Figure 2.

Power comparison for analyzing X‐chromosomal single nucleotide polymorphisms (SNPs). Black $\square$ curves for testing ${\beta }_A=0$ based on model $M_1$ as specified in Table 3, green $◇$ curves for testing ${\beta }_A={\beta }_D=0$ based on model $M_2$, blue $▿$ curves for testing ${\beta }_A={\beta }_{GS}=0$ based on model $M_3$, and red $\times$ curves for testing ${\beta }_A={\beta }_D={\beta }_{GS}=0$ based on the proposed model $M_4$. (a) f_female = f_male = 0.2 and (b) f_female = f_male = 0.5. Upper panels in (a) and (b) examine power as a function of the “dominance” effect. Lower panels in (a) and (b) examine power as a function of the gene–sex “interaction” effect. Note that biological dominance effect and skewed X‐chromosome inactivation (XCI), and gene–sex interaction effect and the XCI status are statistically confounded with each other; see Section 3.2. Results for other parameter values including differential $f$ between males and females are shown in Figures S5. The analyses related to $M_1$–$M_3$ assume that the true baseline allele is known and $f$ being the allele frequency of the non‐baseline allele, and the true XCI status is known at the population level. Unlike the other methods ($M_1$–$M_3$), the proposed method ($M_4$) is invariant to the assumptions of the baseline allele and the XCI status