Flu-CED: A comparative transcriptomics database of influenza virus-infected human and animal models.

Q1 Health Professions
Animal models and experimental medicine Pub Date : 2024-12-01 Epub Date: 2024-02-20 DOI:10.1002/ame2.12384
Yue Wu, Jue Wang, Jing Xue, Zhiguang Xiang, Jianguo Guo, Lingjun Zhan, Qiang Wei, Qi Kong
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引用次数: 0

Abstract

Background: The continuing emergence of influenza virus has highlighted the value of public databases and related bioinformatic analysis tools in investigating transcriptomic change caused by different influenza virus infections in human and animal models.

Methods: We collected a large amount of transcriptome research data related to influenza virus-infected human and animal models in public databases (GEO and ArrayExpress), and extracted and integrated array and metadata. The gene expression matrix was generated through strictly quality control, balance, standardization, batch correction, and gene annotation. We then analyzed gene expression in different species, virus, cells/tissues or after antibody/vaccine treatment and imported sample metadata and gene expression datasets into the database.

Results: Overall, maintaining careful processing and quality control, we collected 8064 samples from 103 independent datasets, and constructed a comparative transcriptomics database of influenza virus named the Flu-CED database (Influenza comparative expression database, https://flu.com-med.org.cn/). Using integrated and processed transcriptomic data, we established a user-friendly website for realizing the integration, online retrieval, visualization, and exploration of gene expression of influenza virus infection in different species and the biological functions involved in differential genes. Flu-CED can quickly query single and multi-gene expression profiles, combining different experimental conditions for comparative transcriptome analysis, identifying differentially expressed genes (DEGs) between comparison groups, and conveniently finding DEGs.

Conclusion: Flu-CED provides data resources and tools for analyzing gene expression in human and animal models infected with influenza virus that can deepen our understanding of the mechanisms underlying disease occurrence and development, and enable prediction of key genes or therapeutic targets that can be used for medical research.

Flu-CED:受流感病毒感染的人类和动物模型的比较转录组学数据库。
背景:流感病毒的不断出现凸显了公共数据库和相关生物信息学分析工具在研究不同流感病毒感染引起的人类和动物模型转录组变化方面的价值:流感病毒的不断出现凸显了公共数据库和相关生物信息学分析工具在研究不同流感病毒感染引起的人类和动物模型转录组变化方面的价值:方法:我们在公共数据库(GEO和ArrayExpress)中收集了大量与流感病毒感染的人类和动物模型相关的转录组研究数据,并提取和整合了阵列和元数据。通过严格的质量控制、平衡、标准化、批次校正和基因注释,生成了基因表达矩阵。然后,我们分析了不同物种、病毒、细胞/组织或抗体/疫苗处理后的基因表达,并将样本元数据和基因表达数据集导入数据库:总体而言,在仔细处理和质量控制的基础上,我们从103个独立数据集中收集了8064个样本,并构建了一个流感病毒比较转录组学数据库,命名为Flu-CED数据库(流感比较表达数据库,https://flu.com-med.org.cn/)。利用整合处理后的转录组数据,我们建立了一个用户友好型网站,实现了不同物种流感病毒感染基因表达的整合、在线检索、可视化和探索,以及差异基因所涉及的生物学功能。Flu-CED可快速查询单基因和多基因表达谱,结合不同实验条件进行转录组对比分析,识别对比组间差异表达基因(DEGs),方便查找DEGs:Flu-CED为分析感染流感病毒的人类和动物模型的基因表达提供了数据资源和工具,可加深我们对疾病发生和发展机制的理解,并预测可用于医学研究的关键基因或治疗靶点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.50
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0.00%
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审稿时长
12 weeks
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