Figure 4

Boxplot of best AUC values for all 90 compounds across 6 data types. For all data types, the highest AUC obtained with either approach (LS-SVM in red circles, or random forest in blue squares) is displayed. For RNAseq and exon array, the highest AUC is shown among models built on gene-level data only versus all features (exons, junctions, and so on). The one-way repeated measures ANOVA test revealed a significant difference in performance among any of the data types (P-value 2.6e-5). Post hoc pairwise comparisons with multiple testing correction revealed a significant outperformance of RNAseq with respect to all other data types. SNP6 copy number performed significantly worse compared to all other data types, and exon array additionally significantly outperformed U133A.