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scSNViz:细胞特异性表达SNV的可视化和分析

Siera Martinez¹, Tushar Sharma¹, Luke Johnson¹

¹McCormick Genomics and Proteomics Center, Department of Biochemistry and Molecular Medicine, School of Medicine and Health Sciences, The George Washington University, Washington, DC 20037, United States.

Bioinformatics (Oxford, England)

|January 14, 2026

概括

scSNViz是一个新的R包,可视化和量化单细胞RNA测序数据中表达的遗传变异. 这个工具有助于理解细胞异质性和等位基调的调节.

科学领域:

基因组学就是基因组学.
计算生物学计算生物学
生物信息学是一种生物信息学.

背景情况:

在单细胞水平上描述表达的遗传变异对于理解细胞异质性,基调节和突变动态至关重要.
现有的工具缺乏全面的可视化和定量分析能力,用于在单个细胞中表达的变异.

研究的目的:

介绍scSNViz,这是一个R包,旨在从单细胞RNA测序 (scRNA-seq) 数据中探索,量化和可视化表达的单核酸变体 (SNV).
为了能够详细研究变异表达模式和单细胞水平的等位基动力学.

主要方法:

开发了scSNViz作为一个R包,利用细胞条形编码的scRNA-seq数据.
实施了用于估计变异性等位基因分数和聚类SNV表达特征的功能.
启用了SNV和SNV组的2D和3D可视化.
确保与已建立的单细胞分析框架 (如Seurat,Slingshot,scType和CopyKat) 的互操作性.

主要成果:

scSNViz提供了用于量化变异性等位基因分数和集群SNV表达特征的工具.
该套件提供单个或组合的SNVs的2D和3D可视化.
便于分析细胞,集群或谱系特定的变异表达和等位基动力学 (印记,随机等位基失活化,转录突破).
通过与其他单细胞分析工具互操作,使综合性多原子分析成为可能.

结论:

scSNViz是一个多功能R包,增强了scRNA-seq数据中表达的遗传变异的分析.
它支持全面的可视化,量化和研究等位基动力学,促进对细胞异质性和调节的更深入的洞察.
该软件包是免费提供的,包含各种生物信息学专业知识的用户的文档和示例.

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