Chen Zihao, Wang Changhu, Xi Ruibin
School of Mathematical Sciences and Center for Statistical Science, Peking University, Beijing 100871, China.
STAR Protoc. 2025 Mar 21;6(1):103514. doi: 10.1016/j.xpro.2024.103514. Epub 2024 Dec 18.
Feature selection by expectation maximization test (Festem) enables the direct selection of cell type marker genes, facilitating downstream clustering of single-cell RNA sequencing (scRNA-seq) data. Here, we present a protocol for using Festem to identify marker genes in scRNA-seq data and perform subsequent analyses. We describe comprehensive steps for setting up the environment, marker gene selection, clustering, and marker gene assignment. This protocol yields both clustering results and identified marker genes, enhancing the interpretation of biological information in scRNA-seq data. For complete details on the use and execution of this protocol, please refer to Chen et al..
通过期望最大化测试进行特征选择(Festem)能够直接选择细胞类型标记基因,有助于对单细胞RNA测序(scRNA-seq)数据进行下游聚类。在此,我们提供了一个使用Festem在scRNA-seq数据中识别标记基因并进行后续分析的方案。我们描述了设置环境、标记基因选择、聚类和标记基因分配的全面步骤。该方案既能产生聚类结果,又能识别标记基因,增强了对scRNA-seq数据中生物信息的解读。有关该方案使用和执行的完整详细信息,请参考Chen等人的研究。