vmrseq: probabilistic modeling of single-cell methylation heterogeneity

被引:0
|
作者
Shen, Ning [1 ,2 ]
Korthauer, Keegan [1 ,2 ]
机构
[1] Univ British Columbia, Dept Stat, Vancouver, BC, Canada
[2] BC Childrens Hosp Res Inst, Ctr Mol Med & Therapeut, Vancouver, BC, Canada
来源
GENOME BIOLOGY | 2024年 / 25卷 / 01期
基金
加拿大自然科学与工程研究理事会;
关键词
DNA methylation; Single-cell bisulfite sequencing; Epigenetic heterogeneity; Hidden Markov model; BODY-SPECIFIC METHYLATION; DNA METHYLATION; SCALE;
D O I
10.1186/s13059-024-03457-7
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Single-cell DNA methylation measurements reveal genome-scale inter-cellular epigenetic heterogeneity, but extreme sparsity and noise challenges rigorous analysis. Previous methods to detect variably methylated regions (VMRs) have relied on predefined regions or sliding windows and report regions insensitive to heterogeneity level present in input. We present vmrseq, a statistical method that overcomes these challenges to detect VMRs with increased accuracy in synthetic benchmarks and improved feature selection in case studies. vmrseq also highlights context-dependent correlations between methylation and gene expression, supporting previous findings and facilitating novel hypotheses on epigenetic regulation. vmrseq is available at https://github.com/nshen7/vmrseq.
引用
收藏
页数:27
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