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

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

International Conference on Research in Computational Molecular Biology

RECOMB 2015: Research in Computational Molecular Biology pp 202-204

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

Authors
Authors and affiliations

Mark D. M. Leiserson
Hsin-Ta Wu
Fabio Vandin
Benjamin J. RaphaelEmail author

Conference paper

First Online:: 26 March 2015

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

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9029)

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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Authors and Affiliations

Mark D. M. Leiserson
- 1
Hsin-Ta Wu
- 1
Fabio Vandin
- 1
Benjamin J. Raphael
- 1
Email author

1.Department of Computer Science and Center for Computational Molecular BiologyBrown UniversityProvidenceUSA

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

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