QEIB: Statistical Issues in Combining Data for Phylogenetic Analysis

这项研究涉及的方法的发展，以获得系统发育关系的可靠估计为目标，从不同的来源结合数据集。作为一个例子，考虑这样一种情况，在这种情况下，以DNA序列数据形式的进化信息可以从整个基因组中采样的几个不同的基因中获得。从这些基因中单独估计的系统发育树将产生估计的基因树，这些树说明了特定基因的进化史。通常最令人感兴趣的是对物种历史的估计，这可能与基因历史不同。因此，必须将遗传信息适当地结合起来，以便估计物种之间的关系。本研究将解决与此问题相关的三个主要问题。首先是研究目前可用的用于评估单个数据集的可组合性的测试，并改进这些现有测试。本研究的第二个组成部分涉及开发新的程序，用于测试数据集中潜在进化史的相似性，以及开发用于测试哪种进化机制（即杂交，水平基因转移等）可能导致不同潜在历史的方法。这些新开发的测试基于似然比统计，将在特定进化力的假设下估计的树状结构的可能性与不受限制的可能性进行比较。本研究的最后一个组成部分是开发适当的方法来结合来自不同来源的数据，以估计物种树。这是通过对一组观察到的基因树从给定的物种树中产生的概率进行建模来实现的。估计的物种树就是使这个概率最大化的树。基于包含在生物体DNA序列中的信息来推断生物体的进化史是进化生物学中一个非常重要的问题。基因组测序项目产生的大量DNA序列数据导致了这些系统发育关系推断的重大挑战。这些挑战之一是基于来自基因组中几个不同基因的DNA序列信息来推断物种集合的进化史。这项研究将解决这个问题的许多方面，包括：(1)评估现有的结合不同基因数据的程序，以及对这些程序的改进；（二）研究不同基因进化史差异原因的检验方法；(3)结合不同基因的DNA信息以推断物种关系的新程序的发展。这项工作可以应用于理解备受争议的物种关系，例如胎盘哺乳动物、有袋动物和单孔目动物之间的进化关系。

This research involves the development of methods for combining data sets from different sources with the goal of obtaining robust estimates of phylogenetic relationships. As an example, consider the case in which evolutionary information in the form of DNA sequence data is available from several distinct genes sampled throughout the genome. Phylogenetic trees estimated individually from each of these genes will yield estimated gene trees, trees which illustrate the evolutionary history of that particular gene. What is often of most interest is the estimation of the species history, which may be different from the gene history. Thus, the genetic information must be combined appropriately so that species relationships can be estimated. This research will address three main issues associated with this problem. The first is the study of currently available tests for assessing combinability of the individual data sets, and the improvement of these existing tests. The second component of this research involves the development of new procedures for testing for similarity in underlying evolutionary history in the datasets, and for development of methods for testing which evolutionary mechanisms (i.e., hybridization, horizontal gene transfer, etc.) might be responsible for differing underlying histories. These newly developed tests are based on likelihood ratio statistics which compare the likelihood of a tree-like structure estimated under the assumption of a particular evolutionary force to an unrestricted likelihood. The final component of this research is the development of appropriate methods for combining data from different sources in order to estimate the species tree. This is achieved by modeling the probability that a set of observed gene trees would have arisen from a given species trees. The estimated species tree is then that tree which maximizes this probability.The inference of the evolutionary history of a collection of organisms based on the information contained in their DNA sequences is a problem of fundamental importance in evolutionary biology. The abundance of DNA sequence data arising from genome sequencing projects has led to significant challenges in the inference of these phylogenetic relationships. Among these challenges is the inference of the evolutionary history of a collection of species based on DNA sequence information from several distinct genes sampled throughout the genome. This research will address numerous aspects of this problem, including (1) the assessment of existing procedures for combining data from different genes, and the improvement of such procedures; (2) the development of methods for testing for the cause of differences in the evolutionary histories of distinct genes; and (3) the development of new procedures for combining DNA information from distinct genes with the goal of inferring species relationships. This work has applications in the understanding of much-debated species relationships, such as the evolutionary relationships between placental mammals, marsupials, and monotremes.