Nature research paper: Mapping clustered mutations in cancer reveals APOBEC3 mutagenesis of ecDNA
-test unless otherwise specified. For each set of tests,values were corrected for multiple hypothesis testing using the Benjamini–Hochberg FDR procedure. The predicted effect of each overlapping variant was determined using ENSEMBL’s Variant Effect Predictor tool by reporting only the most severe consequenceAll survival analyses, including the generation of Kaplan–Meier curves, Cox regressions and log-rank tests, were performed using the Lifelines Python package .
Analysis of whole-exome-sequenced samples from TCGA was altered to reflect the limited resolution for identifying clustered mutations within the exome. Specifically, SigProfilerSimulator was used to derive an IMD cut-off for each sample based on the TMB within the exome and the mutational patterns for a given sample.
For both PCAWG and TCGA analyses, survival distributions within a given cancer type were compared using a log-rank test. Cox regressions were performed to determine hazards ratios and to correct for age and total mutational burden. Allvalues were also corrected for multiple hypothesis testing using the Benjamini–Hochberg FDR procedure.
To investigate differential survival associated with the detection of clustered events within cancer driver genes, Kaplan–Meier survival curves were compared between individuals with clustered versus non-clustered mutations within a given cancer driver gene. The distributions were compared using a log-rank test. Cox regressions were performed to determine the hazards ratios and to correct for age, total mutational burden and cancer type across TCGA.
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