Subtyping children with asthma by clustering analysis of mRNA expression data.

ABSTRACT: Background: Asthma is a heterogeneous disease. There are several phenotypic classifications for childhood asthma. Methods: Unsupervised consensus cluster analysis was used to classify 36 children with persistent asthma from the GSE65204 dataset. The differentially expressed genes (DEGs) between different asthma subtypes were identified, and weighted gene co-expression network analysis (WGCNA) was carried out. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis was performed for DEGs and critical gene modules. Protein-protein interactions (PPI) were constructed to obtain the hub genes. Finally, differences in the immune microenvironment were analyzed between different subtypes. Results: Two subtypes (C1, C2) were identified using unsupervised c

SUBMITTER: Wang T 

PROVIDER: S-EPMC9500203 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature