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Methods for copy number aberration detection from single-cell DNA-sequencing data

机译:从单细胞DNA测序数据复制数量像差检测方法

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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.
机译:拷贝数像差(CNA),其是致病拷贝数变异(CNV),在癌症的开始和进展中起重要作用。单细胞DNA测序(SCDNASEQ)技术产生理想的地推断CNA的数据。在此述评中,我们回顾了八种方法,该方法已经开发用于检测SCDNASEQ数据中的CNA,并根据他们所采用的七步管道的步骤对其进行分类。此外,我们审查了来自SCDNAseq数据的CNA的进化分析的模型和方法,并突出了来自SCDNAseq数据的CNA检测的计算方法的进步和未来研究方向。

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