Fig 1.
Flow chart of the bioinformatics analysis.
Table 1.
RNA-seq expression profile data set from GEO database.
Table 2.
Iron death factors.
Fig 2.
Heat maps of iron death factor expression clustered by sample type (A) and gender (B).
Fig 3.
Cluster classification results of diabetic nephropathy samples.
Fig 4.
Differential gene expression analysis diagram and principal component analysis.
(A) Volcano map. The green dots, down-regulated differential genes; the red dots, up-regulated differential genes; the gray dots, genes that are not differentially expressed. Sixteen of the iron death genes are among the differentially expressed genes. (B) Heat map of differential gene expression. The abscissa represents gene clustering. The more the genes are expressed in the same amount in the sample, the closer they are in the figure. The ordinate represents the clustering of samples. The more the gene expression levels are the same among samples, the closer they are in the picture. The color scale represents the abundance of gene expression. The red presents up-regulation and the blue presents the down-regulation. (C) Principal component analysis based on differentially expressed genes.
Fig 5.
Gene function enrichment analysis: GO function enrichment analysis (A) and KEGG pathway enrichment analysis (B).
Fig 6.
Soft threshold screening (A), hierarchical clustering graph (B) and trait association analysis result graph (C).
Fig 7.
Protein interaction screening candidate key genes (A), Modular gene significance screening candidate key genes (B) and the Venn diagram (C).
Fig 8.
Hub gene correlation analysis and expression differences in different types.
Hub gene correlation analysis (A). Differential analysis of Hub gene expression in different types (B).
Fig 9.
Hub gene multi-factor regulatory network.
Colors and shapes indicate different factor types. Green is hub gene mRNA, pink is transcription factor, and purple is non-coding gene miRNA.