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.

中文翻译：

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scCTS：从群体水平的单细胞 RNA-seq 中鉴定细胞类型特异性标记基因


单细胞 RNA 测序 （scRNA-seq） 提供来自复杂样品的单个细胞的基因表达谱，有助于检测细胞类型特异性标记基因。在具有多个供体的 scRNA-seq 实验中，群体水平的变化为细胞类型特异性基因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。受这一观察结果的启发，我们开发了一个名为 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，所提出的方法鉴定出更具生物学意义的细胞类型特异性基因。