加权基因共表达网络分析技术在人类肿瘤研究中的应用  

Application of weighted gene co-expression network analysis technology in human tumor research

作　　者：王耀群 陈博[2] 黄甫春 周卫国 张丰 WANG Yaoqun;CHEN Bo;HUANG Fuchun;ZHOU Weiguo;ZHANG Feng(Department of Clinical Medicine,First Clinical Medical College of Anhui Medical University,Hefei 230032,Anhui Province,China;Department of Gastrointestinal Surgery,First Afliated Hospital of Anhui Medical University,Hefei 230022,Anhui Province,China)

机构地区：[1]安徽医科大学第一临床医学院临床医学专业,安徽合肥230032 [2]安徽医科大学附属第一医院胃肠外科,安徽合肥230022

出　　处：《肿瘤》2019年第11期949-954,共6页Tumor

摘　　要：加权基因共表达网络分析(weighted gene co-expression network analysis,WGCNA)技术是一种在高通量基因表达数据中,利用系统生物学思想,寻找基因表达相关性,并构建基因模块,进而发现具有生物学意义模块的高通量数据挖掘算法。近年来,随着人类对疾病的认识深入到基因水平,WGCNA越来越多的应用于各种疾病,尤其在肿瘤相关基因的高通量数据的挖掘之中。并且,随着技术的不断完善,该技术在疾病的发病机制、发展过程和治疗方案等的探索中,由单一的共表达网络分析逐渐发展成为与多种技术诸如基于连锁不平衡的全基因组关联分析、支持向量机联合应用以及创新性应用WGCNA进行高通量数据挖掘。作为基于基因层次的高通量研究方法,WGCNA正发挥着重要作用。Weighted gene co-expression network analysis(WGCNA) technology is a high-throughput gene expression data mining algorithm,which uses the idea of system biology to find the correlation of gene expression and to construct gene modules, so as to further discovery a high-throughput data mining algorithm with biological significance modules. In recent years, with the deep understanding of human diseases to gene level, WGCNA has been used increasingly in the researches of various diseases, especially in mining the highthroughput data about tumor-related genes. Moreover, with the continuous improvement of this technology, the research of this technology in disease pathogenesis, development and treatment etc has been developed from a single co-expression network analysis to the multiple technologies [such as genome-wide association study(GWAS) and support vector machine(SVM)] combined WGCNA or the innovative applicated WGCNA. As a high-throughput research method based on gene level, WGCNA is playing an important role.

关 键 词：肿瘤 计算生物学 高通量筛选分析 加权基因共表达网络分析 

分 类 号：R730.2[医药卫生—肿瘤]