College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China.
Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou 330110, China.
Nucleic Acids Res. 2024 Jan 5;52(D1):D859-D870. doi: 10.1093/nar/gkad874.
Large-scale studies of single-cell sequencing and biological experiments have successfully revealed expression patterns that distinguish different cell types in tissues, emphasizing the importance of studying cellular heterogeneity and accurately annotating cell types. Analysis of gene expression profiles in these experiments provides two essential types of data for cell type annotation: annotated references and canonical markers. In this study, the first comprehensive database of single-cell transcriptomic annotation resource (CellSTAR) was thus developed. It is unique in (a) offering the comprehensive expertly annotated reference data for annotating hundreds of cell types for the first time and (b) enabling the collective consideration of reference data and marker genes by incorporating tens of thousands of markers. Given its unique features, CellSTAR is expected to attract broad research interests from the technological innovations in single-cell transcriptomics, the studies of cellular heterogeneity & dynamics, and so on. It is now publicly accessible without any login requirement at: https://idrblab.org/cellstar.
大规模的单细胞测序和生物学实验研究成功揭示了区分组织中不同细胞类型的表达模式，强调了研究细胞异质性和准确注释细胞类型的重要性。这些实验中基因表达谱的分析为细胞类型注释提供了两种基本类型的数据：注释的参考文献和典型标记物。在这项研究中，因此开发了第一个单细胞转录组注释资源的综合数据库（CellSTAR）。它的独特之处在于：(a) 提供了全面的专家注释参考数据，首次可注释数百种细胞类型；(b) 通过整合数以万计的标记物，实现了参考数据和标记基因的集体考虑。鉴于其独特的功能，CellSTAR 有望吸引单细胞转录组学的技术创新、细胞异质性和动力学等方面的广泛研究兴趣。它现在可以在无需登录的情况下公开访问：https://idrblab.org/cellstar。
