Fig. 7: Empirical powers of SPAGxEmixCCT, SPAGxEmixCCT-local (ance1), SPAGxEmixCCT-local (ance2), and SPAGxEmixCCT-local-global at a significance level of 5 × 10−8 for binary trait analysis under the scenario of G×E effect size heterogeneity, with the marginal G×E effect size of ancestry 1 fixed at 0.5. | Nature Communications

Fig. 7: Empirical powers of SPAGxEmixCCT, SPAGxEmixCCT-local (ance1), SPAGxEmixCCT-local (ance2), and SPAGxEmixCCT-local-global at a significance level of 5 × 10−8 for binary trait analysis under the scenario of G×E effect size heterogeneity, with the marginal G×E effect size of ancestry 1 fixed at 0.5.

From: Efficient and accurate framework for genome-wide gene-environment interaction analysis in large-scale biobanks

Fig. 7

SPAGxEmixCCT-local (ance1) tests for \({\beta }_{G\times E}^{\left(1\right)}=0\), and SPAGxEmixCCT-local (ance2) tests for \({\beta }_{G\times E}^{\left(2\right)}=0\). A two-way admixed population was simulated with a sample size n = 10,000. The disease prevalence of the simulated binary phenotypes was 0.2. Two minor allele frequencies (MAFs) in ancestry 1 (from top to bottom) and four MAFs in ancestry 2 (from left to right) were considered. The true G×E effect size of ancestry 1 was fixed at 0.5, and that of ancestry 2 was increased. In each case, 1000 tests were conducted. Tests conducted in the analysis were two-sided.

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