ABI Development: CAFE for very large comparative genomic datasets

ABI 开发：用于非常大的比较基因组数据集的 CAFE

• 批准号: 1564611
• 负责人: Matthew Hahn
• 金额: $ 79.43万
• 依托单位: Indiana University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-04-15 至 2020-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1564611&HistoricalAwards=false
• 关键词: ABI; Development; CAFE; very; large

Genome sequencing projects have revealed frequent gains and losses of genes between species. These changes have been shown to be responsible for morphological, physiological, and behavioral differences, and to contribute to the diversity observed in nature. Advances in sequencing technology are making new genome data available at faster rates than ever before. As the number of species with sequenced genomes grows, so will the number of researchers wanting to take advantage of these valuable resources. They will come from a wide range of biological fields, and have an equally wide range of experience with computational tools. CAFE (Computational Analysis of gene Family Evolution) is a software package that allows researchers to better understand rates of gene gain and loss. This project will result in a version of CAFE that adds to the national infrastructure by enabling new biological discoveries to the benefit of scientists working in many fields. CAFE will be a useful tool in science education, and will also improve and accelerate biological research that can be expected to have multiple societal benefits, including understanding the genetic basis for important biological phenotypes. A vigorous outreach and information dissemination plan will ensure that researchers and faculty engaged in research education are aware of CAFE and able to use it effectively, and will promote the development of a technology-savvy 21st century biology research community.Studies of gene families are essential to a number of research areas, including gene regulation, human disease, and evolutionary genomics. CAFE enables these and other studies into cutting-edge areas by providing a likelihood method for analyzing gene gain and loss over a phylogeny. This method has been shown to work well with the error-prone genome assemblies currently available for most organisms, as well as when analyzing dozens of genomes at a time. This project will extend these capabilities to hundreds or thousands of genomes. To accomplish this goal, several of the maximum likelihood methodologies implemented by CAFE will be re-designed. These changes will include allowing rate variation among gene families, optimizing likelihood calculations on trees, and improving specification of several probability distributions used by these calculations. The quality of the code will be enhanced through best practices in software engineering and the development of better, faster, and more scalable supercomputer versions of the software. All software will be available at www.indiana.edu/~hahnlab/.

基因组测序项目揭示了物种之间基因的频繁获得和丢失。这些变化已被证明是负责形态，生理和行为的差异，并有助于在自然界中观察到的多样性。测序技术的进步使新的基因组数据比以往任何时候都更快。随着拥有测序基因组的物种数量的增长，想要利用这些宝贵资源的研究人员也会越来越多。他们将来自广泛的生物学领域，并拥有同样广泛的计算工具经验。CAFE（基因家族进化的计算分析）是一个软件包，使研究人员能够更好地了解基因获得和丢失的速度。 该项目将产生一个CAFE版本，通过使新的生物发现有利于在许多领域工作的科学家，增加国家基础设施。CAFE将是科学教育的一个有用工具，也将改善和加速生物学研究，预计这些研究将产生多种社会效益，包括了解重要生物表型的遗传基础。一个强有力的推广和信息传播计划将确保从事研究教育的研究人员和教师了解CAFE并能够有效地使用它，并将促进技术娴熟的21世纪世纪生物学研究社区的发展。基因家族的研究对许多研究领域至关重要，包括基因调控，人类疾病和进化基因组学。CAFE通过提供一种可能性方法来分析遗传学中的基因获得和损失，使这些和其他研究能够进入前沿领域。这种方法已被证明与目前大多数生物体可用的易错基因组组装以及一次分析数十个基因组时工作良好。该项目将把这些能力扩展到数百或数千个基因组。为了实现这一目标，将重新设计CAFE实施的几种最大似然方法。这些变化将包括允许基因家族之间的速率变化，优化树上的似然计算，以及改进这些计算所使用的几种概率分布的规范。代码的质量将通过软件工程的最佳实践和开发更好、更快、更可扩展的超级计算机版本的软件来提高。所有软件均可在www.indiana.edu/~hahnlab/上获得。