Copy number aberrations (CNAs), which are pathogenic copy number variations (CNVs), play an important role in the initiation and progression of cancer. Single-cell DNA-sequencing (scDNAseq) technologies produce data that is ideal for inferring CNAs. In this review, we review eight methods that have been developed for detecting CNAs in scDNAseq data, and categorize them according to the steps of a seven-step pipeline that they employ. Furthermore, we review models and methods for evolutionary analyses of CNAs from scDNAseq data and highlight advances and future research directions for computational methods for CNA detection from scDNAseq data.

中文翻译：

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从单细胞 DNA 测序数据中检测拷贝数畸变的方法

拷贝数畸变 (CNA) 是致病性拷贝数变异 (CNV)，在癌症的发生和发展中起重要作用。单细胞 DNA 测序 (scDNAseq) 技术产生的数据非常适合推断 CNA。在这篇综述中，我们回顾了为检测 scDNAseq 数据中的 CNA 而开发的八种方法，并根据它们采用的七步管道的步骤对它们进行分类。此外，我们回顾了从 scDNAseq 数据对 CNA 进行进化分析的模型和方法，并强调了从 scDNAseq 数据检测 CNA 的计算方法的进展和未来研究方向。