Using bioinformatics analysis to screen abnormal methylated differentially expressed hub genes of Kawasaki disease and construct diagnostic model.

ABSTRACT:

Objective

By using bioinformatics analysis, abnormal methylated differentially expressed genes (MDEGs) in Kawasaki disease (KD) were identified and a random forest diagnostic model for KD was established.

Methods

The expression (GSE18606, GSE68004, GSE73461) and methylation (GSE109430) profiles was retrieved and download from Gene Expression Omnibus (GEO). We conducted enrichment analyses by using R software. In addition, we constructed a protein interaction network, and obtained 6 hub genes. We used expression profiles GSE100154 from GEO to verify the hub genes. Finally, we constructed a diagnostic model based on random forest.

Results

We got a total of 55 MDEGs (43 hyper-methylated, low-expressing genes and 12 hypo-methylated, high-expressed genes). Six hub genes (C

SUBMITTER: Sun H 

PROVIDER: S-EPMC9706175 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature