Figure 4. Predictive models with anticipated aetiology or origin.

(a) Overview of predictive models for BRCA1-d and BRCA2-d, showing data source, type of model, and loss-of-function (LOF)-set statistics. (b) PR-AUC-E, (c) area under the receiver operator characteristic (AUROC), and (d) the predictive features and their coefficient for individual models. (e–g) Overview of predictive models of TP53-d (as in a–c). (h) For each cohort, the number of structural variants (x-axis; logarithmic) for TP53 LOF tumours (red) versus TP53 wild-type tumours (grey) and (i) the significance of their difference (two-sided Wilcoxon rank-sum test). (j–l) Predictive models of gene deficiencies in colorectal cancers (as in a–c). (m) Number of deletions in repetitive DNA (as in h) and (n) its significance (as in i). (o) The predictive features of each model (as in d) and (p) the percentage of tumours that are co-mutated with MSH3.