Table 5.
Alcohol Consumption GWAS
| SNP | Chr. | Gene | Distance from Gene (bp) | SMA | Lasso-PL | Lasso-AL | Lasso-Ayers |
|---|---|---|---|---|---|---|---|
| rs7574612 | 2 | LHCGR | -24421 | 9.4∗10−6 (S) | S | S | S |
| rs4836266 | 5 | GRAMD3 | -235 | 1.3∗10−5 (N) | S | N | N |
| rs211598 | 6 | EYA4 | -29329 | 9.3∗10−6 (S) | S | S | S |
| rs4385434 | 8 | hCG_1814486 | -129857 | 5.5∗10−6 (S) | S | S | S |
| rs7136989 | 12 | GOLGA3 | -244 | 1.7∗10−5 (N) | S | N | N |
| rs6072694 | 20 | PTPRT | -1180 | 2.1∗10−6 (S) | S | S | S |
| rs233278 | 21 | KRTAP10-4 | -1677 | 1.3∗10−6 (N) | S | N | N |
For Tables 5 and 6: “S” means ”significant” and “N” means “not significant” using significance level α=1.18∗10−5. Note that Lasso-PL, Lasso-AL, and Lasso-Ayers cannot provide exact p-values, but selects significant SNPs while attempting to control the type-1-error rate at level α. One could fit multiple penalized regression models and estimate λ that controls the type-1-error rate at various orders of magnitude (e.g. 10−5,10−6, etc) to get a better idea of the significance of each selected SNP (not done here)