|SCOPE: A Normalization and Copy-Number Estimation Method for Single-Cell DNA Sequencing.
|Year of Publication
|Wang, Rujin, Dan-Yu Lin, and Yuchao Jiang
|2020 May 20
|Algorithms, Base Sequence, Computer Simulation, DNA Copy Number Variations, Genome, Human, Genomics, High-Throughput Nucleotide Sequencing, Humans, Neoplasms, Polymorphism, Single Nucleotide, Research Design, Sequence Analysis, DNA, Single-Cell Analysis, Whole Genome Sequencing
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.
|SCOPE: A normalization and copy-number estimation method for single-cell DNA sequencing.
|PubMed Central ID
|R35 GM118102 / GM / NIGMS NIH HHS / United States
R01 HG009974 / HG / NHGRI NIH HHS / United States
P30 CA016086 / CA / NCI NIH HHS / United States
P01 CA142538 / CA / NCI NIH HHS / United States
R01 HL149683 / HL / NHLBI NIH HHS / United States