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NGS Analysis of Somatic Mutations in Cancer Genomes

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Big Data Analytics in Genomics

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Abstract

The emergence of next-generation sequencing (NGS) technologies has facilitated the accumulation of large genomic datasets for most types of cancer. The analysis of these data has confirmed the early predictions of extensive sequence and structural diversity of cancer genomes, fueling the development of new computational approaches to decipher inter- and intratumoral somatic variation within and among cancer patients. Overall, these techniques have led to a better understanding of the disease as well as to relevant improvements in the diagnosis and therapy of cancer. In this chapter, we review current approaches for the analysis of somatic mutations in cancer genomes using NGS.

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Acknowledgments

This work was supported by the European Research Council (ERC-617457- PHYLOCANCER to D.P.). T.P. is supported by a PhD fellowship from the Galician Government (ED481A-2015/083).

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Authors and Affiliations

  1. Department of Biochemistry, Genetics and Immunology, University of Vigo, Vigo, Spain

    T. Prieto, J. M. Alves & D. Posada

  2. Galicia Sur Health Research Institute (IISGS), Vigo, Spain

    T. Prieto, J. M. Alves & D. Posada

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  1. T. Prieto
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  2. J. M. Alves
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Correspondence to D. Posada .

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  1. Department of Computer Science, City University of Hong Kong, Kowloon Tong, Hong Kong

    Ka-Chun Wong

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Prieto, T., Alves, J.M., Posada, D. (2016). NGS Analysis of Somatic Mutations in Cancer Genomes. In: Wong, KC. (eds) Big Data Analytics in Genomics. Springer, Cham. https://doi.org/10.1007/978-3-319-41279-5_11

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  • DOI: https://doi.org/10.1007/978-3-319-41279-5_11

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