Screening key genes for intracranial aneurysm rupture using LASSO regression and the SVM-RFE algorithm.

ABSTRACT:

Background

Although an intracranial aneurysm (IA) is widespread and fatal, few drugs can be used to prevent its rupture. This study explored the molecular mechanism and potential targets of IA rupture through bioinformatics methods.

Methods

The gene expression matrices of GSE13353, GSE122897, and GSE15629 were downloaded. Differentially expressed genes (DEGs) were screened using the limma package. Functional enrichment analysis was performed, and a PPI network was constructed. Furthermore, candidate key genes were identified using the least absolute shrinkage and selection operator (LASSO) regression model, support vector machine-recursive feature elimination (SVM-RFE) analysis, and PPI network analysis. ROC analysis was conducted to further verify the diagnostic value of th

SUBMITTER: Wu Q 

PROVIDER: S-EPMC11743535 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature