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scQCEA:单细胞RNA测序数据的注释和质量控制报告的框架

Isar Nassiri¹, Benjamin Fairfax^2,3, Angela Lee⁴

¹Oxford Genomics Centre, Nuffield Department of Medicine, Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK. isar@well.ox.ac.uk.

|July 6, 2023

概括

我们介绍了scQCEA,这是用于单细胞RNA测序 (scRNA-seq) 质量控制的R包. 它提供基于表达的质量评估和自动化的细胞类型注释,改善数据分析和降低噪音.

科学领域:

基因组学就是基因组学.
生物信息学是一种生物信息学.
计算生物学计算生物学

背景情况:

单细胞RNA测序 (scRNA-seq) 数据的系统质量控制对于下游分析至关重要,如图书馆重新聚合.
对于scRNA-seq质量控制 (QC) 指标的现有可视化工具缺乏基于表达的分析,以区分真正的生物变异与背景噪声.

研究的目的:

开发一个R包,scQCEA (单细胞RNA测序质量控制和丰富分析),用于全面的QC和分析scRNA-seq数据.
通过自动化细胞类型注释,使质量评分能够进行视觉评估,并提供基于表达式的QC.

主要方法:

scQCEA从各种单细胞平台 (如10X) 导入数据,并为多omics数据生成交互式QC报告.
使用差异性基因表达模式进行自动化的细胞类型注释,包含95种人类和小鼠细胞类型的2348个标记基因的存储库.
应用scQCEA来评估样本集的质量得分,并确定细胞类型丰富分析的最佳测序要求.

主要成果:

证明了scQCEA在视觉评估scRNA-seq样本集的质量评分中的实用性,包括基因表达和V(D) J T细胞复制物.
确定了用于细胞类型丰富分析的最佳测序要求,使用来自342个人类和小鼠基因表达特征的QC指标.
该包方便了对生物和技术措施中的偏差和异常值的检查.

结论:

scQCEA是一个开源的R包,旨在提高单细胞RNA测序数据的质量评估.
它有助于在下游分析之前客观地选择最佳集群数量.
该工具可以通过在线获得的完整文档和示例来访问.

关键词:

细胞类型的注释.基因组学就是基因组学.一个单细胞RNA测序.文字转录学 (Transcriptomics) 是一个学科.

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