Protocol for directly selecting cell type marker genes for single-cell clustering analyses by Festem

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.<sup>1</sup>.

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Publication Details

Journal
STAR Protocols
Published
2024-12-18
DOI
https://doi.org/10.1016/j.xpro.2024.103514
Citations
1
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.23

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article

Protocol for directly selecting cell type marker genes for single-cell clustering analyses by Festem

Ruibin Xi, Zihao Chen, Changhu Wang
1 citations
STAR Protocols
Single-cell and spatial transcriptomics
0.23
article

Protocol for directly selecting cell type marker genes for single-cell clustering analyses by Festem

Ruibin Xi, Zihao Chen, Changhu Wang
article en
1 citations

Abstract

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.<sup>1</sup>.

STAR ProtocolsVol. 6(1)
Peking University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 40%
Single-cell and spatial transcriptomics
0.23
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