scCTS: identifying the cell type-specific marker genes from population-level single-cell RNA-seq

IF 10.1 1区生物学 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY

Genome Biology Pub Date : 2024-10-14 DOI:10.1186/s13059-024-03410-8

Luxiao Chen, Zhenxing Guo, Tao Deng, Hao Wu

引用次数: 0

Abstract

Single-cell RNA-sequencing (scRNA-seq) provides gene expression profiles of individual cells from complex samples, facilitating the detection of cell type-specific marker genes. In scRNA-seq experiments with multiple donors, the population level variation brings an extra layer of complexity in cell type-specific gene detection, for example, they may not appear in all donors. Motivated by this observation, we develop a statistical model named scCTS to identify cell type-specific genes from population-level scRNA-seq data. Extensive data analyses demonstrate that the proposed method identifies more biologically meaningful cell type-specific genes compared to traditional methods.

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scCTS：从群体级单细胞 RNA-seq 中识别细胞类型特异性标记基因

单细胞 RNA 测序（scRNA-seq）可提供复杂样本中单个细胞的基因表达谱，便于检测细胞类型特异性标记基因。在有多个供体的 scRNA-seq 实验中，群体水平的变化给细胞类型特异性基因的检测带来了额外的复杂性，例如，它们可能不会出现在所有供体中。受此启发，我们开发了一种名为 scCTS 的统计模型，用于从群体水平的 scRNA-seq 数据中识别细胞类型特异性基因。广泛的数据分析表明，与传统方法相比，所提出的方法能识别出更多具有生物学意义的细胞特异性基因。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Genome Biology Biochemistry, Genetics and Molecular Biology-Genetics

CiteScore

21.00

自引率

3.30%

发文量

241

审稿时长

2 months

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