Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples
Author(s)
Cibulskis, Kristian; Sivachenko, Andrey; Jaffe, David B.; Sougnez, Carrie; Gabriel, Stacey B.; Meyerson, Matthew L.; Getz, Gad; Lawrence, Michael S.; Carter, Scott L.; Lander, Eric Steven; ... Show more Show less
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Detection of somatic point substitutions is a key step in characterizing the cancer genome. However, existing methods typically miss low-allelic-fraction mutations that occur in only a subset of the sequenced cells owing to either tumor heterogeneity or contamination by normal cells. Here we present MuTect, a method that applies a Bayesian classifier to detect somatic mutations with very low allele fractions, requiring only a few supporting reads, followed by carefully tuned filters that ensure high specificity. We also describe benchmarking approaches that use real, rather than simulated, sequencing data to evaluate the sensitivity and specificity as a function of sequencing depth, base quality and allelic fraction. Compared with other methods, MuTect has higher sensitivity with similar specificity, especially for mutations with allelic fractions as low as 0.1 and below, making MuTect particularly useful for studying cancer subclones and their evolution in standard exome and genome sequencing data.
Date issued
2013-02Department
Massachusetts Institute of Technology. Department of BiologyJournal
Nature Biotechnology
Publisher
Nature Publishing Group
Citation
Cibulskis, Kristian, Michael S Lawrence, Scott L Carter, Andrey Sivachenko, David Jaffe, Carrie Sougnez, Stacey Gabriel, Matthew Meyerson, Eric S Lander, and Gad Getz. “Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples.” Nature Biotechnology 31, no. 3 (February 10, 2013): 213-219.
Version: Author's final manuscript
ISSN
1087-0156
1546-1696