Automatic cell type identification methods for single-cell RNA sequencing.

ABSTRACT: Single-cell RNA sequencing (scRNA-seq) has become a powerful tool for scientists of many research disciplines due to its ability to elucidate the heterogeneous and complex cell-type compositions of different tissues and cell populations. Traditional cell-type identification methods for scRNA-seq data analysis are time-consuming and knowledge-dependent for manual annotation. By contrast, automatic cell-type identification methods may have the advantages of being fast, accurate, and more user friendly. Here, we discuss and evaluate thirty-two published automatic methods for scRNA-seq data analysis in terms of their prediction accuracy, F1-score, unlabeling rate and running time. We highlight the advantages and disadvantages of these methods and provide recommendations of method choice depend

SUBMITTER: Xie B 

PROVIDER: S-EPMC8572862 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature