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.

在每次紧急病毒暴发期间，都会出现关于其起源、演变、传播方式以及如何检测和缓解它的相同类型的问题。这些问题中的许多(如果不是全部)依赖于多个实验室对不同病毒样本序列的快速和可靠的基因组分析。早期的病毒调查往往缺乏重复性、严谨性和数据/分析共享；目前对新冠肺炎的调查也是如此。如果研究人员不能信任/复制来源数据和分析方法，就不能可靠地回答诸如宿主内基因组变异的程度(指示适应或多重感染)、病毒进化(选择、重组)、传播(系统发生和系统地理)等基本问题。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，以实现对SARS-CoV-2病毒进化和动态的分析和监测，并利用所学到的经验教训为未来的爆发做好准备。将为调查新冠肺炎和未来病毒爆发的关键任务制定生物信息学工作流程，并将通过银河和Datamonkey分析和公开共享新冠肺炎深度测序数据，以促进和加速进化发现，并使研究和应对不可避免的未来传染病爆发成为可能。在一个数字连接的时代，开放和可访问的共享数据和分析平台有可能改变生物医学研究的完成方式，为进入“全球研究市场”开辟道路，在这个市场上，竞争来自于获得理解，而不是获得样本和数据。通过使任何有互联网连接的研究人员能够执行与资源丰富国家的顶级研究小组所做的相同分析，该奖项将为资源有限的环境提供关键组件，这些环境通常是那些首先受到病毒爆发影响且不成比例的环境。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。