首页|Computational Methods for Single-cell DNA Methylome Analysis
Computational Methods for Single-cell DNA Methylome Analysis
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万方数据
维普
Dissecting intercellular epigenetic differences is key to understanding tissue heterogene-ity.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 chal-lenges 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,imputa-tion,dimensionality reduction,cell clustering,supervised cell annotation,cell lineage reconstruc-tion,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.
万方数据
维普
