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Sci Rep. 2017 Sep 14;7(1):11597. doi: 10.1038/s41598-017-11746-4.

CScape: a tool for predicting oncogenic single-point mutations in the cancer genome.

Author information

1
Intelligent Systems Laboratory, University of Bristol, Bristol, BS8 1UB, United Kingdom. Mark.Rogers@bristol.ac.uk.
2
MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, BS8 2BN, United Kingdom.
3
Intelligent Systems Laboratory, University of Bristol, Bristol, BS8 1UB, United Kingdom.

Abstract

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/ .

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