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International Workshop on Algorithms in Bioinformatics

WABI 2014: Algorithms in Bioinformatics pp 354–367Cite as

Reconstructing Mutational History in Multiply Sampled Tumors Using Perfect Phylogeny Mixtures

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Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 8701))

Abstract

High-throughput sequencing of cancer genomes have motivated the problem of inferring the ancestral history of somatic mutations that accumulate in cells during cancer progression. While the somatic mutation process in cancer cells meets the requirements of the classic Perfect Phylogeny problem, nearly all cancer sequencing studies do not sequence single cancerous cells, but rather thousands-millions of cells in a tumor sample. In this paper, we formulate the Perfect Phylogeny Mixture problem of inferring a perfect phylogeny given somatic mutation data from multiple tumor samples, each of which is a superposition of cells, or “species.” We prove that the Perfect Phylogeny Mixture problem is NP-hard, using a reduction from the graph coloring problem. Finally, we derive an algorithm to solve the problem.

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Authors and Affiliations

  1. Department of Computer Science and Center for Computational Molecular Biology, Brown University, Providence, RI, 02906, USA

    Iman Hajirasouliha & Benjamin J. Raphael

Authors
  1. Iman Hajirasouliha
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  2. Benjamin J. Raphael
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Editors and Affiliations

  1. David R. Cheriton School of Computer Science, University of Waterloo, ON, Canada

    Dan Brown

  2. Institute of Microbiology and Genetics, Department of Bioinformatics, University of Göttingen, Germany, Goldschmidtstr. 1, 37077, Göttingen, Germany

    Burkhard Morgenstern

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Hajirasouliha, I., Raphael, B.J. (2014). Reconstructing Mutational History in Multiply Sampled Tumors Using Perfect Phylogeny Mixtures. In: Brown, D., Morgenstern, B. (eds) Algorithms in Bioinformatics. WABI 2014. Lecture Notes in Computer Science(), vol 8701. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44753-6_27

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  • DOI: https://doi.org/10.1007/978-3-662-44753-6_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-44752-9

  • Online ISBN: 978-3-662-44753-6

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