Fig. 6

Assessment using a benchmark dataset based on in vitro cell viability. a Overview of the assessment process. For each mutation, we performed cell viability assays in two “informer” cell lines, Ba/F3 and MCF10A. Consensus calls were inferred by integrating the functional effects observed in Ba/F3 and MCF10A. We considered activating, inactivating, inhibitory, and non-inhibitory mutations as positive cases, while neutral mutations were considered negative. b The ROC curves of the 33 algorithms based on a combined set of published mutations (Ng et al. [42]) and newly generated mutations in this study. c Bar plots showing the AUC scores of the 33 algorithms in the three datasets: new functional data (red), published functional data (green), and the combined set (blue). d Boxplots showing the differences of AUC between two groups of algorithms with or without certain features. p values are based on the Wilcoxon rank sum test. d Sensitivity and specificity of 33 algorithms. Error bars, mean ± 2SD