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Table 5 Power (%) of RAML and SKAT methods to detect association of rare variants under seven scenarios for underlying genetic architecture using data simulated for BRCA2 in 4000 cases and 4000 controls

From: The admixture maximum likelihood test to test for association between rare variants and disease phenotypes

  

Threshold for significance

  

P < 0.001

P < 0.01

P < 0.05

Scenario*

Proportion of variants associated

RAML

SKAT-O

RAML

SKAT-O

RAML

SKAT-O

1

0.05

78.5

14

87.5

22

96

42.5

2

0.05

69.5

8.5

84

18

93

36

3

0.05

67.5

9.5

76.5

21

85

38

4

0.05

61.5

6

72

18.5

83.5

32.5

5

0.05

68.5

8.5

78.5

16

87

35.5

6

0.05

61

12.5

75.5

17.5

82

30.5

7

0.05

65

9

79

21.5

86.5

37.5

1

0.10

75

14.5

86

23

90.5

40.5

2

0.10

61.5

13.5

81.5

22

92.5

39.5

3

0.10

59

9.5

76

20

89

34

4

0.10

58.5

7

72

20.5

84

41

5

0.10

65

9

82

18.5

89.5

39

6

0.10

61

9

79

15.5

86.5

31

7

0.10

66.5

5

83.5

17

91

36

1

0.20

83.5

19.5

95

41

99

63.5

2

0.20

63

9.5

77

22.5

93.5

41

3

0.20

66.5

7

85.5

22.5

94

43.5

4

0.20

53

8.5

72.5

21

87

38.5

5

0.20

70.5

10

86

25.5

93

44

6

0.20

59

11

79

20.5

92

41.5

7

0.20

61

5.5

79.5

18.5

89.5

43.5

  1. Method with greatest power emboldened.
  2. * See text for description of genetic architecture for each scenario.
  3. RAML Rare admixture maximum likelihood, SKAT-O sequence kernel association test, T1 fixed threshold test 1 per cent MAF, T5 fixed threshold test 5 per cent MAF, WST weighted sum test, VTT variable threshold test, EREC estimated regression coefficient test.