Research Progress of Approaches in Single Cell RNA Sequencing Data Analysis

doi:10.13560/j.cnki.biotech.bull.1985.2020-0469

Abstract

Abstract:

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.

Key words: single cell sequencing, data analysis methods, quality control, differential expression, algorithm

ZHANG Miao, SUN Xiang-rui, XU Chun-ming. Research Progress of Approaches in Single Cell RNA Sequencing Data Analysis[J]. Biotechnology Bulletin, 2021, 37(1): 52-59.

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