Fig. 4: Power of tests for detecting sex heterogeneity through simulations.
From: Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability
The power of sex-combined, sex-dimorphic and female-specific analyses, as well as Cochran’s Q-test was evaluated under three scenarios of sex-effects: no sex heterogeneity at a CAF = 0.05 and b CAF = 0.1, effects on both sexes with the presence of heterogeneity between them at c CAF = 0.05 and d CAF = 0.1, an effect specific to one sex only, e.g., women at e CAF = 0.05 and f CAF = 0.1. The power at P < 5 × 10−8 is given for all three tests: sex-combined, sex-dimorphic and female-specific. The power for the heterogeneity test implemented in GWAMA (Cochran’s Q-test) is also given. Simulations are based on 70,000 men and 70,000 women. For each parameter setting, 10,000 replicates of data were generated. CAF is the causal variant allele frequency and beta is the effect size in SD units in women. Within each scenario, we considered two CAFs (0.05 and 0.1) and a range of betas (from 0 to 0.1) representing the effect size in SD units in women. For the no sex heterogeneity setting, the beta in men is the same as in women; for the sex-dimorphic setting, the beta in men is fixed at 0.05 SD units; for the female-specific setting, the beta in men is fixed at zero.
