Identification of immune- and autophagy-related genes and effective diagnostic biomarkers in endometriosis: a bioinformatics analysis.

ABSTRACT:

Background

To identify autophagy- and immune-related hub genes affecting the diagnosis and treatment of endometriosis.

Methods

Gene expression data were downloaded from the Gene Expression Omnibus (GEO) (GSE11691 and GSE120103 for training, and GSE7305 for validation). By overlapping the differentially expressed genes (DEGs), Weighted gene co-expression network analysis (WGCNA) module genes, and autophagy-related genes (ARGs), and immune-related genes (IRGs) separately, hub genes were identified using the least absolute shrinkage and selection operator (LASSO)and support vector machine recursive feature elimination (SVM-RFE). The hub genes were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. A hub gene-prediction

SUBMITTER: Ji X 

PROVIDER: S-EPMC9843312 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature