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 FST 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.

中文翻译：

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用于种子库检测的统计工具。

我们衍生出统计工具来分析由与种子库相关的模型产生的遗传变异的模式；特别是金曼（Kingman）联盟，其时变伙伴描述了所谓的弱种子银行，强种子银行联盟和两岛结构联盟。随着（强大的）种子库对人口进行分层，我们希望它们产生与人口结构相当的信号。我们为这些模型提供了Wright的FST和预期站点频谱的易于处理的公式，并表明它们可以在某些参数范围内的某些模型之间进行区分。然后，我们使用伪边际MCMC来证明在中等分层情况下，在存在参数不确定性的情况下，完全似然可以可靠地区分所有模型，并指出由于太强或太弱而导致的分层带来的统计陷阱。我们进一步表明，可以推断参数，尤其是确定突变是否在（强）种子库中发生。