Fig. 6 | Scientific Reports

Fig. 6

From: Machine learning analysis of gene expression profiles of pyroptosis-related differentially expressed genes in ischemic stroke revealed potential targets for drug repurposing

Fig. 6

Correlation analysis of Common PRDEGs. (A) LASSO regression models for PRDEGs and SVM models, Venn plots for PRDEGs in random forest models. (B,C) Chord plots for the 10 Common PRDEGs (B), correlation heat map (C). (D–I) Correlation scatter plots for Common PRDEGs: GSK3B and STAT3 (D), ATF6 and GSK3B (E), IKBKE and NDUFA13 (F), BNIP3L and IKBKE (G), ELAVL1 and STAT3 (H), and BIRC2 and NDUFA13 (I) correlation scatterplot results are shown. P ≥ 0.05, not statistically significant; P < 0.05, statistically significant; P < 0.01, highly statistically significant; P < 0.001, highly statistically significant. Correlation coefficients (r) in correlation scatter plots with absolute values above 0.8 are strongly correlated; absolute values between 0.5 and 0.8 are moderately correlated; absolute values between 0.3 and 0.5 are weakly correlated; absolute values below 0.3 are weakly or not correlated. LASSO least absolute shrinkage and selection operator, SVM support vector machine, PRDEGs pyroptosis-related differentially expressed genes.

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