SCSA: A Cell Type Annotation Tool for Single-Cell RNA-seq Data.

ABSTRACT: Currently most methods take manual strategies to annotate cell types after clustering the single-cell RNA sequencing (scRNA-seq) data. Such methods are labor-intensive and heavily rely on user expertise, which may lead to inconsistent results. We present SCSA, an automatic tool to annotate cell types from scRNA-seq data, based on a score annotation model combining differentially expressed genes (DEGs) and confidence levels of cell markers from both known and user-defined information. Evaluation on real scRNA-seq datasets from different sources with other methods shows that SCSA is able to assign the cells into the correct types at a fully automated mode with a desirable precision.

SUBMITTER: Cao Y 

PROVIDER: S-EPMC7235421 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature