Identification of key genes associated with rheumatoid arthritis with bioinformatics approach.

ABSTRACT: We aimed to identify key genes associated with rheumatoid arthritis (RA).The microarray datasets of GSE1919, GSE12021, and GSE21959 (35 RA samples and 32 normal controls) were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) in RA samples were identified using the t test in limma package. Functional enrichment analysis was performed using clusterProfiler package. A protein-protein interaction (PPI) network of selected DEGs was constructed based on the Human Protein Reference Database. Active modules were explored using the jActiveModules plug-in in the Cytoscape Network Modeling package.In total, 537 DEGs in RA samples were identified, including 241 upregulated and 296 downregulated genes. A total of 24,451 PPI pairs were collected, and 5 active m

SUBMITTER: Gang X 

PROVIDER: S-EPMC5626145 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature