Figure 7. Genome graph-derived features define biologically distinct patient groups.

(A) Heatmap of normalized junction burden across 2,487 unique patients yields 14 clusters named after their most prevalent event types (CT, chromothripsis; TYF, tyfonas; BFB, BFBC; BR, BFBC and rigma; SPRS, sparse; CP, chromoplexy; TIC, templated insertion chain; TRA, translocations; DM, double minute; PYR, pyrgo; DUP, various duplications; DDT, deletion, duplication, and TIC; INVD, inverted duplications). (B-C) Significantly enriched tumor types within and outside of selected clusters. Blue (vs. gray) bars indicate the fraction of cases within (vs. outside of) the cluster that have the given feature, e.g. tumor type (B) or mutation (C). Significance in (B) and (C) determined by Bayesian logistic regression (Wald Test), with significant results (FDR < 0.1) for 742 hypotheses in (B) and 4,774 hypotheses in (C) (see STAR Methods). (D) Kaplan-Meier curves across BR, PYR and TYF clusters. P-values obtained via log-rank test. (E) Cox proportional hazard analysis correcting for age, tumor type, sex, metastasis status, tumor mutational burden, SV junction burden, and TP53 status demonstrating confidence bounds on the adjusted hazard ratio for 13 clusters relative to the QUIET cluster. Significantly associated variables (FDR < 0.1, 13 hypotheses) colored in red. Error bars on bar plots represent 95% confidence intervals on the Bernoulli trial parameter. See also Fig. S7 and Tables S3, S4