| 引用本文: | 郑德华,许达华,毕小慢,曹勐,徐智洲,陈荔旸,李思,鲁健平,李孔宁.基于ceRNA网络识别登革热诊断标志物[J].生物信息学,2023,21(4):304-310. |
| ZHENG Dehua,XU Dahua,BI Xiaoman,CAO Meng,XU Zhizhou,CHEN Liyang,LI Si,LU Jianping,LI kongning.Identification of dengue diagnostic markers based on ceRNA network[J].Chinese Journal of Bioinformatics,2023,21(4):304-310. |
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| 基于ceRNA网络识别登革热诊断标志物 |
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郑德华1,许达华1,毕小慢1,曹勐1,徐智洲1,陈荔旸1,李思1, 鲁健平2,李孔宁1
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(1.海南医学院 生物医学信息与工程学院 热带转化医学教育部重点实验室,海口 570099; 2.哈尔滨医科大学 生物信息科学与技术学院,哈尔滨 150076)
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| 摘要: |
| 通过比较登革热患者和健康人群转录组数据,识别差异基因,构建失调ceRNA网络,筛选关键基因富集分析,解析潜在生物学功能,助力登革热诊断标志物的研究。从GEO数据库下载登革热外周血芯片数据,识别差异基因并进行富集分析。结合miRNA-mRNA互作数据,利用超几何算法和皮尔森相关性计算方法识别登革热失调ceRNA互作对,使用Cytoscape软件可视化ceRNA网络与模块挖掘,对网络模块进行功能富集及外部数据验证表达模式。筛选出251个差异基因,发现其富集在细胞周期等生物学通路中。经外部数据验证,网络模块基因的表达趋势与训练集数据大致相同,表明模块基因在登革热疾病中的潜在诊断效能。本研究可为确定有效的疾病诊断分子标志物提供思路。 |
| 关键词: 登革热 竞争性内源RNA(ceRNA) 富集分析 网络模块 |
| DOI：10.12113/202209011 |
| 分类号:R3 |
| 文献标识码:A |
| 基金项目: |
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| Identification of dengue diagnostic markers based on ceRNA network |
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ZHENG Dehua1, XU Dahua1, BI Xiaoman1, CAO Meng1, XU Zhizhou1, CHEN Liyang1, LI Si1, LU Jianping2, LI kongning1
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(1.College of biomedical information and Engineering, Key Laboratory of Tropical Translational Medicine of Ministry of Education, Hainan Medical University, Haikou 570099, China;2.College of bioinformatics science and technology, Harbin Medical University, Harbin 150076, China)
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| Abstract: |
| Differentially expressed genes were systematically indentified by analyzing transcriptome data of dengue fever patients and healthy samples. Then a competing endogenous RNA (ceRNA) network was constrcuted and essential genes were indentified. The potential biological functions were revealed through enrichment analysis. This study can give an insight into the development of diagnostic markers for dengue disease. The differential expression gene and enrichment analysis were performed based on the microarray data from the GEO database for dengue. Through integration of the StarBase dataset, hypergeometric and Pearson correlation methods, we identified ceRNA interactions for dengue disease. The visualization and the screening of ceRNA network modules were performed by Cytoscape software. We also performed enrichment analysis and verified the expression pattern of ceRNA in an external dataset and identified 251 differentially expressed (DE) genes, The DE genes were significantly enriched in several biological processes like cell cycle. The expression pattern of network module genes was verified in the external dataset, indicating the potential diagnostic efficacy of the ceRNA network module in dengue disease. This study can provide insights for identifying effective molecular markers for disease diagnosis. |
| Key words: Dengue Fever Competitive endogenous RNA (ceRNA) Enrichment analysis Network module |
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