rujinwang/SCOPE: A normalization and copy number estimation method for single-cell DNA sequencing

Whole genome single-cell DNA sequencing (scDNA-seq) enables 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 propose SCOPE, a normalization and copy number estimation method for scDNA-seq data. The distinguishing features of SCOPE include: (i) utilization of cell-specific Gini coefficients for quality controls and for identification of normal/diploid cells, which are further used as negative control samples in a Poisson latent factor model for normalization; (ii) modeling of GC content bias using an expectation-maximization algorithm embedded in the Poisson generalized linear models, which accounts for the different copy number states along the genome; (iii) a cross-sample iterative segmentation procedure to identify breakpoints that are shared across cells from the same genetic background.

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Package details

AuthorRujin Wang, Danyu Lin, Yuchao Jiang
Bioconductor views Alignment CopyNumberVariation Coverage DNASeq DataImport Normalization QualityControl Sequencing SingleCell WholeGenome
MaintainerRujin Wang <>
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
rujinwang/SCOPE documentation built on Sept. 10, 2020, 9:19 p.m.