Collaborative Research: Aggregating and Repurposing Phylogeographic Data

合作研究：系统发育地理学数据的汇总和重新利用

• 批准号: 1911293
• 负责人: Tara Pelletier
• 金额: $ 12.88万
• 依托单位: Radford University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1911293&HistoricalAwards=false
• 关键词: Collaborative; Research; Aggregating; Repurposing; Phylogeographic

Patterns of genetic diversity within species contain information about the history of the species, including how it responded to historical climate change and the degree of isolation of its populations. For this reason, thousands of scientific projects have been funded by federal agencies with the goal of investigating the genetic diversity within a particular focal species. The data from these efforts, including the genetic data collected from a given specimen and the physical location from which that specimen was collected, are a valuable resource and typically are made available to other researchers upon publication of the study. However, since different types of data are stored in different databases, it can be difficult to access and assemble these data for reanalysis. This project will build a database that (i) aggregates data from different sources, (ii) connects these data at the specimen level, and (iii) includes customized web-based apps that will enable these data to be analyzed in a variety of ways. This project will benefit the public by increasing an understanding of conservation risks that may be faced by species in particular habitats and by facilitating comparisons across species. This project will facilitate two types of scientific research: large meta-analyses of thousands of species that can address classic questions in evolutionary biology, ecology, and conservation biology on a global scale, and student- or citizen- science based investigations that will introduce a broad range of people to the analysis of genetic data for species of interest.More than 40,000 phylogeographic investigations have been published to date, each collecting genetic data from hundreds of samples. Despite millions of data points, few meta-analyses have been conducted because the synthesis of results across hundreds of studies, each using different methods and forms of analysis, is a daunting and time-consuming task. It is more efficient to proceed by repurposing existing data and using automated data analysis. While the editorial policies of most journals now require data to be made available upon publication, the utility of these data are limited because genetic data and geographic sampling localities are typically published in separate databases that are not easily linked. This project will: (i) provide a series of web-based tools to connect accessions in genetic databases such as GenBank with geographic information on databases such as GBIF; (ii) expand data analysis pipelines that can be used to automate phylogeographic analyses from thousands of species on a global scale; (iii) promote these tools to the broader community of organismal biologists; and (iv) work with High School teachers and undergraduate students to develop educational modules that utilize this project's software. The primary deliverable will be Phylogatr, a database and web application built by professional software engineers via a partnership with the Ohio Supercomputer Center. The project will enhance the value of existing data via the creation of software and web-based tools that enable these data to be recycled and reanalyzed.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

物种内的遗传多样性模式包含有关该物种历史的信息，包括它如何应对历史气候变化以及其种群的孤立程度。因此，联邦机构资助了数千个科学项目，目的是调查特定焦点物种内的遗传多样性。这些工作的数据，包括从给定样本收集的遗传数据以及收集该样本的物理位置，是宝贵的资源，通常在研究发表后可供其他研究人员使用。然而，由于不同类型的数据存储在不同的数据库中，因此访问和组合这些数据以进行重新分析可能很困难。该项目将建立一个数据库，该数据库（i）聚合来自不同来源的数据，（ii）在样本级别连接这些数据，以及（iii）包括定制的基于网络的应用程序，使这些数据能够以多种方式进行分析。该项目将通过增加对特定栖息地的物种可能面临的保护风险的了解并促进物种之间的比较来使公众受益。该项目将促进两种类型的科学研究：对数千个物种进行大型荟萃分析，可以解决全球范围内进化生物学、生态学和保护生物学中的经典问题；以及基于学生或公民科学的调查，该调查将引入广泛的人们对感兴趣物种的遗传数据进行分析。迄今为止，已发表了 40,000 多项系统发育地理学调查，每个调查都从数百个样本中收集遗传数据。尽管有数百万个数据点，但很少进行荟萃分析，因为数百项研究的结果综合（每项研究都使用不同的方法和分析形式）是一项艰巨且耗时的任务。通过重新利用现有数据并使用自动数据分析来进行工作会更有效。虽然大多数期刊的编辑政策现在要求在出版时提供数据，但这些数据的效用受到限制，因为遗传数据和地理采样地点通常发布在不易链接的单独数据库中。该项目将： (i) 提供一系列基于网络的工具，将 GenBank 等遗传数据库中的种质与 GBIF 等数据库中的地理信息连接起来； (ii) 扩展可用于对全球范围内数千个物种进行系统发育地理学分析的自动化的数据分析管道； (iii) 向更广泛的有机生物学家群体推广这些工具； (iv) 与高中教师和本科生合作开发利用该项目软件的教育模块。主要交付成果是 Phylogatr，这是一个由专业软件工程师通过与俄亥俄州超级计算机中心合作构建的数据库和网络应用程序。该项目将通过创建软件和基于网络的工具来提高现有数据的价值，使这些数据能够被回收和重新分析。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准。