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

宿主对 COVID-19 和其他呼吸道病毒感染的转录反应的综合和交互式分析

• 批准号: 10372463
• 负责人: Ka Yee Yeung-Rhee
• 金额: $ 7.77万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-05 至 2024-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10372463
• 关键词: 2019-nCoV; Bioinformatics; Biological; COVID-19; COVID-19 pandemic; Clinical; Code; Collaborations; Communities; Computer software; Computing Methodologies; Coronavirus; Custom; Data; Data Analyses; Data Set; Databases; Dependence; Disease; Family; Gene Expression; Gene Expression Profile; Gene Expression Profiling; Gene set enrichment analysis; Generations; Genes; Genetic Transcription; Human; Image; Immune response; Infection; Infectious Agent; Influenza; Intuition; Laboratories; Learning Module; Machine Learning; Manuals; Methodology; Methods; Middle East Respiratory Syndrome Coronavirus; Organism; Patients; Performance; Process; Protocols documentation; Public Health; RNA Processing; RNA analysis; Race; Reproducibility; Respiratory Tract Infections; Rhinovirus; SARS coronavirus; SARS-CoV-2 variant; Selection Criteria; Sequence Alignment; Severities; Software Tools; Specific qualifier value; Symptoms; Technology; Time; Traction; Transcript; Update; Variant; Viral Respiratory Tract Infection; Virus; Virus Diseases; Visualization; analytical tool; base; biomedical scientist; coronavirus disease; dashboard; diagnostic strategy; differential expression; experimental study; genetic signature; genomic data; graphical user interface; knowledge base; large scale data; multiple datasets; novel; novel coronavirus; pandemic disease; portability; prototype; public database; public repository; repository; respiratory virus; response; sex; software development; tool; transcriptome sequencing; treatment strategy; user-friendly; vaccine development; vaccine strategy

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.

项目概要 当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 应对全球公共卫生问题。这种新型冠状病毒病（COVID-19）具有相似的临床症状 与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 感染因子在宿主生物体内复制，宿主与病毒相互作用并对病毒做出反应 各种机制。鉴于患者的严重程度不同以及新的 SARS-CoV-2 变种的出现， 迫切需要了解宿主如何应对 COVID-19 及其变种。 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 可从公共数据库获取。比较呼吸道病毒的基因特征将确定 宿主对这些感染反应的相似点和不同点。特别是，纲要分析 多个数据集的整合为产生新的生物学假设带来了巨大的机会。 然而，对不同实验室生成的 RNA-seq 数据进行概要分析是一项艰巨的任务 考虑到分析时使用的不同协议、参数、软件和软件版本。 该提案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 RNA-seq 数据使用相同的分析工具和输入集创建基因特征概要 参数。我们的交付成果将包括已保存输入文件和参数的工作流程、固定软件 版本和依赖关系将促进可重复性和协作。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来创建自定义签名集，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。用户将会 能够过滤生物变量、执行跨物种分析、将基因特征与其他基因集进行比较 存储库。此外，我们将创建一个可访问的仪表板，支持查询、下载、 对 SARS-CoV-2 和其他常见基因表达数据进行可视化和可重复分析 呼吸道病毒。将提供工具来允许用户交互式地可视化数据并通知 选择适当的基因特征。我们的软件工具和仪表板不仅提供易于访问的 除了前端之外，我们还将开发一个易于使用、可扩展且支持云的后端，以实现高效 测序数据的对齐。我们提出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）以及 呼吸道病毒感染。因此，利用生成的数据集促进集成和交互式分析 多个实验室来加深我们对宿主对 COVID-19 转录反应的理解。