  X-chromosome is often excluded from the so called `whole-genome' association
studies due to its intrinsic difference between males and females. One
particular analytical challenge is the unknown status of X-inactivation, where
one of the two X-chromosome variants in females may be randomly selected to be
silenced. In the absence of biological evidence in favour of one specific
model, we consider a Bayesian model averaging framework that offers a
principled way to account for the inherent model uncertainty, providing model
averaging-based posterior density intervals and Bayes factors. We examine the
inferential properties of the proposed methods via extensive simulation
studies, and we apply the methods to a genetic association study of an
intestinal disease occurring in about twenty percent of Cystic Fibrosis
patients. Compared with the results previously reported assuming the presence
of inactivation, we show that the proposed Bayesian methods provide more
feature-rich quantities that are useful in practice.
