Figure 2.

Identifying the circRNA signature in the training dataset. (A) Univariate Cox proportional hazards regression analysis of circRNA expression profiling data in the training dataset. (B) Procedure of the random forest supervised classification algorithm. (C) Procedure for identifying the final signature. The accuracies of all 511 signatures were calculated, and the 9 highest accuracies for k=1–9 are presented in the plot. (D) Receiver operating characteristic curve for the circRNA signature prediction model in the training dataset. CircRNA, circular RNA; AUC, area under the curve; PFS, progression-free survival.