Table 1.
CEO microarray chip information.
Fig 1.
Flow chart for the comprehensive analysis of NRDEGs.
GSEA, gene set enrichment analysis; DEGs, differentially expressed genes; NRGs, NETosis-related genes; NRDEGs, NETosis-related differentially expressed genes; GO, gene ontology; KEGG, Kyoto encyclopedia of genes and genomes; PPI, Protein-protein interaction; ROC curve, Receiver operating characteristic curve; TF, Transcription factor.
Fig 2.
Batch effects removal of GSE134347 and GSE26440.
A. before going to batch processing integrated GEO dataset (Combined Dataset) distribution box plot. B. Post-batch integrated GEO dataset (Combined Dataset) distribution boxplots. C. PCA plot of the datasets before debatching. D. to batch processing of the integration of GEO datasets (Combined Dataset) of PCA. PCA, Principal Component analysis; Red for sepsis GSE134347 dataset, blue for sepsis GSE26440 dataset.
Fig 3.
Differential gene expression analysis.
A. Combined Dataset in Sepsis group and Control group volcanic diagram analysis of differentially expressed genes. B. Combined Dataset of DEGs and NRGs Venn diagram. C. Combined Dataset neutrophilic inflammation in NRDEGs heat maps. Pale red for Sepsis, light blue for Control. Red represents high expression in heat map, blue represents lower expression.
Fig 4.
GO and KEGG enrichment analysis for NRDEGs.
A. Bubble diagram of gene ontology (GO) and pathway (KEGG) enrichment analysis results of NRDEGs: biological process (BP), cell Component (CC), molecular function (MF) and biological pathway (KEGG). Abscissa to GO terms and KEGG terms. B-E. NRDEGs differentially expressed genes related to the gene ontology (GO) and pathway enrichment analysis results (KEGG) network diagram shows: BP (B), CC (C), MF (D) and KEGG (E). Red nodes represent items, blue nodes represent molecules, and the lines represent the relationship between items and molecules. GO KEGG selection criteria for adj. (p < 0.05) and FDR value (q value) < 0.25, p value correction methods for BH.
Table 2.
Results of GO and KEGG enrichment.
Fig 5.
A. four biological functions mountain map of GSEA of Combined Dataset. B-E. GSEA showed that all genes were significantly enriched in Selenoamino Acid Metabolism(B), IL5 Pathway(C), Natural Killer Cell Mediated Cytotoxicity(D). Neutrophil Degranulation (E). The screening criteria of GSEA were adj. p < 0.05 and FDR value (q value) < 0.25, and the p value correction method was BH.
Table 3.
Results of GSEA for combined dataset.
Fig 6.
PPI network and hub genes analysis.
A. STRING database calculation of neutrophils differentially expressed genes related to inflammation cell death protein-protein interaction network. B-F. CytoHubba plug-in calculated need neutrophils differentially expressed genes related to inflammation cell death of PPI network, including the MCC (B), newsun focus (C), Degree (D), EPC (E) and Closeness (F). G. CytoHubba need the five kinds of algorithms of the plugin neutrophils differentially expressed genes related to inflammation cell death (NRDEGs) Venn diagram. PPI network, interaction network; NRDEGs, differentially expressed genes.
Fig 7.
A. Genetic variations associated with neutrophilic inflammation cell death mRNA - miRNAs regulation Network. B. Neutrophils genetic variations associated with inflammatory cell death mRNA-TF control network (mRNA-TF regulatory network). mRNA are shown in purple, miRNAs in blue, and TFs in orange.
Fig 8.
Expression difference and ROC curve analysis.
A. The hub genes linked to the neutrophilic inflammation cell death (hub genes) in the integration of Combined Dataset the grouping comparison chart. B-J: Expression values have significant differences in group comparison chart of neutrophilic inflammation cell death related to the hub genes: MPO(B), ELANE(C), PRTN3(D), CTSG(E), MMP9(F), CAMP(G), ITGAM(H), CXCR2(I), FCGR3B and(J) of the ROC curve. ROC, Receiver Operating Characteristic Curve. On behalf of p value < 0.001, highly statistically significant. The closer AUC is to 1, the better the diagnosis results, AUC in 0.5 ∼ 0.7 with low accuracy, and AUC in 0.7 ∼ 0.9 has a certain accuracy. Grouping is red for Sepsis group, blue for Control group.
Fig 9.
Combined dataset immune infiltration analysis by CIBERSORT algorithm.
A - B. Immune cells in the integration of Combined Dataset of than histogram (A) and (B) grouping comparison chart. C. Correlation heatmap of immune cell infiltration abundance in the integrated Combined Dataset. D. Hub genes in the integration of Combined Dataset and immune cell infiltration in abundance the relevance of the bubble chart. ** on behalf of the p < 0.01, there is highly statistically significant; *** represents p < 0.001 and highly statistically significant. The absolute value of correlation coefficient (r value) below 0.3 was weak or no correlation, between 0.3 and 0.5 was weak correlation, between 0.5 and 0.8 was moderate correlation, and above 0.8 was strong correlation. Red for Sepsis group, blue for Control group. Is positively related to green as the negative correlation, orange, color shades on behalf of the correlation.