Table 1.
Details of leprosy microarray datasets from GEO database.
Fig 1.
Workflow of bioinformatics analysis.
Fig 2.
A) Obtaining soft-thresholding power by analyzing the scale-free fit index and mean connectivity of network topology. B) Heatmap depicts the Topological Overlap Matrix (TOM) of all genes of the WGCNA network. The darker the color, the higher the overlap. C) Heatmap of module eigengenes and leprosy trait. D) Heatmap of the correlation between module eigengenes and clinical traits. Each row corresponds to a module, and each column corresponds to a trait. Each square is colored according to the corresponding correlation and labels correlation and P value.
Fig 3.
A) Volcano plot of normalized gene expression profile. B) Chromosome mapping of differentially expressed genes. Red color represents up-regulated genes and blue represents down-regulated. C) Heatmap of differentially expressed genes.
Fig 4.
GO annotation and KEGG pathway of crucial genes related to leprosy.
A) Bubble plots showing GO annotations regarding biological process(BP). B) Bubble plots showing GO annotations regarding cellular component(CC). C) Bubble plots showing GO annotations regarding and molecular function(MF). D) Bubble plots showing KEGG pathway.
Fig 5.
PPI Analysis of crucial genes related to leprosy.
A) Protein-protein interaction network of two key components identified based on MCODE. Red color represents MCODE1 genes and blue represents MCODE2 genes. B) The network of immune system pathways and component genes. Oval box represents gene and square box represents pathway. The wider the pathway frame, the more genes the pathway contains.