Screening of atrial fibrillation diagnostic markers based on a GEO database chip and bioinformatics analysis.

ABSTRACT:

Background

Study have shown that atrial fibrillation (AF) is a disease with genetic risk, and its pathogenesis is still unclear. This study sought to screen the gene microarray data of AF patients and to perform a bioinformatics analysis to identify AF signature diagnostic genes.

Methods

The AF gene sets from the Gene Expression Omnibus (GEO) database were screened, and the differentially expressed genes (DEGs) were identified after the normalization of the data set by R software. We conducted a gene set enrichment analysis, a protein-protein interaction (PPI) network analysis, a gene-gene interaction (GGI) network analysis, and an immuno-infiltration analysis. The core genes were identified from the DEGs, and base on receiver operating characteristic, the top 5 core genes i

SUBMITTER: Wei B 

PROVIDER: S-EPMC9840052 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature