Abstract
Single-cell RNA sequencing (scRNA-seq) allows researchers to study biological activities at the cellular level, enabling the discovery of new cell types and the analysis of intercellular interactions. However, annotating cell types in scRNA-seq data is a crucial and time-consuming process, with its quality significantly influencing downstream analyses. Accurate identification of potential cell types provides valuable insights for discovering new cell populations or identifying novel markers for known cells, which may be utilized in future research. While various methods exist for single-cell annotation, one of the most common approaches is to use known cell markers. The CellMarker2.0 database, a human-curated repository of cell markers extracted from published articles, is widely used for this purpose. However, it currently offers only a web-based tool for usage, which can be inconvenient when integrating with workflows like Seurat. To address this limitation, we introduce easybio, an R package designed to streamline single-cell annotation using the CellMarker2.0 database in conjunction with Seurat. easybio provides a suite of functions for querying the CellMarker2.0 database locally, offering insights into potential cell types for each cluster. In addition to single-cell annotation, the package also supports various bioinformatics workflows, including RNA-seq analysis, making it a versatile tool for transcriptomic research.
Competing Interest Statement
The authors have declared no competing interest.