Statistical tools for seed bank detection

We derive statistical tools to analyze the patterns of genetic variability produced by models related to seed banks; in particular the Kingman coalescent, its time-changed counterpart describing so-called weak seed banks, the strong seed bank coalescent, and the two-island structured coalescent. As (strong) seed banks stratify a population, we expect them to produce a signal comparable to population structure. We present tractable formulas for Wright's F_ST and the expected site frequency spectrum for these models, and show that they can distinguish between some models for certain ranges of parameters. We then use pseudo-marginal MCMC to show that the full likelihood can reliably distinguish between all models in the presence of parameter uncertainty under moderate stratification, and point out statistical pitfalls arising from stratification that is either too strong or too weak. We further show that it is possible to infer parameters, and in particular determine whether mutation is taking place in the (strong) seed bank.