From: Wavelet Screening: a novel approach to analyzing GWAS data
Size | Model | Method | Significance | 1 | 2 | 3 | 4 | 5 | 6–10 | 11–15 | 16–20 | > 20 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
1000 | MD | WS | \(1\times 10^{-5}\) | 0.9 | 1.1 | 0.7 | 0.9 | 0.6 | 0.8 | 0.6 | 0.9 | 0.9 |
1000 | RD | WS | \(1\times 10^{-5}\) | 1.2 | 0.9 | 0.2 | 0.7 | 0.8 | 0.5 | 0.6 | 0.4 | 0.8 |
1000 | NA | SKAT | \(1\times 10^{-5}\) | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1 | 1.4 | 4.6 | 19.8 |
1000 | NA | GWAS | \(5\times 10^{-8}\) | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
5000 | MD | WS | \(1\times 10^{-5}\) | 17.3 | 18.3 | 19.1 | 20.6 | 24.0 | 20.9 | 19.4 | 19.3 | 20.2 |
5000 | RD | WS | \(1\times 10^{-5}\) | 7.3 | 10.5 | 8.8 | 7.1 | 9.4 | 8.5 | 9.2 | 8.0 | 9.3 |
5000 | NA | SKAT | \(1\times 10^{-5}\) | 0.0 | 0.2 | 1.4 | 3.0 | 5.9 | 26.7 | 69.5 | 95.4 | 99.9 |
5000 | NA | GWAS | \(5\times 10^{-8}\) | 45.5 | 25.8 | 16 | 3.1 | 2.7 | 2.8 | 1.1 | 0.6 | 0.4 |
10,000 | MD | WS | \(1\times 10^{-5}\) | 54.8 | 70.9. | 86.8 | 90.1 | 92.2 | 95.4 | 93.6 | 94.1 | 96.5 |
10,000 | RD | WS | \(1\times 10^{-5}\) | 57.3 | 49.8 | 54.6 | 53.8 | 56.1 | 54.4 | 50.7 | 50.6 | 52.1 |
1000 | NA | SKAT | \(1\times 10^{-5}\) | 0.0 | 1.1 | 6.5 | 15.6 | 24.9 | 64.5 | 96.5 | 100.0 | 100.00 |
10,000 | NA | GWAS | \(5\times 10^{-8}\) | 100 | 81.8 | 75.0 | 68.8 | 30.6 | 28.1 | 15.5 | 9.6 | 3.2 |