Identification potential biomarkers in pulmonary tuberculosis and latent infection based on bioinformatics analysis.

ABSTRACT:

Background

The study aimed to identify the potential biomarkers in pulmonary tuberculosis (TB) and TB latent infection based on bioinformatics analysis.

Methods

The microarray data of GSE57736 were downloaded from Gene Expression Omnibus database. A total of 7 pulmonary TB and 8 latent infection samples were used to identify the differentially expressed genes (DEGs). The protein-protein interaction (PPI) network was constructed by Cytoscape software. Then network-based neighborhood scoring analysis was performed to identify the important genes. Furthermore, the functional enrichment analysis, correlation analysis and logistic regression analysis for the identified important genes were performed.

Results

A total of 1084 DEGs were identified, including 565 down- and 519

SUBMITTER: Qin XB 

PROVIDER: S-EPMC5031349 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature