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Improving the prediction of the functional impact of cancer mutations by baseline tolerance transformation

Abel Gonzalez-Perez1*, Jordi Deu-Pons1 and Nuria Lopez-Bigas12*

Author Affiliations

1 Research Programme on Biomedical Informatics - GRIB. Universitat Pompeu Fabra - UPF, Hospital del Mar Medical Research Institute - IMIM. Parc de Recerca Biomèdica de Barcelona (PRBB). Dr. Aiguader, 88, E-08003 Barcelona, Spain

2 Institució Catalana de Recerca i Estudis Avançats (ICREA). Passeig Lluís Companys, 23, E-08010, Barcelona, Spain

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Genome Medicine 2012, 4:89  doi:10.1186/gm390

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Published: 26 November 2012


High-throughput prioritization of cancer-causing mutations (drivers) is a key challenge of cancer genome projects, due to the number of somatic variants detected in tumors. One important step in this task is to assess the functional impact of tumor somatic mutations. A number of computational methods have been employed for that purpose, although most were originally developed to distinguish disease-related nonsynonymous single nucleotide variants (nsSNVs) from polymorphisms. Our new method, transformed Functional Impact score for Cancer (transFIC), improves the assessment of the functional impact of tumor nsSNVs by taking into account the baseline tolerance of genes to functional variants.