CAJ | 학술논문

WGCNA (weighted gene co-expression network analysis)算法是一种构建基因共表达网络的典型系统生物学算法,该算法基于高通量的基因信使RNA (mRNA)表达芯片数据,被广泛应用于国际生物医学领域.本文旨在介绍WGCNA的基本数理原理,并依托R软件包WGNCA以实例的方式介绍其应用.WGCNA算法首先假定基因网络服从无尺度分布,并定义基因共表达相关矩阵、基因网络形成的邻接函数,然后计算不同节点的相异系数,并据此构建分层聚类树(hierarchical clustering tree),该聚类树的不同分支代表不同的基因模块(module),模块内基因共表达程度高,而分数不同模块的基因共表达程度低.最后,探索模块与特定表型或疾病的关联关系,最终达到鉴定疾病治疗的靶点基因、基因网络的目的.
WGCNA (weighted gene co-expression network analysis)산법시일충구건기인공표체망락적전형계통생물학산법,해산법기우고통량적기인신사RNA (mRNA)표체심편수거,피엄범응용우국제생물의학영역.본문지재개소WGCNA적기본수리원리,병의탁R연건포WGNCA이실례적방식개소기응용.WGCNA산법수선가정기인망락복종무척도분포,병정의기인공표체상관구진、기인망락형성적린접함수,연후계산불동절점적상이계수,병거차구건분층취류수(hierarchical clustering tree),해취류수적불동분지대표불동적기인모괴(module),모괴내기인공표체정도고,이분수불동모괴적기인공표체정도저.최후,탐색모괴여특정표형혹질병적관련관계,최종체도감정질병치료적파점기인、기인망락적목적.
WGCNA (weighted gene co-expression network analysis) is a typical algorithm which is used in gene co-expression network identification. This algorithm is based on high-throughout mRNA gene expression pro-files and being widely used in the international biomedical field. In this article, we will introduce the basic the-ory and it's implementation in R software. Firstly, the scale-free of gene network condition should be satisfied before conducting WGCNA, what's more, it was necessary to define the correlation matrix of gene co-expres-sion and adjacency function. Secondly, the dissimilarity measurements of different nodes were calculated, and then hierarchical clustering tree was built based on these data. Different dendrogram branches represented vari-ous modules. There is much higher co-expression strength among genes in the same module than that in differ-ent modules. At last, it is critical to connect the modules with interesting phenotypes or disease and identity the target genes for disease treatment.