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Fig. 4 | BMC Medical Genomics

Fig. 4

From: Integrated network analysis and logistic regression modeling identify stage-specific genes in Oral Squamous Cell Carcinoma

Fig. 4

Analysis of expression data on oral squamous cell carcinoma (OSCC) in the WGCNA software. WGCNA: Weighted Gene Correlation Network Analysis. Suitability of the pink module is clearly visible.a A heatmap of module eigengenes (MEs) and correlations, where each row represents a module (labeled by color), and each column represents a trait. The value at the top of each square represents Pearson’s correlation coefficient between the MEs and trait, along with the associated p-value in parentheses. The red and blue colors represent a strong positive and negative correlation, respectively, between a ME and a trait. b Module significance (MS) of all modules, with pink at the top of the plot, indicating that expression profiles of the pink module are strongly associated with the trait. c Analysis of topological robustness of the pink module via plotting of a simultaneous node deletion against changes in the size of the largest component, σ(ρ), when the fraction ρ of the vertices (nodes) was removed. The results indicate network robustness. d The plot of gene significance (GS i GS) against scaled connectivity (K i ) where each point (“darkgolden” and “darkcyan”) corresponds to a gene in the pink module. Intramodular connectivity significantly correlated with gene significance (r = 0.36, p = 8.3 × 10−5). All large labeled nodes (GS i >0.2 and K i  > 0.3) are the identified hubs. Among these, darkgolden nodes represent hubs with the strongest correlation with the phenotype (GS i >0.2, K i  > 0.3, and f >675); these hubs represent “key hub genes”

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