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
| |
|
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 |
Method with greatest power emboldened.
* See text for description of genetic architecture for each scenario.
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.