Improving the prediction of the functional impact of cancer mutations by baseline tolerance transformation
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 method...
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| Veröffentlicht in: | Genome medicine 2012-11, Vol.4 (11), p.89-89, Article 89 |
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| creator | Gonzalez-Perez, Abel Deu-Pons, Jordi Lopez-Bigas, Nuria |
| description | 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. |
| doi_str_mv | 10.1186/gm390 |
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| source | Springer Online Journals Complete; DOAJ Directory of Open Access Journals; Recercat; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Springer Nature OA/Free Journals; PubMed Central Open Access |
| subjects | Method |
| title | Improving the prediction of the functional impact of cancer mutations by baseline tolerance transformation |
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