Identification of Inflammatory Gene in the Congenital Heart Surgery Patients following Cardiopulmonary Bypass via the Way of WGCNA and Machine Learning Algorithms

Figure 1

Screening of key modules and genes by WGCNA. (a) Clustering dendrogram of samples with trait heat map. (b) Analysis of network topology for various soft-thresholding powers. The left panel shows the scale-free fit index (-axis) as a function of the soft-thresholding power (-axis). The right panel displays the mean connectivity (degree, -axis) as a function of the soft-thresholding power (-axis). (c) Clustering dendrogram of genes, with dissimilarity based on topological overlap, together with assigned module colors. (d) Module-trait associations: each row corresponds to a module eigengene and each column to a trait. Each cell contains the corresponding correlation and value. (e) MM and GS scatter plots for the key module blue. The vertical line is , and the horizontal line is . The key genes of the module are in the box in the upper right corner of the figure.

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