Single-cell DNA methylation sequencing technology has seen rapid advancements in recent years,playing a crucial role in uncovering cellular heterogeneity and the mechanisms of epigenetic regulation.As sequencing technologies have progressed,the quality and quantity of single-cell methylation data have also increased,making standardized preprocessing workflows and appropriate analysis methods essential for ensuring data comparability and result reliability.However,a comprehensive data analysis pipeline to guide researchers in mining existing data has yet to be established.This review systematically summarizes the preprocessing steps and analysis methods for single-cell methylation data,introduces relevant algorithms and tools,and explores the application prospects of single-cell methylation technology in neuroscience,hematopoietic differentiation,and cancer research.The aim is to provide guidance for researchers in data analysis and to promote the development and application of single-cell methylation sequencing technology.
维普
万方数据