Identification of key genes associated with sepsis patients infected by staphylococcus aureus through weighted gene co-expression network analysis.

ABSTRACT: The prevention and treatment of staphylococcus aureus septicemia is one of the thorniest problems in modern medicine. However, as the underlying pathogenesis of sepsis is still unclear, there is currently no golden standard for clinical diagnosis. In this study, we used GSE33341 dataset for differentially expressed gene (DEG) analysis and screened out 857 differentially expressed genes associated with staphylococcus aureus infection. The module having the highest correlation with clinical features of sepsis was screened by weighted gene co-expression network analysis (WGCNA). The genes in the selected module and the differentially expressed genes were represented in Venn diagram, and 59 pathogenic genes at the intersection were obtained. GO and KEGG analysis showed that these genes were ma

SUBMITTER: Wu H 

PROVIDER: S-EPMC8748107 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature