Identification of key genes and pathways using bioinformatics analysis in septic shock children

Infection and Drug Resistance
Junting YangFang Wu

Abstract

Sepsis is still one of the reasons for serious infectious diseases in pediatric intensive care unit patients despite the use of anti-infective therapy and organ support therapy. As it is well-known, the effect of single gene or pathway does not play a role in sepsis. We want to explore the interaction of two more genes or pathways in sepsis patients for future works. We hypothesize that the discovery from the available gene expression data of pediatric sepsis patients could know the process or improve the situation. The gene expression profile dataset GSE26440 of 98 septic shock samples and 32 normal samples using whole blood-derived RNA samples were generated. A total of 1,108 upregulated and 142 downregulated differentially expressed genes (DEGs) were identified in septic shock children using R software packages. The Gene Ontology (GO) enrichment and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were analyzed using DAVID software; Gene Set Enrichment Analysis method was also used for enrichment analysis of the DEGs. The protein-protein interaction (PPI) network and the top 10 hub genes construction of the DEGs were constructed via plug-in Molecular Complex Detection and cytoHubba of Cytoscape software. From the P...Continue Reading

Citations

May 7, 2020·Pharmaceutics·Vladimir F LazarevBoris A Margulis
Oct 1, 2019·Journal of the Chinese Medical Association : JCMA·Yanjun QinCaiyan Zhao
Mar 20, 2021·Journal of Inflammation Research·Xiaoliang ZengJianfeng Zhang

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Datasets Mentioned

BETA
GSE26440
GPL570

Software Mentioned

Cytoscape
cytoHubba
DAVID
Hubba
R
GSEA
Gene Set Enrichment Analysis ( GSEA )
affy
Bioconductor
limma

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