A gene module identification algorithm and its applications to identify gene modules and key genes of hepatocellular carcinoma.

ABSTRACT: To further improve the effect of gene modules identification, combining the Newman algorithm in community detection and K-means algorithm framework, a new method of gene module identification, GCNA-Kpca algorithm, was proposed. The core idea of the algorithm was to build a gene co-expression network (GCN) based on gene expression data firstly; Then the Newman algorithm was used to initially identify gene modules based on the topology of GCN, and the number of clusters and clustering centers were determined; Finally the number of clusters and clustering centers were input into the K-means algorithm framework, and the secondary clustering was performed based on the gene expression profile to obtain the final gene modules. The algorithm took into account the role of modularity in the clusteri

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC7943822 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature