Cellinker: a platform of ligand–receptor interactions for intercellular communication analysis

Author:

Zhang Yang1,Liu Tianyuan2,Wang Jing2,Zou Bohao3,Li Le4,Yao Linhui2,Chen Kechen2,Ning Lin5,Wu Bingyi1,Zhao Xiaoyang16,Wang Dong125

Affiliation:

1. Shunde Hospital, Southern Medical University (The First People’s Hospital of Shunde Foshan), Foshan 528308, China

2. Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China

3. Department of Statistics, University of California Davis, Davis, CA 95616, USA

4. Department of Pathology, Harbin Medical University, Harbin 150081, China

5. Dermatology Hospital, Southern Medical University, Guangzhou 510091, China

6. State Key Laboratory of Organ Failure Research, Department of Developmental Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China

Abstract

Abstract Motivation Ligand–receptor (L–R) interactions mediate cell adhesion, recognition and communication and play essential roles in physiological and pathological signaling. With the rapid development of single-cell RNA sequencing (scRNA-seq) technologies, systematically decoding the intercellular communication network involving L–R interactions has become a focus of research. Therefore, construction of a comprehensive, high-confidence and well-organized resource to retrieve L–R interactions in order to study the functional effects of cell–cell communications would be of great value. Results In this study, we developed Cellinker, a platform of literature-supported L–R interactions that play roles in cell–cell communication. We aimed to provide a useful platform for studies on cell–cell communication mediated by L–R interactions. The current version of Cellinker documents over 3700 human and 3200 mouse L–R protein–protein interactions (PPIs) and embeds a practical and convenient webserver with which researchers can decode intercellular communications based on scRNA-seq data. And over 400 endogenous small molecule (sMOL) related L–R interactions were collected as well. Moreover, to help with research on coronavirus (CoV) infection, Cellinker collects information on 16L–R PPIs involved in CoV–human interactions (including 12L–R PPIs involved in SARS-CoV-2 infection). In summary, Cellinker provides a user-friendly interface for querying, browsing and visualizing L–R interactions as well as a practical and convenient web tool for inferring intercellular communications based on scRNA-seq data. We believe this platform could promote intercellular communication research and accelerate the development of related algorithms for scRNA-seq studies. Availability and implementation Cellinker is available at http://www.rna-society.org/cellinker/ Supplementary information Supplementary data are available at Bioinformatics online.

Funder

National Key Research and Development Project of China

National Natural Science Foundation of China

Basic and Applied Basic Research Fund of Guangdong Province

China Postdoctoral Science Foundation

Guangzhou science and technology project key project topic

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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