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

作者：Yinghao Cao, Xiaoyue Wang, Gongxin Peng · 发表于：Frontiers in Genetics · 年份：2020 · DOI：10.3389/fgene.2020.00490 · 被引用次数：182 · 研究领域：Single-cell and spatial transcriptomics、Extracellular vesicles in disease、Cell Image Analysis Techniques

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.