{"title":"单细胞 DNA 甲基化测序数据的处理管道和分析方法。","authors":"Yan-Ni Wang, Jia Li","doi":"10.16288/j.yczz.24-154","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":35536,"journal":{"name":"遗传","volume":"46 10","pages":"807-819"},"PeriodicalIF":0.0000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Processing pipelines and analytical methods for single-cell DNA methylation sequencing data.\",\"authors\":\"Yan-Ni Wang, Jia Li\",\"doi\":\"10.16288/j.yczz.24-154\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":35536,\"journal\":{\"name\":\"遗传\",\"volume\":\"46 10\",\"pages\":\"807-819\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"遗传\",\"FirstCategoryId\":\"1091\",\"ListUrlMain\":\"https://doi.org/10.16288/j.yczz.24-154\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"遗传","FirstCategoryId":"1091","ListUrlMain":"https://doi.org/10.16288/j.yczz.24-154","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
摘要
近年来,单细胞 DNA 甲基化测序技术突飞猛进,在揭示细胞异质性和表观遗传调控机制方面发挥了至关重要的作用。随着测序技术的进步,单细胞甲基化数据的质量和数量也在不断增加,因此标准化的预处理工作流程和适当的分析方法对于确保数据的可比性和结果的可靠性至关重要。然而,指导研究人员挖掘现有数据的综合数据分析管道尚未建立。本综述系统总结了单细胞甲基化数据的预处理步骤和分析方法,介绍了相关算法和工具,并探讨了单细胞甲基化技术在神经科学、造血分化和癌症研究中的应用前景。旨在为研究人员提供数据分析指导,促进单细胞甲基化测序技术的发展和应用。
Processing pipelines and analytical methods for single-cell DNA methylation sequencing data.
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.