RUI: Quartet-Based Approaches to Phylogenomics

为了跟上遗传数据迅速扩大的步伐，需要对用来揭示地球生命进化史的数学和统计工具进行现代化改造。此外，不同的遗传信息片段可以告诉生物体集合的相互矛盾的进化历史。 该项目开发了数学工具，用于重建大量生物体的进化历史，并构建一个单一的树，该树包含了基因组不同片段所讲述的相互冲突的故事。 10名本科生，其中许多人是从这个主要是本科生的机构中STEM领域代表性不足的群体中招募的，他们将接受算法开发所需的数学，统计学和生物学交叉技术的培训。大多数超树或物种树重建方法依赖于精确重建的基因树。 然而，在实践中，这些重建中使用的大多数推断基因树确实包含错误。通过识别和明确占基因树估计误差，这个项目将改进算法的超级树和物种树重建。也将开发其他方法，在不依赖于基因树的先验估计的情况下重建物种树。

A modernization of the mathematical and statistical tools used to uncover the evolutionary history of life on earth is required to keep pace with the rapid expansion in the availability of genetic data. Moreover, different segments of genetic information can tell conflicting evolutionary histories about a collection of organisms. This project develops mathematical tools for reconstructing the evolutionary history of large collections of organisms, and for constructing a single tree that encapsulates the conflicting stories told by different pieces of the genome. Ten undergraduate students, many recruited from groups underrepresented in STEM fields at this primarily undergraduate institution, will be trained in techniques at the intersection of mathematics, statistics, and biology that are required for the algorithmic developments. Most methods of super-tree or species tree reconstruction rely on accurately reconstructed gene trees. In practice, however, most inferred gene trees used in these reconstructions do contain errors. By identifying and explicitly accounting for gene tree estimation error, this project will improve algorithms for super-tree and species tree reconstruction. Alternative approaches for which species trees are reconstructed without dependence on the prior estimation of gene trees will also be developed.