An In-Silico Study to Identify Relevant Biomarkers in Sepsis Applying Integrated Bulk RNA Sequencing and Single-Cell RNA Sequencing Analyses.

ABSTRACT: This study aims to discover sepsis-related biomarkers via in-silico analyses. The single-cell sequencing RNA (sc-RNA) data and metabolism-related genes are obtained from public databases and previous studies, respectively. Cell subpopulations are identified and annotated, followed by performing single-sample geneset enrichment analysis (ssGSEA and identification of differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA) is applied to classify specific gene modules, and the key module is subjected to immune infiltration analysis. The communication between the subclusters of monocytes is visualized. Five cell subpopulations (subcluster C1-5) containing a relatively higher percentage of monocytes are identified, with subcluster C4 having the lowest enrichme

SUBMITTER: Ye Q 

PROVIDER: S-EPMC12003214 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature