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scNucMap:在单细胞分辨率下绘制核细胞的地图

Qianming Xiang^1,2, Binbin Lai^1,2,3,4

¹Institute of Medical Technology, Peking University Health Science Center, Beijing 100191, China.

Bioinformatics (Oxford, England)

|May 27, 2025

概括

一个名为scNucMap的新工具解码了单细胞微菌核酶测序 (scMNase-seq) 数据,以绘制无核素组区域的地图. 它准确地聚类细胞并识别转录因子,进步我们对单细胞分辨率的基因调节的理解.

科学领域:

表观遗传学在表观遗传学中,表观遗传学是指表观遗传学.
基因组学就是基因组学.
计算生物学计算生物学

背景情况:

在cis调节元件 (CREs) 附近的核细胞体枯竭与基因调节活性相关.
单细胞微球菌核酶测序 (scMNase-seq) 在单细胞分辨率下捕获染色质的可访问性和核细胞的定位.
缺乏专门的计算工具阻碍了scMNase-seq数据的分析,以获得精确的染色质动态和基因调节见解.

研究的目的:

介绍 scNucMap,这是一个用于分析 scMNase-seq 数据的计算工具.
为了使无核体区域 (NFRs) 的映射,并促进基因调节网络推断.

主要方法:

开发scNucMap,这是一个针对scMNase-seq数据量身定制的新型计算工具.
与现有工具 (Signac,chromVAR) 进行基准测试,以提高细胞聚类的准确性.
应用scNucMap来识别与CREs相关的转录因子 (TF),并分析scATAC-seq数据.

主要成果:

与Signac和chromVAR相比,scNucMap在细胞聚类方面表现出更好的表现,显示出更高的精度和卡帕系数.
该工具成功地确定了与单细胞和集群水平的CREs核细胞枯竭相关的显著TF.
当应用到scATAC-seq数据时,scNucMap提供了补充的见解,突出了其跨模式实用性.

结论:

scNucMap是一个可靠和适应性的工具,用于分析scMNase-seq数据,改善细胞聚类和监管网络推断.
该工具通过将核细胞定位见解与其他表观遗传数据相结合来增强多式研究.
scNucMap有助于更深入地了解基因调节网络与核细胞位定之间的关系,以单细胞分辨率.

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