Known cancer genes are differentially mutated across 24 cancer types. a The fraction of genes that are in a set of known cancer driver genes  when we rank genes by uEMD scores as computed by DiffMut, our method for differential mutation analysis, and consider an increasing number of top-ranked genes. When computing uEMD scores using non-silent mutations, we find that a large fraction of the highest scoring genes are cancer driver genes (black line). When uEMD scores are computed based on silent mutations instead, we do not see an enrichment for cancer driver genes (gray). b For each cancer type, we ranked all genes by uEMD scores using either non-silent mutations or silent mutations. We then computed the log2 fold change in AUPRC using non-silent mutations as compared to silent mutations. As expected, AUPRCs are significantly higher when using non-silent mutations (left). When computing the log2 fold change in AUPRC when ranking genes by uEMD scores when using non-silent mutations compared to ranking them using their non-silent mutation rate, we also see a notable improvement across all cancer types (right).