Gene correlation network analysis to identify regulatory factors in sepsis.

ABSTRACT:

Background and objectives

Sepsis is a leading cause of mortality and morbidity in the intensive care unit. Regulatory mechanisms underlying the disease progression and prognosis are largely unknown. The study aimed to identify master regulators of mortality-related modules, providing potential therapeutic target for further translational experiments.

Methods

The dataset GSE65682 from the Gene Expression Omnibus (GEO) database was utilized for bioinformatic analysis. Consensus weighted gene co-expression netwoek analysis (WGCNA) was performed to identify modules of sepsis. The module most significantly associated with mortality were further analyzed for the identification of master regulators of transcription factors and miRNA.

Results

A total number of 682 subjects wi

SUBMITTER: Zhang Z 

PROVIDER: S-EPMC7545567 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature