生物信息学2025，Vol.23Issue(1)：1-27,27.DOI:10.12113/202307007
单细胞转录组数据分析中的数学
Mathematics in single-cell RNA transcriptome analysis
摘要
Abstract
In recent years,high-throughput single-cell sequencing technology has brought profound new findings to biological research.The rapid development of single-cell RNA sequencing technology enables researchers to study the transcriptome of individual cells.How we can obtain helpful information about cells and genomes from high-dimensional single-cell RNA sequencing data is an important issue in analyzing single-cell RNA sequencing data.Many researchers have conducted studies on single-cell RNA sequencing data analysis and developed many computational methods and corresponding software packages.This review summarizes the classical computational methods and mathematical basis involved in single-cell RNA sequencing data analysis,including data preprocessing,dimensionality reduction,clustering analysis,pseudo-time analysis,copy number variation analysis,and non-negative matrix factorization.We mainly focus on the mathematical principles behind the corresponding data processing methods,reveal how we can apply mathematical tools to obtain information from single-cell RNA data,and provide guidance for mathematicians to analyze single-cell data and to further develop and improve the existing methods.关键词
单细胞转录组测序数据/数据预处理/聚类分析/数学基础Key words
Single-cell RNA-seq data/Data preprocessing/Clustering analysis/Mathematical basic分类
生物学引用本文复制引用
罗琴琴,雷锦志..单细胞转录组数据分析中的数学[J].生物信息学,2025,23(1):1-27,27.基金项目
国家自然科学基金项目(No.11831015). （No.11831015）
