Sequenza: allele-specific copy number and mutation profiles from tumor sequencing data

Francesco Favero, Tejal Joshi, Andrea Marion Marquard, Nicolai Juul Birkbak, Marcin Krzystanek, Qiyuan Li, Zoltan Imre Szallasi, Aron Charles Eklund

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    Abstract

    Background: Exome or whole genome deep sequencing of tumor DNA along with paired normal DNA can potentially provide a detailed picture of the somatic mutations that characterize the tumor. However, analysis of such sequence data can be complicated by the presence of normal cells in the tumor specimen, by intratumor heterogeneity, and by the sheer size of the raw data. In particular, determination of copy number variations from exome sequencing data alone has proven difficult; thus SNP arrays have often been used for this task. Recently, algorithms to estimate absolute, but not allele-specific, copy number profiles from tumor sequencing data have been described.
    Materials and Methods: We developed Sequenza, a software package that uses paired tumornormal DNA sequencing data to estimate tumor cellularity and ploidy, and to calculate allele-specific copy number profiles and mutation profiles. We applied Sequenza, as well as two previously published algorithms, to exome sequence data from 30 tumors from The Cancer Genome Atlas. We assessed the performance of these algorithms by comparing their results to those generated using matched SNP arrays and processed by the ASCAT algorithm.
    Results: Comparison between Sequenza/exome and SNP/ASCAT revealed strong correlation in cellularity (Pearson’s r = 0.90) and ploidy estimates (r = 0.42, or r = 0.94 after manual inspecting alternative solutions). This performance was noticeably superior to previously published algorithms. In addition, in artificial data simulating normal-tumor admixtures, Sequenza detected the correct ploidy in samples with tumor content as low as 30%.
    Conclusions: The agreement between Sequenza and SNP array-based copy number profiles suggests that exome sequencing alone is sufficient not only for identifying small scale mutations but also for estimating cellularity and inferring DNA copy number aberrations.
    Original languageEnglish
    JournalAnnals of Oncology
    Volume26
    Issue number1
    Number of pages16
    ISSN0923-7534
    Publication statusPublished - 2015

    Bibliographical note

    This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

    Keywords

    • Cancer genomics
    • Copy number alterations
    • Mutations
    • Next-generation sequencing
    • Software

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