Statistical and Computational Methods for the Study of Gene Families

印第安纳州大学获得一笔赠款，用于开发一个统计框架，该框架将允许推断物种之间的基因家族进化。为了充分利用各种基因组测序项目产生的数据，该项目旨在扩展生物研究人员研究基因家族所需的统计和计算工具。该提案有三个主要目标：1）开发更好的统计工具。这项工作将使物种之间的基因复制和缺失参数的更精确的估计，并将提供新的方法来研究基因家族内的单基因组。包括检测和整合全基因组重复的方法将大大扩展统计推断。2)创建易于使用的软件。一个免费的软件包将被实施，可用于研究整个基因组或单个基因家族的研究人员。在这个项目中创建的统计工具将通过这个软件包迅速传播到社区。3)提供果蝇的注释基因家族。12种果蝇的测序将是比较基因组学研究的布恩。通过与FlyBase合作，提供一组来自这些物种的注释良好的基因家族，我们将为生物学家提供新的方法，将这些信息与功能和比较基因组数据联系起来。这项研究的成果将为未来所有基因家族的研究提供一个广泛的统计和计算框架。该研究还将为分子进化、统计学和生物信息学领域的本科生、研究生和博士后研究人员提供多样化的培训环境。代表性不足的群体和妇女通过多个奖学金计划的参与将确保实现这一特定的研究优先事项。该研究还将用于开发课程和课程，以了解生物多样性和遗传变异之间的关系，并用于生物信息学学生的研究生教育。

Indiana University is awarded a grant to develop a statistical framework that would allow for inferences regarding gene family evolution among species. In order to take full advantage of the data being produced by various genome sequencing projects, this project aims to extend the statistical and computational tools necessary for biological researchers to study gene families. There are three main goals of this proposal: 1) Development of improved statistical tools. This work will enable more refined estimates of gene duplication and deletion parameters between species, and will provide new ways in which to study gene families within single genomes. The inclusion of methods for detecting and incorporating whole genome duplications will greatly extend statistical inferences. 2) Creation of easy-to-use software. A free software package will be implemented that can be used by researchers studying whole genomes or individual gene families. Statistical tools created in this project will be quickly disseminated to the community via this package. 3) Providing annotated gene families for Drosophila. The sequencing of 12 Drosophila species will be a boon to comparative genomics studies. By working with FlyBase to provide a well-annotated set of gene families from across these species, we will present new ways for biologists to connect this information with functional and comparative genomic data. The products of this research will provide a broad statistical and computational framework for all future studies of gene families. The research will also provide a diverse training environment for undergraduates, graduate students, and postdoctoral researchers in molecular evolution, statistics, and bioinformatics. The participation of under-represented groups and women via multiple scholarship programs will ensure that this specific research priority is achieved. The research will also be used in the development of classes and programs for understanding the relationship between biodiversity and genetic variation, and in graduate education for bioinformatics students.