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scNucMap:在单细胞分辨率下绘制核小体图谱。

scNucMap: mapping the nucleosome landscapes at single-cell resolution.

作者信息

Xiang Qianming, Lai Binbin

机构信息

Institute of Medical Technology, Peking University Health Science Center, Beijing 100191, China.

Biomedical Engineering Department, Institute of Advanced Clinical Medicine, Peking University, Beijing 100191, China.

出版信息

Bioinformatics. 2025 Jun 2;41(6). doi: 10.1093/bioinformatics/btaf324.

Abstract

MOTIVATION

Nucleosome depletion around cis-regulatory elements (CREs) is associated with CRE activity and implies the underlying gene regulatory network. Single-cell micrococcal nuclease sequencing (scMNase-seq) enables the simultaneous measurement of nucleosome positioning and chromatin accessibility at single-cell resolution, thereby capturing cellular heterogeneity in epigenetic regulation. However, there is currently no computational tool specifically designed to decode scMNase-seq data, impeding the generation of more precise and context-dependent insights into chromatin dynamics and gene regulation.

RESULTS

Here, we present scNucMap, a tool designed to leverage the unique characteristics of scMNase-seq data to map the landscapes of candidate nucleosome-free regions (NFRs). scNucMap demonstrated superior performance and robustness in cell clustering on scMNase-seq data compared to Signac and chromVAR across diverse sample compositions and data complexities, achieving higher overall accuracy and Kappa coefficients. Additionally, scNucMap identified significant TFs associated with nucleosome depletion at CREs at both single-cell and cell-cluster levels, thereby facilitating cell-type annotation and regulatory network inference. When applied to scATAC-seq data, scNucMap enriched standard analyses with complementary insights into nucleosome architecture, underscoring its cross‑modality versatility. Overall, scNucMap exhibits both high reliability and adaptability, making it an effective tool for analyzing scMNase-seq data and supporting multimodal studies, thereby illuminating the intricate relationship between regulatory networks and nucleosome positioning at single-cell resolution.

AVAILABILITY AND IMPLEMENTATION

scNucMap is available at https://github.com/qianming-bioinfo/scNucMap.

摘要

动机

顺式调控元件(CRE)周围的核小体缺失与CRE活性相关,并暗示潜在的基因调控网络。单细胞微球菌核酸酶测序(scMNase-seq)能够在单细胞分辨率下同时测量核小体定位和染色质可及性,从而捕捉表观遗传调控中的细胞异质性。然而,目前尚无专门设计用于解码scMNase-seq数据的计算工具,这阻碍了对染色质动力学和基因调控产生更精确且依赖上下文的见解。

结果

在此,我们展示了scNucMap,这是一种旨在利用scMNase-seq数据的独特特征来绘制候选无核小体区域(NFR)图谱的工具。与Signac和chromVAR相比,scNucMap在不同样本组成和数据复杂性的scMNase-seq数据细胞聚类中表现出卓越的性能和稳健性,实现了更高的总体准确率和卡帕系数。此外,scNucMap在单细胞和细胞簇水平上均识别出与CRE处核小体缺失相关的重要转录因子(TF),从而有助于细胞类型注释和调控网络推断。当应用于scATAC-seq数据时,scNucMap通过对核小体结构的补充见解丰富了标准分析,突出了其跨模态通用性。总体而言,scNucMap既具有高可靠性又具有适应性,使其成为分析scMNase-seq数据和支持多模态研究的有效工具,从而在单细胞分辨率下阐明调控网络与核小体定位之间的复杂关系。

可用性和实现方式

scNucMap可在https://github.com/qianming-bioinfo/scNucMap获取。

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