Fig. 1

The landscape of exome-based driver events MM. a Landscape of driver mutations in MM. Each bar represents a distinct positively selected gene and each bar’s color indicates its prevalence across the main MM cytogenetic subgroups. b We built the optimal Bayesian network by considering the recurrent SVs and CNAs (n = 14) and driver SNVs (n = 55) across 724 MM patients, where the final list of 69 variables was assessed. To further investigate the type of recurrence patterns we fitted logic gates between parent and child nodes in the network. The gate combination with the most significant Fisher exact test p value was selected. The line width is proportional to the log hazard ratio of the test. Dashed lines represent non-significant associations (p > 0.05). CNAs and translocations were colored in brown and light blue respectively. The thickness of the outline of each box is proportional to the prevalence of the event across the entire series. c The heatmap showing the main MM genomic subgroups across 724 MM patients. The genomic profile of each cluster was generated by integrating the hierarchical Dirichlet process and Bayesian network data. Rows in the graph represent individual genomic lesions, and the columns represent patients