Assessing the Performance of Methods for Copy Number Aberration Detection from Single-cell DNA Sequencing Data

Overview

Journal PLoS Comput Biol

Specialty Biology

Date 2020 Jul 14

PMID 32658894

Citations 21

Authors

Xian F Mallory

Mohammadamin Edrisi

Nicholas Navin

Luay Nakhleh

Affiliations

Soon will be listed here.

Abstract

Single-cell DNA sequencing technologies are enabling the study of mutations and their evolutionary trajectories in cancer. Somatic copy number aberrations (CNAs) have been implicated in the development and progression of various types of cancer. A wide array of methods for CNA detection has been either developed specifically for or adapted to single-cell DNA sequencing data. Understanding the strengths and limitations that are unique to each of these methods is very important for obtaining accurate copy number profiles from single-cell DNA sequencing data. We benchmarked three widely used methods-Ginkgo, HMMcopy, and CopyNumber-on simulated as well as real datasets. To facilitate this, we developed a novel simulator of single-cell genome evolution in the presence of CNAs. Furthermore, to assess performance on empirical data where the ground truth is unknown, we introduce a phylogeny-based measure for identifying potentially erroneous inferences. While single-cell DNA sequencing is very promising for elucidating and understanding CNAs, our findings show that even the best existing method does not exceed 80% accuracy. New methods that significantly improve upon the accuracy of these three methods are needed. Furthermore, with the large datasets being generated, the methods must be computationally efficient.

Citing Articles

SCGclust: Single Cell Graph clustering using graph autoencoders integrating SNVs and CNAs.

Potu T, Hu Y, Khan R, Dharani S, Ni J, Zhang L bioRxiv. 2025; .

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Single-cell copy number calling and event history reconstruction.

Kuipers J, Tuncel M, Ferreira P, Jahn K, Beerenwinkel N Bioinformatics. 2025; 41(3).

PMID: 39946094 PMC: 11897432. DOI: 10.1093/bioinformatics/btaf072.

DICE: fast and accurate distance-based reconstruction of single-cell copy number phylogenies.

Weiner S, Bansal M Life Sci Alliance. 2024; 8(3).

PMID: 39667913 PMC: 11638338. DOI: 10.26508/lsa.202402923.

Single-cell somatic copy number variants in brain using different amplification methods and reference genomes.

Kalef-Ezra E, Turan Z, Perez-Rodriguez D, Bomann I, Behera S, Morley C Commun Biol. 2024; 7(1):1288.

PMID: 39384904 PMC: 11464624. DOI: 10.1038/s42003-024-06940-w.

SCCNAInfer: a robust and accurate tool to infer the absolute copy number on scDNA-seq data.

Zhang L, Zhou X, Mallory X Bioinformatics. 2024; .

PMID: 39067018 PMC: 11286278. DOI: 10.1093/bioinformatics/btae454.

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