Table 1.
Concordance between the LD clumped regions discovered by BayesW or fastGWA.
| BayesW: no | BayesW: no | BayesW: yes | BayesW: yes | Total BayesW | |
|---|---|---|---|---|---|
| Phenotype | fastGWA: no | fastGWA: yes | fastGWA: no | fastGWA: yes | |
| Time to Angina | 290,220 | 0 | 128 | 0 | 128 |
| Time to Heart attack | 289,787 | 0 | 128 | 0 | 128 |
| Time to HBP | 291,674 | 4 | 653 | 10 | 666 |
| Time to Menarche | 292,127 | 242 | 223 | 191 | 414 |
| Time to Menopause | 292,202 | 125 | 126 | 97 | 227 |
| Time to Diabetes | 290,599 | 40 | 174 | 8 | 183 |
We split the genome into LD clumped regions and we evaluated the significance of each of the regions using the results from the groups BayesW model and the fastGWA model. The fastGWA results for our CAD and T2D definition were missing so instead time-to-angina and time-to-heart attack are shown for CAD and time-to-diabetes is shown for T2D. Here, BayesW calls an LD clumped region significant if the PPWV of the region (explaining at least 0.001% of the genetic variance) is higher than 0.9; fastGWA calls an LD clumped region significant if there exists at least one marker with a p-value < 5 × 10−8. We find that although for age-at-menarche and age-at-menopause there exists an abundance of regions with concordant significance, for other traits most of the discovered regions differ between two methods. For creating the comparison only overlapping markers were used; in the column Total BayesW we show the total number of discovered LD clumped regions, including those that did not have a counterpart among fastGWA results.