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

被引：73

作者：

Gonzalez-Perez, Abel ^{[1
]}

Deu-Pons, Jordi ^{[1
]}

Lopez-Bigas, Nuria ^{[1
,2
]}

机构：

[1] Univ Pompeu Fabra, Hosp Mar Med Res Inst IMIM, Res Programme Biomed Informat GRIB, E-08003 Barcelona, Spain

[2] ICREA, E-08010 Barcelona, Spain

来源：

GENOME MEDICINE | 2012年 / 4卷

关键词：

HIGH-THROUGHPUT ANNOTATION; SOMATIC MUTATIONS; DRIVER MUTATIONS; HUMAN BREAST; GENES; LANDSCAPE; VARIANTS; PATHWAYS; PATTERNS; DOMINANT;

D O I：

10.1186/gm390

中图分类号：

Q3 [遗传学];

学科分类号：

071007 ; 090102 ;

摘要：

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.

引用

页数：13

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