@article {Uricchio015917, author = {Lawrence H. Uricchio and John S. Witte and Ryan D. Hernandez}, title = {Selection and explosive growth may hamper the performance of rare variant association tests}, elocation-id = {015917}, year = {2015}, doi = {10.1101/015917}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Much recent debate has focused on the role of rare variants in complex phenotypes. However, it is well known that rare alleles can only contribute a substantial proportion of the phenotypic variance when they have much larger effect sizes than common variants, which is most easily explained by natural selection constraining trait-altering alleles to low frequency. It is also plausible that demographic events will influence the genetic architecture of complex traits. Unfortunately, most rare variant association tests do not explicitly model natural selection or non-equilibrium demography. Here, we develop a novel evolutionary model of complex traits. We perform numerical calculations and simulate phenotypes under this model using inferred human demographic and selection parameters. We show that rare variants only contribute substantially to complex traits under very strong assumptions about the relationship between effect size and selection strength. We then assess the performance of state-of-the-art rare variant tests using our simulations across a broad range of model parameters. Counterintuitively, we find that statistical power is lowest when rare variants make the greatest contribution to the additive variance, and that power is substantially lower under our model than previously studied models. While many empirical studies have attempted to identify causal loci using rare variant association methods, few have reported novel associations. Some authors have interpreted this to mean that rare variants contribute little to heritability, but our results show that an alternative explanation is that rare variant tests have less power than previously estimated.}, URL = {https://www.biorxiv.org/content/early/2015/03/01/015917}, eprint = {https://www.biorxiv.org/content/early/2015/03/01/015917.full.pdf}, journal = {bioRxiv} }