CScape: a tool for predicting oncogenic single-point mutations in the cancer genome - Rogers, Mark F.; Shihab, Hashem A.; Gaunt, Tom R.; Campbell, Colin (Scientific reports, 2017)
For somatic point mutations in coding and non-coding regions of the genome, we propose CScape , an integrative classifier for predicting the likelihood that mutations are cancer drivers. Tested on somatic mutations, CScape tends to outperform alternative methods, reaching 91% balanced accuracy in coding regions and 70% in non-coding regions, while even higher accuracy may be achieved using thresholds to isolate high-confidence predictions. Positive predictions tend to cluster in genomic regions, so we apply a statistical approach to isolate coding and non-coding regions of the cancer genome that appear enriched for high-confidence predicted disease-drivers. Predictions and software are available at http://CScape.biocompute.org.uk/ .