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An ensemble approach to accurately detect somatic mutations using SomaticSeq
Authors:Li Tai Fang  Pegah Tootoonchi Afshar  Aparna Chhibber  Marghoob Mohiyuddin  Yu Fan  John C Mu  Greg Gibeling  Sharon Barr  Narges Bani Asadi  Mark B Gerstein  Daniel C Koboldt  Wenyi Wang  Wing H Wong  Hugo YK Lam
Abstract: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.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-015-0758-2) contains supplementary material, which is available to authorized users.
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