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Computational Methods for Analysis of Tumor Clonality and Evolutionary History

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Cancer Bioinformatics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1878))

Abstract

Cancer is an evolutionary process. Recent advances in sequencing technologies have allowed us to investigate intratumor heterogeneity at the single nucleotide level. Here, we describe computational methods that use sequencing data to identify genetically distinct tumor subclones and reconstruct tumor evolutionary histories.

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Author information

Authors and Affiliations

  1. Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK

    Gerald Goh & Nicholas McGranahan

  2. Genome Institute of Singapore, Singapore, Singapore

    Gerald Goh

  3. Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK

    Gareth A. Wilson

  4. Translational Cancer Therapeutics Laboratory, The Francis Crick Institute, London, UK

    Gareth A. Wilson

Authors
  1. Gerald Goh
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  2. Nicholas McGranahan
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  3. Gareth A. Wilson
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Corresponding author

Correspondence to Gerald Goh .

Editor information

Editors and Affiliations

  1. Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA

    Alexander Krasnitz

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Goh, G., McGranahan, N., Wilson, G.A. (2019). Computational Methods for Analysis of Tumor Clonality and Evolutionary History. In: Krasnitz, A. (eds) Cancer Bioinformatics. Methods in Molecular Biology, vol 1878. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8868-6_13

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  • DOI: https://doi.org/10.1007/978-1-4939-8868-6_13

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-8866-2

  • Online ISBN: 978-1-4939-8868-6

  • eBook Packages: Springer Protocols

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