Introduction

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.

Publications

  1. An ensemble approach to accurately detect somatic mutations using SomaticSeq.
    Cite this
    Fang LT, Afshar PT, Chhibber A, Mohiyuddin M, Fan Y, Mu JC, Gibeling G, Barr S, Asadi NB, Gerstein MB, Koboldt DC, Wang W, Wong WH, Lam HY, 2015-09-01 - Genome biology

Credits

  1. Li Tai Fang
    Developer

    Bina Technologies, Roche Sequencing, United States of America

  2. Pegah Tootoonchi Afshar
    Developer

    Department of Electrical Engineering, Stanford University, United States of America

  3. Aparna Chhibber
    Developer

    Bina Technologies, Roche Sequencing, United States of America

  4. Marghoob Mohiyuddin
    Developer

    Bina Technologies, Roche Sequencing, United States of America

  5. Yu Fan
    Developer

    Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, United States of America

  6. John C Mu
    Developer

    Bina Technologies, Roche Sequencing, United States of America

  7. Greg Gibeling
    Developer

    Bina Technologies, Roche Sequencing, United States of America

  8. Sharon Barr
    Developer

    Bina Technologies, Roche Sequencing, United States of America

  9. Narges Bani Asadi
    Developer

    Bina Technologies, Roche Sequencing, United States of America

  10. Mark B Gerstein
    Developer

    Program in Computational Biology and Bioinformatics, Yale University, United States of America

  11. Daniel C Koboldt
    Developer

    The Genome Institute, Washington University in St Louis

  12. Wenyi Wang
    Developer

    Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, United States of America

  13. Wing H Wong
    Developer

    Department of Health Research and Policy, Stanford University, United States of America

  14. Hugo Y K Lam
    Investigator

    Bina Technologies, Roche Sequencing, United States of America

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Summary
AccessionBT006951
Tool TypeApplication
Category
PlatformsLinux/Unix
Technologies
User InterfaceTerminal Command Line
Download Count0
Country/RegionUnited States of America
Submitted ByHugo Y K Lam