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Updated: Jun 21, 2025

Single-cell RNA-Seq of Defined Subsets of Retinal Ganglion Cells

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Published on: May 22, 2017

Directly selecting cell-type marker genes for single-cell clustering analyses.

Zihao Chen¹, Changhu Wang¹, Siyuan Huang²

¹School of Mathematical Sciences and Center for Statistical Science, Peking University, Beijing 100871, China.

Cell Reports Methods

|July 9, 2024

Summary

This summary is machine-generated.

Festial is a new statistical method that directly selects cell-type marker genes for single-cell RNA sequencing (scRNA-seq) studies. This approach improves cell type identification and discovers novel marker genes, even for rare cell populations.

Keywords:

CP: Systems biology clustering analysis double dipping feature screening heterogeneity test high-dimension data highly variable gene marker gene identification mixture model terminal exhausted T cell terminally differentiated effector memory T cell

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Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

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Published on: January 10, 2019

Area of Science:

Computational Biology
Genomics
Bioinformatics

Background:

Single-cell RNA sequencing (scRNA-seq) studies commonly use clustering and differential gene expression (DEG) analysis to identify cell types and marker genes.
Current methods often rely on surrogate criteria for gene selection, which can lead to missing important genes or including irrelevant ones, while DEG analysis suffers from selection bias.

Purpose of the Study:

To introduce Festem, a novel statistical method for the direct selection of cell-type marker genes in scRNA-seq data.
To overcome limitations of existing gene selection and marker detection methods in scRNA-seq analysis.

Main Methods:

Festial directly selects marker genes by identifying those with a heterogeneous distribution across cells that are informative for clustering.
The method was evaluated using simulations and real-world scRNA-seq datasets.

Main Results:

Festial demonstrates high precision and sensitivity in selecting marker genes.
The method successfully identified cell types that are often missed by conventional approaches.
Application to an intrahepatic cholangiocarcinoma dataset revealed diverse CD8+ T cell types and potential prognostic marker genes.

Conclusions:

Festial offers a more accurate and sensitive approach to cell-type marker gene selection in scRNA-seq.
This method enhances the identification of cellular heterogeneity and aids in discovering clinically relevant biomarkers.