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Fig. 2 | BMC Pediatrics

Fig. 2

From: Bioinformatic analysis of underlying mechanisms of Kawasaki disease via Weighted Gene Correlation Network Analysis (WGCNA) and the Least Absolute Shrinkage and Selection Operator method (LASSO) regression model

Fig. 2

Weighted gene correlation network analysis (WGCNA) and functional annotations of the hub genes. A The heatmap of top 10 up- and down-regulated genes between Kawasaki disease (KD) patients and health controls (HC). Row: genes, Columns: samples. Colors indicate the gene expression level, in which red means high level and blue means low level. B Cluster dendrogram represents the distribution of genes with corresponding module colors, which incorporates a sum of 2 modules, and genes that don’t co-express with other genes are divided into the gray module. C Module-trait correlation heatmap. Numbers in the upper left corners represent the correlation coefficient of modules to traits, red color represents positive correlation, and green color represents negative correlation. Numbers in the lower right corners means the p-values. Each row symbolizes a module eigengene and each column symbolizes a trait. Sex(F): female; Sex(M): male. D The bubble plot displays the significant enriched biological processes (BPs) of 80 genes. E The bubble plot shows the significant enriched pathways of 80 genes. The color of the dots refers to the -log10 (p-value), and the size of the dots refers to the number of DEGs mapped to the indicted pathways, respectively. The significant biological processes and pathways are selected according to p-value < 0.05

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