Fig. 2

Quantitative views into the ten topmost contributing features of the gain and loss models. Features are ordered from bottom to top by their increased average absolute contribution to the model, as calculated by SHAP. A The average absolute contribution of each feature to the gain model. The directionality of the feature (i.e., whether high feature values correspond to gain or neutral) is represented by an arrow. B A detailed view of the contribution of each feature to the gain model. Per feature, each dot represents the contribution per instance of a chromosome-arm and cancer type pair. The dots are spread based on whether they were classified as neutral (left) or gain (right) by the model. Instances are colored by the feature value (green-to-orange scale denotes low-to-high value). The order (height) of each feature is the same as in A. C Same as panel A for the loss model. D Same as panel B for the loss model. E The correlations between top contributing features and the frequencies of chromosome-arm gains and losses, as measured by Spearman correlation. P-values were adjusted for multiple hypothesis testing using Benjamini–Hochberg procedure. Negative correlation between TSG density and gain frequency (ρ = − 0.52, adjusted p = 0.006). Positive correlation between TSG density and loss frequency (ρ = 0.3, adjusted p = 0.17). Positive correlation between OG density and gain frequency (ρ = 0.25, adjusted p = 0.18). Negative correlation between OG density and loss frequency (ρ = − 0.47, adjusted p = 0.01). Positive correlation between TCGA expression and gain frequency (ρ = 0.29, adjusted p = 0.14). Negative correlation between TCGA expression and loss frequency (ρ = − 0.33, adjusted p = 0.12). Positive correlation between essential gene density and gain frequency (ρ = 0.16, adjusted p = 0.37). Negative correlation between essential gene density and loss frequency (ρ = − 0.1, adjusted p = 0.5)