Identification and validation of differentially expressed chromatin regulators for diagnosis of aortic dissection using integrated bioinformatics analysis and machine-learning algorithms.

ABSTRACT: Background: Aortic dissection (AD) is a life-threatening disease. Chromatin regulators (CRs) are indispensable epigenetic regulators. We aimed to identify differentially expressed chromatin regulators (DECRs) for AD diagnosis. Methods: We downloaded the GSE52093 and GSE190635 datasets from the Gene Expression Omnibus database. Following the merging and processing of datasets, bioinformatics analysis was applied to select candidate DECRs for AD diagnosis: CRs exertion; DECR identification using the "Limma" package; analyses of enrichment of function and signaling pathways; construction of protein-protein interaction (PPI) networks; application of machine-learning algorithms; evaluation of receiver operating characteristic (ROC) curves. GSE98770 served as the validation dataset

SUBMITTER: Liu C 

PROVIDER: S-EPMC9403720 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature