Department of Cardiology, Yidu Central Hospital of Weifang, Qingzhou, P.R. China.
Eur Rev Med Pharmacol Sci. 2018 Jun;22(11):3553-3569. doi: 10.26355/eurrev_201806_15182.
This paper aims at screening the common differential genes of coronary atherosclerotic heart disease (CAD) and ischemic cardiomyopathy (ICM), and to conduct pathway analysis and protein-protein interaction (PPI) network analysis for the differential genes.
The CAD and ICM datasets were collected from the Gene Expression Omnibus (GEO) database for human tumors to extract data components of peripheral blood RNA of patients and normal people in GSE71226 and GSE9128 chips; "limma" package of "R" software was used to screen the differential genes, and "pheatmap" package was applied to construct heat maps for the differential genes; Cytoscape, Database for Annotation, Visualization and Integration Discovery (DAVID) and String platforms were utilized for PPI network analysis, Genome Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis on the selected differential genes.
A total of 575 differential genes were screened from GSE71226, including 350 genes with up-regulated expression and 225 with down-regulated expression, which was statistically significant (p<0.05, fold change >1). 75 differential genes were screened from GSE9128, including 47 genes with up-regulated expression and 28 with down-regulated expression. By virtue of String, DAVID and Cytoscape software, the PPI network diagram was constructed, and GO and KEGG analyses were performed successfully.
A total of 8 common differential genes are screened, and functional annotation and pathway analysis are conducted, which is conducive to further studying the interactions between the differentially expressed genes.
筛选冠心病和缺血性心肌病的常见差异基因,并对差异基因进行通路分析和蛋白质-蛋白质相互作用(PPI)网络分析。
从基因表达综合数据库(GEO)中收集人类肿瘤的 CAD 和 ICM 数据集,以提取 GSE71226 和 GSE9128 芯片中患者和正常人外周血 RNA 的数据成分;使用“R”软件中的“limma”包筛选差异基因,并使用“pheatmap”包构建差异基因的热图;利用 Cytoscape、数据库注释、可视化和综合发现(DAVID)和 String 平台对选定的差异基因进行 PPI 网络分析、基因组本体论(GO)分析和京都基因与基因组百科全书(KEGG)分析。
从 GSE71226 中筛选出 575 个差异基因,其中 350 个基因表达上调,225 个基因表达下调,差异有统计学意义(p<0.05,倍数变化>1)。从 GSE9128 中筛选出 75 个差异基因,其中 47 个基因表达上调,28 个基因表达下调。通过 String、DAVID 和 Cytoscape 软件构建了 PPI 网络图,并成功进行了 GO 和 KEGG 分析。
共筛选出 8 个共同差异基因,并进行了功能注释和通路分析,有助于进一步研究差异表达基因之间的相互作用。