Figure 3.
RNA sequencing-based model classification performance
(A) Mean AUROC curves and performance across TPR and FPR for the indicated seven classification models.
(B) Confusion matrices for the same models described in (A). n, number of samples after ROSE-based gender balancing (STAR Methods).
(C) Upset plot of the machine learning models using all preoperative samples from seven assessed comparisons referring to different postoperative outcomes. Set size indicates the number of differentially expressed genes (DEGs) used in each comparison. Interaction size indicates the number of DEGs common across different comparisons. The interaction matrix indicates the number of shared DEGs across different classification models.
(D) Heatmap representing the top 5 most important DEGs as indicated by the highest mean importance value using the varImp function of the R caret package across all seven classification models. DEGs shared by more than one classification model are indicated in bold font. Abbreviations: TPR, true positive rate (sensitivity); FPR, false positive rate; CI95, 95% confidence interval.