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: 10618134
• 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 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10618134
• 关键词: 2019-nCoV; Bioinformatics; Biological; COVID-19; COVID-19 pandemic; Clinical; Code; Collaborations; Communities; Computer software; Computing Methodologies; Coronavirus; Custom; Data; 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; biomedical scientist; coronavirus disease; current pandemic; dashboard; data integration; data visualization; diagnostic strategy; differential expression; empowerment; experimental study; genetic signature; genomic data; graphical user interface; knowledge base; large scale data; multiple datasets; novel; novel coronavirus; 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.

项目总结