InterCellDB: A User‐Defined Database for Inferring Intercellular Networks. Issue 22 (2nd June 2022)

• Record Type: Journal Article
• Authors: Jin, Ziyang; Zhang, Xiaotao; Dai, Xuejiao; Huang, Jinyan; Hu, Xiaoming; Zhang, Jianmin; Shi, Ligen
• Is Part Of: Advanced science. Volume 9:Issue 22(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-06-02
• Subjects: cellular localization -- functional annotation -- intercellular network -- scRNA‐seq -- user‐defined database; Science -- Periodicals; 505
• DOI: 10.1002/advs.202200045
• Languages: English
• ISSNs: 2198-3844

Abstract

Abstract: Recent advances in single cell RNA sequencing (scRNA‐seq) empower insights into cell–cell crosstalk within specific tissues. However, customizable data analysis tools that decipher intercellular communication from gene expression in association with biological functions are lacking. The authors have developed InterCellDB, a platform that allows a user‐defined analysis of intercellular communication using scRNA‐seq datasets in combination with protein annotation information, including cellular localization and functional classification, and protein interaction properties. The application of InterCellDB in tumor microenvironment research is exemplified using two independent scRNA‐seq datasets from human and mouse and it is demonstrated that InterCellDB‐inferred cell–cell interactions and ligand–receptor pairs are experimentally valid. Abstract : User‐defined analysis: A platform is developed for user‐defined analysis on intercellular crosstalk using single cell RNA sequencing (scRNA‐seq) datasets. Protein annotation including expression change, cellular localization and functional classification are considered. Protein interaction properties including evidence source, credibility score, action mode, and action effect are provided as well. Therefore, biological meaningful processes can be explored further by InterCellDB.