Univariate | Bivariate Filter | Bivariate Filter + GSS |
---|
Dataset | log10 | |
| | DSS | GBOOST | |
| DSS | GBOOST |
---|
HT | -9.8 | | 128 | | 429 | 51 | | 41 | 107 | 24 |
BD | -10.9 | | 2445 | | 556 | 34 | | 44 | 179 | 27 |
CAD | -13.1 | | 210147 | | 7807 | 43 | | 42 | 116 | 39 |
T2D | -13.3 | | 56592 | | 3105 | 52 | | 79 | 134 | 41 |
CD | -34.3 | | > 500000∗ | | 5591 | 25 | | 29 | 57 | 22 |
RA | -37.7 | | > 500000∗ | | 823 | 99 | | 59 | 312 | 95 |
T1D | -133.6 | | > 500000∗ | | 4993 | 37 | | 2 | 107 | 33 |
- Summary of the number of SNP pairs detected by , GBOOST and our introduced DSS heuristic over all WTCCC datasets before and after filtering with GSS. The rows of the table are sorted in descending order of p-values for univariate test (Column 2). Columns 3-5 show results for the bivariate filters, and columns 6-8 show the number of epistatic interactions discovered after further filtering with GSS. In some diseases, strong univariate SNPs likely cause proliferation of non-epistatic but significant pairs according to . These pairs are largely removed by the proposed GSS filter. A '*' indicates that an upper bound on the number of recorded pairs was reached. The number of significant pairs may be much higher.