RAPID: Accelerating Phylodynamic Analyses of SARS-CoV-2

使用基因组数据的进化分析是科学应对COVID-19大流行的重要组成部分，COVID-19大流行由严重急性呼吸系统综合征冠状病毒2（SARS-CoV-2）引起。通过采样时间和地点信息推断病毒样本的进化历史或进化史，使科学家能够估计病毒谱系在时间和地点上的分歧。这些分析提供了早于采样事件的时间估计。关于突变和突变率的信息是这些系统发育分析所固有的，使得可以鉴定具有加速突变率的特定病毒谱系（如果存在的话）。此外，分子生物学动力学不仅包括进化历史，还包括病毒遗传变异和病毒种群动力学的信息，同样都是在地理和时间的背景下。该项目的软件将用于SARS-CoV-2研究：移动和迁移模式;爆发起源时间;突变率和对潜在健康影响的重大突变的检测;不同地理范围内的人群流行率;生殖数量和对政策的影响;以及感染到病例报告率。也许最直接的影响是，该项目的软件将加速追踪和确定接触者追踪无效的特定地理区域爆发的起源。接触者追踪和系统发育分析在不同的尺度上起作用，因此是互补的。它们共同提供了对当前大流行的传播模式的更全面的看法。系统动力学分析在推论方面特别丰富，尽管计算成本相当高。该项目将大大加快SARS-CoV-2数据集的系统发育和系统动力学分析，并促进其在国家科学基金会支持的计算资源，学术计算中心以及云计算环境中的计算。具体活动包括设计新的战略，用于有效并行计算来自病毒爆发的大型数据集，重点是SARS-CoV-2，制定战略，消除易于使用高性能并行系统发育和系统动力学分析的障碍，开发在图形处理单元（GPU）上实施这些新战略的算法，并与其他人合作，缩短SARS-CoV-2数据集分析结果的时间。该奖项由生物基础设施部使用冠状病毒援助，救济和经济安全（CARES）法案的资金颁发。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Evolutionary analyses using genomic data are an essential component of the scientific response to the COVID-19 pandemic, which is caused by Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2). Inferring the evolutionary history, or phylogeny, of virus samples with sampling time and location information allows scientists to estimate the divergence of viral lineages in time and place. These analyses provide time estimates that predate sampling events. Information about mutations, and the rate of mutation, is inherent to these phylogenetic analyses such that specific viral linages with accelerated mutation rates, if they exist, can be identified. Furthermore, molecular phylodynamics includes not only evolutionary history but also information on viral genetic variation and viral population dynamics, again all in the context of geography and time. The software from this project will be used in SARS-CoV-2 research on: patterns of movement and migration; time of outbreak origin; rate of mutation and detection of significant mutations with potential health impact; prevalence in populations at different geographical scales; reproductive number and impact on policy; and infection-to-case reporting rates. Perhaps of most immediate impact is that software from this project will accelerate tracing and dating the origins of outbreaks in specific geographic regions where contact tracing is not effective. Contact tracing and phylogenetic analyses work on different scales, and thus are complementary. Together they provide a more comprehensive view of the transmission patterns for the current pandemic.Phylodynamic analyses are particularly rich in terms of inferences, albeit at a considerable computational cost. This project will greatly accelerate phylogenetic and phylodynamic analysis of SARS-CoV-2 data sets, and facilitate their computation on National Science Foundation supported computing resources, academic computing centers, as well as cloud computing environments. Specific activities include designing new strategies for efficient parallel computation of large data sets from viral outbreaks focusing on SARS-CoV-2, developing strategies for removing the barriers to easy use of highly performant parallel phylogenetic and phylodynamic analyses, developing algorithms for implementing these new strategies on graphical processing units (GPUs), and working with others to improve the time to results for analyses of SARS-CoV-2 data sets. This RAPID award is made by the Division of Biological Infrastructure using funds from the Coronavirus Aid, Relief, and Economic Security (CARES) Act.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.