Detection and assessment of immune and stromal related risk genes to predict preeclampsia: A bioinformatics analysis with dataset.

ABSTRACT: This study aimed to investigate immune score and stromal score-related signatures associated with preeclampsia (PE) and identify key genes for diagnosing PE using bioinformatics analysis. Four microarray datasets, GSE75010, GSE25906, GSE44711, and GSE10588 were obtained from the Gene Expression Omnibus database. GSE75010 was utilized for differential expressed gene (DEGs) analysis. Subsequently, bioinformatic tools such as gene ontology, Kyoto Encyclopedia of Genes and Genomes, weighted gene correlation network analysis, and gene set enrichment analysis were employed to functionally characterize candidate target genes involved in the pathogenesis of PE. The least absolute shrinkage and selection operator regression approach was employed to identify crucial genes and develop a predictive mo

SUBMITTER: Qin H 

PROVIDER: S-EPMC11466178 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature