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Copy Number Variation Detection by Single-Cell DNA Sequencing with SCOPE

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Variant Calling

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2493))

Abstract

Whole-genome single-cell DNA sequencing (scDNA-seq) enables the characterization of copy number profiles at the cellular level. This circumvents the averaging effects associated with bulk-tissue sequencing and has increased resolution yet decreased ambiguity in deconvolving cancer subclones and elucidating cancer evolutionary history. ScDNA-seq data is, however, sparse, noisy, and highly variable even within a homogeneous cell population, due to the biases and artifacts that are introduced during the library preparation and sequencing procedure. Here, we describe SCOPE, a normalization and copy number estimation method for scDNA-seq data. We give an overview of the methodology and illustrate SCOPE with step-by-step demonstrations.

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Author information

Authors and Affiliations

  1. Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA

    Rujin Wang & Yuchao Jiang

  2. Department of Genetics, School of Medicine, University of North Carolina, Chapel Hill, NC, USA

    Yuchao Jiang

  3. Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA

    Yuchao Jiang

Authors
  1. Rujin Wang
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  2. Yuchao Jiang
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Corresponding author

Correspondence to Yuchao Jiang .

Editor information

Editors and Affiliations

  1. Department of BioMedical Research, University of Bern, Bern, Switzerland

    Charlotte Ng

  2. Department of Biomedicine, University of Basel, Basel, Switzerland

    Salvatore Piscuoglio

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© 2022 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature

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Wang, R., Jiang, Y. (2022). Copy Number Variation Detection by Single-Cell DNA Sequencing with SCOPE. In: Ng, C., Piscuoglio, S. (eds) Variant Calling. Methods in Molecular Biology, vol 2493. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2293-3_18

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  • DOI: https://doi.org/10.1007/978-1-0716-2293-3_18

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-2292-6

  • Online ISBN: 978-1-0716-2293-3

  • eBook Packages: Springer Protocols

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