Gene-Based Methods for Estimating the Degree of the Skewness of X Chromosome Inactivation

Skewed X chromosome inactivation (XCI-S) has been reported to be associated with some X-linked diseases, and currently several methods have been proposed to estimate the degree of the XCI-S (denoted as [Formula: see text]) for a single locus. However, no method has been available to estimate [Formula: see text] for genes. Therefore, in this paper, we first propose the point estimate and the penalized point estimate of [Formula: see text] for genes, and then derive its confidence intervals based on the Fieller’s and penalized Fieller’s methods, respectively. Further, we consider the constraint condition of [Formula: see text] and propose the Bayesian methods to obtain the point estimates and the credible intervals of [Formula: see text] , where a truncated normal prior and a uniform prior are respectively used (denoted as GBN and GBU). The simulation results show that the Bayesian methods can avoid the extreme point estimates (0 or 2), the empty sets, the noninformative intervals ([Formula: see text]) and the discontinuous intervals to occur. GBN performs best in both the point estimation and the interval estimation. Finally, we apply the proposed methods to the Minnesota Center for Twin and Family Research data for their practical use. In summary, in practical applications, we recommend using GBN to estimate [Formula: see text] of genes.