Duke University, Durham, USA.
Interface Focus. 2011 Dec 6;1(6):909-21. doi: 10.1098/rsfs.2011.0054. Epub 2011 Oct 5.
Phylogeographic methods have attracted a lot of attention in recent years, stressing the need to provide a solid statistical framework for many existing methodologies so as to draw statistically reliable inferences. Here, we take a flexible fully Bayesian approach by reducing the problem to a clustering framework, whereby the population distribution can be explained by a set of migrations, forming geographically stable population clusters. These clusters are such that they are consistent with a fixed number of migrations on the corresponding (unknown) subdivided coalescent tree. Our methods rely upon a clustered population distribution, and allow for inclusion of various covariates (such as phenotype or climate information) at little additional computational cost. We illustrate our methods with an example from weevil mitochondrial DNA sequences from the Iberian peninsula.
近年来，系统地理学方法受到了广泛关注，强调需要为许多现有的方法提供一个坚实的统计框架，以便进行具有统计学意义的可靠推断。在这里，我们通过将问题简化为聚类框架，采用灵活的完全贝叶斯方法，从而可以通过一系列迁移来解释种群分布，形成地理上稳定的种群聚类。这些聚类与相应（未知）细分的合并树的固定迁移次数一致。我们的方法依赖于聚类的种群分布，并允许在不增加额外计算成本的情况下包含各种协变量（例如表型或气候信息）。我们使用来自伊比利亚半岛的象鼻虫线粒体 DNA 序列的示例来说明我们的方法。
