Identifying Obstructive Sleep Apnea Syndrome-Associated Genes and Pathways through Weighted Gene Coexpression Network Analysis.

ABSTRACT:

Background

Obstructive sleep apnea syndrome (OSAS) is the most common type of sleep apnea disorder. The disease seriously affects the patient's respiratory system. At present, the prognosis of the disease is poor and there is a lack of effective treatments. Therefore, it is urgent to explore its pathogenesis and treatment methods.

Method

We downloaded a set of expression profile data from GSE75097 related to OSAS based on the Gene Expression Omnibus (GEO) database and selected the representative differentially expressed genes (DEGs) from the sample of the GSE75097 dataset. WGCNA was used to find genes related to OSAS and obtain coexpression modules. The Gene Ontology (GO) function and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were used to analyze genes from

SUBMITTER: Li Y 

PROVIDER: S-EPMC8817882 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature