4.5 Article

An ensemble approach to accurately detect somatic mutations using SomaticSeq

期刊

GENOME BIOLOGY
卷 16, 期 -, 页码 -

出版社

BMC
DOI: 10.1186/s13059-015-0758-2

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资金

  1. National Institute of Health [R01-GM109836, R01-HG007834]
  2. Computational Cancer Biology Training Program, Cancer Prevention and Research Institute of Texas (CPRIT) [RP140113]
  3. National Cancer Institute [1R01CA183793, 1R01CA174206, P30 CA016672]
  4. Cancer Prevention Research Institute of Texas [RP130090]

向作者/读者索取更多资源

SomaticSeq is an accurate somatic mutation detection pipeline implementing a stochastic boosting algorithm to produce highly accurate somatic mutation calls for both single nucleotide variants and small insertions and deletions. The workflow currently incorporates five state-of-the-art somatic mutation callers, and extracts over 70 individual genomic and sequencing features for each candidate site. A training set is provided to an adaptively boosted decision tree learner to create a classifier for predicting mutation statuses. We validate our results with both synthetic and real data. We report that SomaticSeq is able to achieve better overall accuracy than any individual tool incorporated.

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