加权基因共表达网络在肌少症基因筛选中的应用研究

Application Research on Weighted Gene Co-expression Network Analysis in Gene Screening of Sarcopenia

为克服当前肌少症治疗靶点较少及肌少症基因筛选方法的局限性,提出将加权基因共表达网络用于识别肌少症基因。基于拓扑矩阵构建共表达网络,将相似基因通过层次聚类法和动态剪切树法切割为一个个基因簇,利用主成分分析提取每个基因模块的特征值,计算其与肌少症性状向量的相关性,筛选出与肌少症高度关联的模块,并从中挑选枢纽基因进行验证。通过实验表明,该方法可从16879个基因中筛选出86个枢纽基因,并成功验证了69个,准确率为80.2%,相较于传统方法约提高了40%。

In order to solve the limitations of few therapeutic targets and gene screening methods for sarcopenia,a weighted gene coexpression network was proposed to identify sarcopenia genes.The coexpression network is constructed based on the topological matrix,the similar genes are cut into gene clusters by hierarchical clustering method and dynamic shear tree method,the eigenvalues of each gene module are extracted by principal component analysis,the correlation between the eigenvalues of gene modules and the trait vector of sarcopenia is calculated,the modules highly associated with sarcopenia are screened,and their hub genes are selected for verification.The experiment shows that 86 hub genes can be screened from 16,879 genes,and 69 are successfully verified.The accuracy is 80.2%,which is about 40%higher than that of traditional methods.