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

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 co...

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Bibliographic Details
Published in:Scientific reports 2017-09, Vol.7 (1), p.11597-10, Article 11597
Main Authors: Rogers, Mark F., Shihab, Hashem A., Gaunt, Tom R., Campbell, Colin
Format: Article
Language:English
Subjects:
631/114/2785
639/705/1046
Cancer
Computational Biology - methods
Databases, Genetic
Genome, Human
Genomes
Genomics - methods
Humanities and Social Sciences
Humans
Molecular Sequence Annotation
multidisciplinary
Mutation
Neoplasms - genetics
Point Mutation
ROC Curve
Science
Science (multidisciplinary)
Software
Web Browser
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Summary: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/ .
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-017-11746-4