SCOPE: A Normalization and Copy-Number Estimation Method for Single-Cell DNA Sequencing

Cell Syst. 2020 May 20;10(5):445-452.e6. doi: 10.1016/j.cels.2020.03.005.


Whole-genome single-cell DNA sequencing (scDNA-seq) enables characterization of copy-number profiles at the cellular level. We propose SCOPE, a normalization and copy-number estimation method for the noisy scDNA-seq data. SCOPE's main features include the following: (1) a Poisson latent factor model for normalization, which borrows information across cells and regions to estimate bias, using in silico identified negative control cells; (2) an expectation-maximization algorithm embedded in the normalization step, which accounts for the aberrant copy-number changes and allows direct ploidy estimation without the need for post hoc adjustment; and (3) a cross-sample segmentation procedure to identify breakpoints that are shared across cells with the same genetic background. We evaluate SCOPE on a diverse set of scDNA-seq data in cancer genomics and show that SCOPE offers accurate copy-number estimates and successfully reconstructs subclonal structure. A record of this paper's transparent peer review process is included in the Supplemental Information.

Keywords: cancer genomics; copy number aberration; copy number variation; normalization; single-cell DNA sequencing; tumor heterogeneity.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Base Sequence / genetics
  • Computer Simulation
  • DNA Copy Number Variations / genetics*
  • Genome, Human / genetics
  • Genomics / methods
  • High-Throughput Nucleotide Sequencing / methods
  • Humans
  • Neoplasms / genetics
  • Polymorphism, Single Nucleotide / genetics
  • Research Design
  • Sequence Analysis, DNA / methods*
  • Single-Cell Analysis / methods*
  • Whole Genome Sequencing / methods