单细胞DNA甲基化分析的计算方法

IF 11.5 2区 生物学 Q1 GENETICS & HEREDITY Genomics, Proteomics & Bioinformatics Pub Date : 2023-02-01 DOI:10.1016/j.gpb.2022.05.007
Waleed Iqbal , Wanding Zhou
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引用次数: 2

摘要

分析细胞间表观遗传学差异是理解组织异质性的关键。单细胞DNA甲基组分析的最新进展为以最大分辨率解决这种异质性提供了机会。虽然这些进展使我们能够探索染色质生物学的前沿,更好地理解细胞谱系关系,但它们在数据处理和解释方面提出了新的挑战。这篇综述综述了为单细胞DNA甲基组数据分析开发的计算工具的现状。我们讨论了单细胞DNA甲基组数据分析的关键组成部分,包括数据预处理、质量控制、插补、降维、细胞聚类、监督细胞注释、细胞谱系重建、基因活性评分以及与转录组数据的整合。我们还强调了单细胞DNA甲基组数据分析的独特方面,并讨论了如何将其他单细胞组学数据分析中常见的技术应用于分析DNA甲基组。最后,我们讨论了当前的挑战和未来发展的机遇。
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Computational Methods for Single-cell DNA Methylome Analysis

Dissecting intercellular epigenetic differences is key to understanding tissue heterogeneity. Recent advances in single-cell DNA methylome profiling have presented opportunities to resolve this heterogeneity at the maximum resolution. While these advances enable us to explore frontiers of chromatin biology and better understand cell lineage relationships, they pose new challenges in data processing and interpretation. This review surveys the current state of computational tools developed for single-cell DNA methylome data analysis. We discuss critical components of single-cell DNA methylome data analysis, including data preprocessing, quality control, imputation, dimensionality reduction, cell clustering, supervised cell annotation, cell lineage reconstruction, gene activity scoring, and integration with transcriptome data. We also highlight unique aspects of single-cell DNA methylome data analysis and discuss how techniques common to other single-cell omics data analyses can be adapted to analyze DNA methylomes. Finally, we discuss existing challenges and opportunities for future development.

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来源期刊
Genomics, Proteomics & Bioinformatics
Genomics, Proteomics & Bioinformatics Biochemistry, Genetics and Molecular Biology-Biochemistry
CiteScore
14.30
自引率
4.20%
发文量
844
审稿时长
61 days
期刊介绍: Genomics, Proteomics and Bioinformatics (GPB) is the official journal of the Beijing Institute of Genomics, Chinese Academy of Sciences / China National Center for Bioinformation and Genetics Society of China. It aims to disseminate new developments in the field of omics and bioinformatics, publish high-quality discoveries quickly, and promote open access and online publication. GPB welcomes submissions in all areas of life science, biology, and biomedicine, with a focus on large data acquisition, analysis, and curation. Manuscripts covering omics and related bioinformatics topics are particularly encouraged. GPB is indexed/abstracted by PubMed/MEDLINE, PubMed Central, Scopus, BIOSIS Previews, Chemical Abstracts, CSCD, among others.
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