scCTS: identifying the cell type-specific marker genes from population-level single-cell RNA-seq
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.
Authors
- Luxiao Chen
- Tao Deng (ORCID: https://orcid.org/0000-0001-7401-311X)
- Hao Wu (ORCID: https://orcid.org/0000-0003-1269-7354)
- Zhenxing Guo (ORCID: https://orcid.org/0000-0003-1681-1337)
Institutions
- Emory University (US)
- Shenzhen University (CN)
- Shenzhen Research Institute of Big Data (CN)
- Chinese University of Hong Kong, Shenzhen (CN)
- Shenzhen Institutes of Advanced Technology (CN)
- Shenzhen Technology University (CN)
Publication Details
- Journal
- Genome biology
- Published
- 2024-10-14
- DOI
- https://doi.org/10.1186/s13059-024-03410-8
- Citations
- 4
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.94