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Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples

Nature Biotechnology, ISSN: 1087-0156, Vol: 31, Issue: 3, Page: 213-219
2013
  • 3,547
    Citations
  • 0
    Usage
  • 2,511
    Captures
  • 19
    Mentions
  • 23
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    3,547
    • Citation Indexes
      3,511
    • Patent Family Citations
      29
      • Patent Families
        29
    • Policy Citations
      6
      • Policy Citation
        6
    • Clinical Citations
      1
      • PubMed Guidelines
        1
  • Captures
    2,511
  • Mentions
    19
    • News Mentions
      16
      • News
        16
    • References
      3
      • Wikipedia
        3
  • Social Media
    23
    • Shares, Likes & Comments
      23
      • Facebook
        23

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Article Description

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. Copyright © 2013 Nature America, Inc.

Bibliographic Details

Cibulskis, Kristian; Lawrence, Michael S; Carter, Scott L; Sivachenko, Andrey; Jaffe, David; Sougnez, Carrie; Gabriel, Stacey; Meyerson, Matthew; Lander, Eric S; Getz, Gad

Springer Science and Business Media LLC

Biochemistry, Genetics and Molecular Biology; Chemical Engineering; Immunology and Microbiology; Engineering

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