基于加权基因共表达网络分析阿尔茨海默病相关核心靶点(英文)
发布时间:2021-11-26 04:44
目的阿尔茨海默病(Alzheimer‘s disease,AD)是痴呆症最常见的病因,但其发病机制尚不明确。本研究拟通过加权基因共表达网络探究AD发病相关的核心靶点。方法 GSE36980数据集下载于高通量基因表达数据库(Gene Expression Omnibus, GEO)。首先进行数据标准化,质控和过滤,以及计算软阈值,然后根据基因表达的相关性,聚类划分为不同的模块,通过计算各模块与临床特征的相关系数,确定关键基因模块。我们通过基因富集分析(Gene Ontology,GO)和通路富集分析(Kyoto Encyclopedia of Genes and Genomes, KEGG)探究关键基因模块中的基因功能。随后通过STRING数据库构建蛋白-蛋白相互作用网络,并使用Cytoscape软件MCODE插件进行网络拓扑分析筛选核心调控基因,最后使用GEO外部数据集GSE1297和GSE28146对核心基因进行验证。结果共表达基因共聚类27个模块,其中6个模块与AD发病显著相关,以此作为关键模块用于下游分析。通过基因功能富集分析发现关键模块与神经递质传递(GO:0007268)、三...
【文章来源】:Chinese Medical Sciences Journal. 2020,35(04)CSCD
【文章页数】:12 页
【文章目录】:
MATERIALS AND METHODS
Data source
WGCNA analysis
Identification of significant modules of clinical traits
Intramodular and intermodular analysis
Network construction
Protein-protein interaction network construction
Hub genes validations
Statistical analyses
RESULTS
Key modules of Alzheimer’s disease
Identification of the key modules and the key trait of AD
Intramodular analyses and intermodular analyses
Module genes GO and KEGG analysis
Identification of hub genes
PPI network analysis
Hub genes validations
DISCUSSION
Conflict of interests
Supplementary matierials
本文编号:3519421
【文章来源】:Chinese Medical Sciences Journal. 2020,35(04)CSCD
【文章页数】:12 页
【文章目录】:
MATERIALS AND METHODS
Data source
WGCNA analysis
Identification of significant modules of clinical traits
Intramodular and intermodular analysis
Network construction
Protein-protein interaction network construction
Hub genes validations
Statistical analyses
RESULTS
Key modules of Alzheimer’s disease
Identification of the key modules and the key trait of AD
Intramodular analyses and intermodular analyses
Module genes GO and KEGG analysis
Identification of hub genes
PPI network analysis
Hub genes validations
DISCUSSION
Conflict of interests
Supplementary matierials
本文编号:3519421
本文链接:https://www.wllwen.com/yixuelunwen/jsb/3519421.html
最近更新
教材专著