CellSTAR: a comprehensive resource for single-cell transcriptomic annotation

Author:

Zhang Ying1ORCID,Sun Huaicheng1ORCID,Zhang Wei1,Fu Tingting1,Huang Shijie1,Mou Minjie1ORCID,Zhang Jinsong1,Gao Jianqing1,Ge Yichao12,Yang Qingxia34ORCID,Zhu Feng12ORCID

Affiliation:

1. College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University , Hangzhou  310058 , China

2. Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare , Hangzhou  330110 , China

3. Zhejiang Provincial Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases, Women's Hospital, Zhejiang University School of Medicine , Hangzhou  310058 , China

4. Department of Bioinformatics, School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications , Nanjing  210023 , China

Abstract

Abstract 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.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Zhejiang Province

National High-Level Talents Special Support Plan of China

‘Double Top-Class’ University Projects

Fundamental Research Funds for Central Universities

Westlake Laboratory of Life Sciences and Biomedicine

Key R&D Programs of Zhejiang Province

National Key Research and Development Program of China

Natural Science Foundation of Jiangsu Province

Information Technology Centers of Zhejiang University

Alibaba-Zhejiang University

Alibaba Cloud

Publisher

Oxford University Press (OUP)

Subject

Genetics

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