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对可靠的单细胞RNA-seq注释进行符合性推断

Marcos López-De-Castro^1,2,3, Alberto García-Galindo^1,2,3, José González-Gomariz^1,2,3

¹Institute of Data Science and Artificial Intelligence (DATAI), University of Navarra, Pamplona, Navarra 31009, Spain.

Bioinformatics (Oxford, England)

|September 19, 2025

概括

这项研究引入了可靠的单细胞RNA测序注释的合规预测,改善了不确定性量化和检测新型细胞类型. 该方法确保了没有分布假设的统计保证.

科学领域:

计算生物学计算生物学
基因组学就是基因组学.
生物信息学是一种生物信息学.

背景情况:

对细胞类型分配的监督学习模型往往缺乏严格的不确定性量化.
处理不确定的注释的现有方法依赖于任意假设,缺乏统计保障.

研究的目的:

为可靠的单细胞注释提出一种使用符合性预测的方法.
解决单细胞RNA测序 (scRNA-seq) 标注方面的挑战,包括检测分布外的细胞类型和量化标注不确定性.

主要方法:

利用合规预测框架对预测的统计保证.
为scRNA-seq数据开发一个异常探测器和一个不确定性意识注释器.
在各种组织,注释分类学和不符合性措施中评估方法.

主要成果:

异常检测器成功识别了以前看不见的细胞类型.
不确定性意识的注释器产生了精确校准的预测集,保持了覆盖概率.
符合性预测输出增强下游分析.

结论:

符合性预测为可靠的单单元格注释提供了一个强大的框架,具有统计保障.
拟议的方法有效地处理不确定性,并在scRNA-seq数据中检测新型细胞类型.
这种方法提高了自动化细胞类型识别的准确性和可靠性.

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相关概念视频

RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...