Integrative and interactive analyses of host transcriptional response to COVID-19 and other respiratory viral infections

项目总结 目前由严重急性呼吸综合征冠状病毒2(SARS-CoV-2)引起的大流行已导致 以应对全球公共卫生问题。这种新型冠状病毒病(新冠肺炎)具有相似的临床症状 由冠状病毒家族中的其他病毒和其他常见呼吸道病毒引起的疾病。什么时候 感染剂在宿主体内复制，宿主与病毒相互作用，并通过 各种机制。鉴于不同患者的严重程度不同，以及新的SARS-CoV-2变种的出现， 现在迫切需要了解主持人是如何回应新冠肺炎及其变体的。RNA测序 (RNA-seq)数据描述了对SARS-CoV-2和其他呼吸道病毒感染的转录反应 可从公共数据库中获得。比较不同呼吸道病毒的基因特征将确定 宿主如何应对这些感染的相似和不同之处。特别是，《简编》中的分析 这些多个数据集的集成为产生新的生物假说带来了巨大的机会。 然而，对不同实验室产生的rna-seq数据进行概要分析是一项繁重的任务。 考虑到分析时使用的不同协议、参数、软件和软件版本。 这项提议的重点是开发软件工具，以促进对现有主机响应的重新分析 使用相同的分析工具和输入创建基因签名简编的RNA-SEQ数据 参数。我们的交付成果将包括带有已保存的输入文件和参数的工作流程、修复的软件 促进可重复性和协作的版本和依赖项。我们将提供一个无障碍的 图形用户界面，允许用户通过查询数据创建自定义特征码集，如果需要， 使用我们提供的工作流程之一或他们自己选择的工作流程重新分析数据。用户将成为 能够过滤生物变量，执行跨物种分析，将基因签名与其他基因组进行比较 储存库。此外，我们还将创建一个可访问的仪表板，以支持查询、下载 SARS-CoV-2和其他常见病毒基因表达数据的可视化和可重复性分析 呼吸道病毒。将提供工具，使用户能够以交互方式可视化数据并通知 选择合适的基因签名。我们的软件工具和控制面板不仅将提供可访问的 前端，我们还将开发易于使用、可扩展且支持云的后端，从而实现高效 测序数据的比对。我们提议的项目将使生物医学科学家能够进行实验 跨多个数据集的不同计算方法、输入参数(包括对齐步骤)和 呼吸道病毒感染。因此，便于使用由生成的数据集进行集成和交互分析 多个实验室，以促进我们对宿主对新冠肺炎转录反应的理解。

PROJECT SUMMARY The current pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to global public health concerns. This novel coronavirus disease (COVID-19) shares similar clinical symptoms with diseases caused by other viruses in the coronavirus family and other common respiratory viruses. When an infectious agent replicates within a host organism, the host interacts with, and responds to the virus with various mechanisms. Given the varying severity across patients and emergence of new SARS-CoV-2 variants, there is an urgent need to understand how the host responds to COVID-19 and its variants. RNA sequencing (RNA-seq) data that profile transcriptional response to SARS-CoV-2 and other respiratory viral infections are available from public databases. Comparing the gene signatures across respiratory viruses will identify similarities and differences of how the host responds to these infections. In particular, compendium analyses in which multiple datasets are integrated bring great opportunities for generating novel biological hypotheses. However, compendium analysis of RNA-seq data generated across different laboratories is an onerous task given the different protocols, parameters, software and software versions used at the time of analyses. This proposal focuses on the development of software tools to facilitate re-analyses of existing host-response RNA-seq data to create a compendium of gene signatures using the same set of analytical tools and input parameters. Our deliverables will include workflows with saved input files and parameters, fixed software versions and dependencies that will facilitate reproducibility and collaboration. We will provide an accessible graphical user interface that allows users to create custom signature sets by querying the data and if desired, re-analyzing the data using one of our provided workflows or a workflow of their own choosing. Users will be able to filter biological variables, perform cross species analysis, compare gene signatures to other gene set repositories. In addition, we will create an accessible dashboard that will support the query, download, visualization and reproducible analysis of gene expression data from SARS-CoV-2 and other common respiratory viruses. Tools will be provided to allow the user to interactively visualize the data and inform the choice of appropriate gene signatures. Not only will our software tools and dashboard provide an accessible front end, we will also develop an easy-to-use, scalable and cloud-enabled backend that enables efficient alignment of sequencing data. Our proposed project will empower biomedical scientists to experiment with different computational methods, input parameters (including the alignment step) across multiple datasets and respiratory viral infections. Thus, facilitating integrated and interactive analyses using datasets generated by multiple laboratories to advance our understanding of host transcriptional response to COVID-19.