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

Reference52 articles.

1. The IUPHAR/BPS guide to PHARMACOLOGY in 2020: extending immunopharmacology content and introducing the IUPHAR/MMV guide to MALARIA PHARMACOLOGY;Armstrong;Nucleic Acids Res,2020

2. Signaling receptome: a genomic and evolutionary perspective of plasma membrane receptors involved in signal transduction;Ben-Shlomo;Science's STKE,2003

3. Mapping the physical network of cellular interactions;Boisset;Nat. Methods,2018

4. NicheNet: modeling intercellular communication by linking ligands to target genes;Browaeys;Nat. Methods,2020

5. SingleCellSignalR: inference of intercellular networks from single-cell transcriptomics;Cabello-Aguilar;Nucleic Acids Res,2020

Cited by 47 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3