单细胞RNA测序数据分析方法研究进展

Advances on Approaches Used in Single-Cell RNA Sequencing Data Analysis

【目的】综述当前单细胞RNA测序数据分析的关键流程和环节,介绍完成不同分析任务所需的代表性方法及流行的工具。【方法】通过文献调研,总结了当前单细胞RNA测序数据分析的流程和代表性工具。【结果】许多针对单细胞RNA测序数据的分析流程和工具被陆续开发出来,用于从海量数据中发掘生物学知识,进而揭示复杂疾病或表型背后潜在的分子机制。【结论】单细胞RNA测序在生命科学研究中扮演了极为重要的角色,良好的数据分析策略是决定能否有效揭示单细胞表达谱数据背后蕴含生物学信息的关键环节。目前单细胞RNA测序数据分析步骤和工具方法繁多,研究者应根据实际场景选择合适准确的分析方法与工具。

[Purposes]To review the current key processes and aspects of single-cell RNA sequencing data analysis,and to introduce representative methods and popular tools required to accomplish different analysis tasks.[Methods]The current analysis processes and representative tools for single-cell RNA sequencing data are summarized through a survey of the literature and condensed summaries.[Findings]Many analytical procedures and tools for single-cell RNA sequencing data have been developed to uncover biological knowledge from the vast amount of data,in order to reveal complex diseases or phenotypes.[Conclusions]Single-cell RNA sequencing plays an extremely important role in life science field,and a good data analysis strategy is a key component to effectively reveal the biological information behind single-cell expression profiling data.There is a wide range of steps and tools available for single-cell RNA sequencing data analysis,and researchers should choose the appropriate and accurate analysis methods and tools,according to the practice scenarios.