This article aims to evaluate the performance of a recent method to estimate heritability of continuous and binary traits, specifically in the context of pharmacogenetic studies.Materials & methods:
The approach to be evaluated was designed to estimate heritability in large-scale disease studies. Extensive simulation studies designed to emulate common scenarios seen in pharmacogenetic studies were performed to elucidate the potential utility of this approach outside of disease genetics. The simulations cover continuous and binary traits with small-to-moderate heritability values across a variety of samples sizes in genome-wide, as well as candidate gene, settings.Results:
On a genome-wide scale, a combination of relatively large sample sizes (i.e., n ≥ 1000) and at least moderate underlying heritability (i.e., ≥0.25) are needed in order to attain reasonable statistical power. However, in candidate gene studies, reasonable power can be attained across a more broad range of scenarios.Conclusion:
Our simulation studies show that the proposed approach has clear utility in the context of pharmacogenetic studies, especially in candidate gene settings, and provides novel supplementary information that can be used to inform decision-making in the pharmaceutical industry.