From G1 to M: a comparative study of methods for identifying cell cycle phases.

ABSTRACT: Accurate identification of cell cycle phases in single-cell RNA-sequencing (scRNA-seq) data is crucial for biomedical research. Many methods have been developed to tackle this challenge, employing diverse approaches to predict cell cycle phases. In this review article, we delve into the standard processes in identifying cell cycle phases within scRNA-seq data and present several representative methods for comparison. To rigorously assess the accuracy of these methods, we propose an error function and employ multiple benchmarking datasets encompassing human and mouse data. Our evaluation results reveal a key finding: the fit between the reference data and the dataset being analyzed profoundly impacts the effectiveness of cell cycle phase identification methods. Therefore, researchers must c

SUBMITTER: Guo X 

PROVIDER: S-EPMC10805071 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature