Abstract
Background: Single-cell RNA-sequencing (scRNA-seq) has become a widely used tool for both basic and translational biomedical research. In scRNA-seq data analysis, cell type annotation is an essential but challenging step. In the past few years, several annotation tools have been developed. These methods require either labeled training/reference datasets, which are not always available, or a list of predefined cell subset markers, which are subject to biases. Thus, a user-friendly and precise annotation tool is still critically needed. Results: We curated a comprehensive cell marker database named scMayoMapDatabase and developed a companion R package scMayoMap, an easy-to-use single-cell annotation tool, to provide fast and accurate cell type annotation. The effectiveness of scMayoMap was demonstrated in 48 independent scRNA-seq datasets across different platforms and tissues. Additionally, the scMayoMapDatabase can be integrated with other tools and further improve their performance. Conclusions: scMayoMap and scMayoMapDatabase will help investigators to define the cell types in their scRNA-seq data in a streamlined and user-friendly way.
Original language | English (US) |
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Article number | 223 |
Journal | BMC Biology |
Volume | 21 |
Issue number | 1 |
DOIs | |
State | Published - Dec 2023 |
Keywords
- Cell type annotation
- Cell type markers
- Single-cell RNA-sequencing
- scMayoMap
- scMayoMapDatabase
ASJC Scopus subject areas
- Biotechnology
- Structural Biology
- Ecology, Evolution, Behavior and Systematics
- Physiology
- General Biochemistry, Genetics and Molecular Biology
- General Agricultural and Biological Sciences
- Plant Science
- Developmental Biology
- Cell Biology