CoMEt: A Statistical Approach to Identify Combinations of Mutually Exclusive Alterations in Cancer

  • Mark D. M. Leiserson
  • Hsin-Ta Wu
  • Fabio Vandin
  • Benjamin J. Raphael
Conference paper

DOI: 10.1007/978-3-319-16706-0_19

Volume 9029 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Leiserson M.D.M., Wu HT., Vandin F., Raphael B.J. (2015) CoMEt: A Statistical Approach to Identify Combinations of Mutually Exclusive Alterations in Cancer. In: Przytycka T. (eds) Research in Computational Molecular Biology. RECOMB 2015. Lecture Notes in Computer Science, vol 9029. Springer, Cham

Abstract

A major goal of large-scale cancer sequencing studies is to identify the genetic and epigenetic alterations that drive cancer development and to distinguish these events from random passenger mutations that have no consequence for cancer. Identifying driver mutations is a significant challenge due to the mutational heterogeneity of tumors: different combinations of somatic mutations drive different tumors, even those of the same cancer type.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Mark D. M. Leiserson
    • 1
  • Hsin-Ta Wu
    • 1
  • Fabio Vandin
    • 1
  • Benjamin J. Raphael
    • 1
  1. 1.Department of Computer Science and Center for Computational Molecular BiologyBrown UniversityProvidenceUSA