

15.89 ± 0.7498

30/0

11.72

3.4

 

(0.1, 0.1)

15.81 ± 0.8359

30/0

11.72

3.4

EBLASSO

(0.5, 0.5)

15.86 ± 0.7717

31/0

11.57

3.4

 

(1, 1)

16.07 ± 0.7203

29/0

12.31

3.4

 

(0.5, 0.1)

16.14 ± 0.8557

28/0

12.5

3.4

 

(-0.01, 0.1)

15.92 ± 1.0161

32/1

11.31

3.4

 

(-1, 0.0001)

-

14/1

21.22

2,760.0

EB

(-1, 0.0005)

-

13/1

12.15

4,140.0

 

(-1, 0.001)

-

22/1

0.25

14,940.0

 

(-1, 0.01)

-

8/0

0.01

2,760.0

  1. ◇ Parameters are (a, b) for the EBLASSO, and (τ, ω) for the EB.
  2. *The average PE and the standard error were obtained from ten-fold cross validation.
  3. †The number of effects and residual variance were obtained using all 1000 samples not from cross validation.
  4. ‡The first number is the number of true positive effects; the second number is number of false positive effects. All the effects counted have a p-value ≤ 0.05.