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.

项目摘要 严重的急性呼吸综合症冠状病毒2（SARS-COV-2）引起的当前大流行已导致 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 冠状病毒家族和其他常见呼吸道病毒引起的疾病。什么时候 传染剂在宿主生物中复制，宿主与 各种机制。鉴于患者的严重程度不同，新的SARS-COV-2变体的出现， 迫切需要了解主机对Covid-19及其变体的反应。 RNA测序 （RNA-seq）谱图对SARS-COV-2和其他呼吸道病毒感染的转录响应的数据是 可从公共数据库获得。比较跨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性和差异。特别是，汇编分析 集成了多个数据集为产生新的生物学假设带来了巨大的机会。 但是，对不同实验室生成的RNA-seq数据的汇编分析是一项繁重的任务 给定分析时使用的不同协议，参数，软件和软件版本。 该建议重点是开发软件工具，以促进现有宿主响应的重新分析 RNA-seq数据使用相同的分析工具和输入来创建基因特征的汇编 参数。我们的可交付成果将包括带有保存的输入文件和参数的工作流程，固定的软件 将有助于可重复性和协作的版本和依赖项。我们将提供可访问的 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或自己选择的工作流程之一重新分析数据。用户会 能够过滤生物变量，进行跨物种分析，将基因特征与其他基因组进行比较 存储库。此外，我们将创建一个可访问的仪表板，该仪表板将支持查询，下载， 来自SARS-COV-2和其他常见的基因表达数据的可视化和可重复分析 呼吸道病毒。将提供工具以允许用户交互可视化数据并通知 选择适当的基因签名。我们的软件工具和仪表板不仅会提供可访问的 前端，我们还将开发易于使用，可扩展和启用云的后端 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尝试 不同的计算方法，输入参数（包括对齐步骤），跨多个数据集和 呼吸道病毒感染。因此，使用由数据集生成的数据集来促进集成和交互分析 多个实验室，以促进我们对宿主转录响应对COVID-19的理解。