Collaborative Research: Aggregating and Repurposing Phylogeographic Data

物种内遗传多样性的模式包含有关物种历史的信息，包括它如何应对历史上的气候变化以及其种群的孤立程度。出于这个原因，数以千计的科学项目得到了联邦机构的资助，目的是调查特定重点物种的遗传多样性。来自这些努力的数据，包括从特定标本收集的遗传数据和该标本收集的物理位置，是一种宝贵的资源，通常在研究发表后可供其他研究人员使用。但是，由于不同类型的数据存储在不同的数据库中，因此很难访问和组合这些数据以进行重新分析。该项目将建立一个数据库，(I)从不同来源汇总数据，(Ii)在标本层面连接这些数据，(Iii)包括定制的基于网络的应用程序，使这些数据能够以各种方式进行分析。该项目将使公众更好地了解物种在特定生境中可能面临的保护风险，并促进不同物种之间的比较。该项目将促进两种类型的科学研究：对数千个物种的大型荟萃分析，可以在全球范围内解决进化生物学、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，将向广泛的人介绍感兴趣物种的遗传数据分析。迄今为止，已发表了40,000多项系统地理调查，每个调查从数百个样本中收集基因数据。尽管有数百万个数据点，但很少进行荟萃分析，因为综合数百项研究的结果是一项艰巨而耗时的任务，每项研究都使用不同的分析方法和形式。通过重新调整现有数据的用途并使用自动数据分析来继续进行会更有效率。虽然大多数期刊的编辑政策现在要求在出版时提供数据，但这些数据的用途有限，因为遗传数据和地理抽样地点通常是在不同的数据库中发表的，这些数据库不容易联系起来。该项目将：(I)提供一系列基于网络的工具，将遗传数据库(如GenBank)中的材料与GBIF等数据库的地理信息连接起来；(Ii)扩展数据分析管道，可用于在全球范围内自动对数千个物种进行系统地理分析；(Iii)向更广泛的生物生物学家社区推广这些工具；(Iv)与高中教师和本科生合作，开发利用该项目软件的教学模块。主要交付内容将是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开发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进行评估，被认为值得支持。

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.