Statistical Inference under Isolation-with-Migration Models

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Abstract for proposal 0949561:Statistical Inference under Isolation-with-Migration Models This research will develop new methods to understand how new species arise. As related populations diverge from each other, on the way to becoming separate species, evolutionary forces leave an imprint on the patterns of genetic variation within those populations. To reconstruct the history of the divergence process, genetic data are collected from natural population and then subject to statistical analyses that incorporate population genetic theory. The accuracy of these inferences depends critically on the computer programs that are used in the data analyses. The goal of this research is to improve existing analytical programs by developing methods to determine whether the best conclusions that these methods provide actually are a good fit to the data. Also existing methods will be extended to better address questions about natural selection, and to include genes that have experienced a history of recombination. This research will greatly improve scientists? ability to understand how separate species have come into being. The project will directly support a postdoctoral scientist and a graduate student. In addition several undergraduate students will be involved in the project each semester. The results of the research will include improved methods and tools (i.e. computer programs) and these programs will be freely available on the internet for other scientists to download and to use.