单细胞RNA测序数据分析方法研究进展

Research Progress of Approaches in Single Cell RNA Sequencing Data Analysis

单细胞RNA测序(Single cell RNA sequencing,scRNA-Seq)已经广泛应用于细胞分化、肿瘤微环境及多种疾病病因学研究。目前,由于scRNA-Seq具有低捕获率、高噪声、高变异性等特点,通过优化数据分析方法提高测序结果准确性已经成为测序领域的研究热点。对近年来数据分析过程中利用的数学方法进行了总结,讨论了数据分析的优势及存在的问题,以期为新算法的开发和应用提供参考,逐步提高测序结果的可靠性。

Single cell RNA sequencing(scRNA-Seq)has been widely used in cell differentiation,tumor microenvironment and etiology of various diseases.Currently improving the accuracy of sequencing results by optimizing data analysis methods has become a research hotspot in the field of sequencing due to the characteristics of low capture rate,high noise,and high variability of scRNA-Seq.Here an overview of the mathematical methods used in the process of data analysis in recent years is summarized,and the advantages and issues in data analysis are discussed,aiming to provide a reference for the development and application of new algorithms,and to gradually improve the reliability of sequencing results.