Bioinformatics analysis identifies potential diagnostic signatures for coronary artery disease.

ABSTRACT:

Background

Coronary artery disease (CAD) is the leading cause of mortality worldwide. We aimed to screen out potential gene signatures and construct a diagnostic model for CAD.

Method

We downloaded two mRNA profiles, GSE66360 and GSE60993, and performed analyses of differential expression, gene ontology terms, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The STRING database was used to identify protein-protein interactions (PPI). PPI network visualization and screening out of key genes were performed using Cytoscape software. Finally, a diagnostic model was constructed.

Results

A total of 2127 differentially expressed genes (DEGs) were identified in GSE66360, and 527 DEGs in GSE60993. Of the 153 DEGs from both datasets that showed differential expressi

SUBMITTER: Zhang D 

PROVIDER: S-EPMC7840986 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature