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Table 3 Simulation scenario 3.

From: Genetic mapping of complex traits by minimizing integrated square errors

  

H2 = 0.4

  

H2 = 0.2

  

H2 = 0.1

  

Parameter

True Value

L2E

ML

NP

L2E

ML

NP

L2E

ML

NP

g 2

35

35.3(0.0709)

35.9(0.0606)

-

35.7(0.1028)

35.9(0.0905)

-

36(0.1646)

36(0.1404)

-

g 1

30

30.1(0.0335)

31.4(0.0389)

-

30.7(0.074)

31.5(0.0573)

-

31(0.1108)

31.4(0.0916)

-

g 0

25

25(0.0696)

26.7(0.0774)

-

25.4(0.0911)

26.8(0.0881)

-

25.8(0.1628)

26.6(0.1244)

-

sigma

4.3

4.7(0.0238)

6.2(0.022)

-

     

-

sigma

7.1

   

7.6(0.0386)

8.3(0.0312)

    

sigma

10.6

      

11.1(0.0567)

11.5(0.0376)

 

Position

86

85.5(0.1466)

85.2(0.1712)

86.7(0.1387)

86(0.2272)

85.1(0.2528)

85.9(0.2562)

85.7(0.4935)

86.6(0.362)

85.4(0.3452)

  1. The L2 and ML estimates of QTL parameters from an F2 population of 400 individuals for the phenotypic data simulated from normal distributions containing 10% noise points with mean g = 45. Numbers in the parentheses are the mean square errors (MSE) of the estimates