Rapid: Collaborative Research: Agile and effective responses to emerging pathogen threats through open data and open analytics

快速：协作研究：通过开放数据和开放分析，敏捷、有效地应对新兴病原体威胁

• 批准号: 2027194
• 负责人: Anton Nekrutenko
• 金额: $ 10万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-01 至 2022-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2027194&HistoricalAwards=false
• 关键词: Rapid; Collaborative; Research; Agile; effective

The same types of questions arise during every emergent viral outbreak regarding its origin, its evolution, the manner of spread, and how to detect and mitigate it. Many, if not all, of these questions depend on rapid and reliable genomic analysis of diverse viral sample sequences by multiple laboratories. Early viral investigation is often impaired lack of reproducibility, rigor, and data/analytic sharing; the current investigation of COVID-19 is no different. Essential questions such as the extent of intra-host genomic variability (indicative of adaptation or multiple infection), viral evolution (selection, recombination), transmission (phylogentic and phylogeographic) cannot be answered reliably if researchers cannot trust/replicate the source data and analytical approaches. The goal of this award is to develop, deploy, and continuously update viral genomic analysis workflows to enable the analysis and monitoring of viral evolution and dynamics for SARS-CoV-2, and to use the lessons learned to prepare capacity for future outbreaks. Bioinformatics workflows for critical tasks in investigating COVID-19 and future viral outbreaks will be developed and COVID-19 deep sequencing data will be analyzed and shared openly via Galaxy and Datamonkey to facilitate and accelerate evolutionary discovery and enable the study of and response to inevitable future infectious disease outbreaks. In an age of digital connectivity, open and accessible shared data and analysis platforms have the potential to transform the way biomedical research is done, opening the way to ‘global research markets’, where competition arises from deriving understanding rather than access to samples and data. By enabling any researcher with an Internet connection to perform the same analyses as are done by top-flight research groups in resource-rich countries, this award will deliver critical components to resource limited settings, which are often those that are first and disproportionately affected by viral outbreaks.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.

在每次新出现的病毒爆发期间，都会出现相同类型的问题，涉及其起源、进化、传播方式以及如何检测和减轻病毒，其中许多（如果不是全部）取决于对不同病毒的快速可靠的基因组分析。早期的病毒研究往往缺乏可重复性、严谨性和数据/分析共享；目前对 COVID-19 的研究也不例外，例如宿主内基因组变异的程度。适应或多重感染），如果研究人员不能信任/复制源数据和分析方法，则无法可靠地回答病毒进化（选择、重组）、传播（系统发育和系统地理学）。该奖项的目标是开发、部署和持续更新病毒基因组分析工作流程。能够分析和监测 SARS-CoV-2 的病毒进化和动态，并利用吸取的经验教训为未来的爆发做好准备，以完成调查 COVID-19 和未来病毒爆发的关键任务。将开发并通过 Galaxy 和 Datamonkey 公开分析和共享 COVID-19 深度测序数据，以促进和加速进化发现，并在数字连接、开放和可访问的时代研究和应对未来不可避免的传染病爆发。共享数据和分析平台有可能改变生物医学研究的方式，为“全球研究市场”开辟道路，其中竞争源于理解而不是获取样本和数据。执行与以下相同的分析该奖项由资源丰富国家的顶级研究小组提供，将为资源有限的环境提供关键组成部分，这些环境通常是最先受到病毒爆发影响的地区。该奖项是 NSF 的法定使命，并通过评估被认为值得支持利用基金会的智力优势和更广泛的影响审查标准。