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Cellinker: a platform of ligand-receptor interactions for intercellular communication analysis.
Zhang, Yang; Liu, Tianyuan; Wang, Jing; Zou, Bohao; Li, Le; Yao, Linhui; Chen, Kechen; Ning, Lin; Wu, Bingyi; Zhao, Xiaoyang; Wang, Dong.
  • Zhang Y; Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde Foshan), Foshan 528308, China.
  • Liu T; Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China.
  • Wang J; Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China.
  • Zou B; Department of Statistics, University of California Davis, Davis, California, USA.
  • Li L; Department of Pathology, Harbin Medical University, Harbin 150081, China.
  • Yao L; Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China.
  • Chen K; Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China.
  • Ning L; Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China.
  • Wu B; Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde Foshan), Foshan 528308, China.
  • Zhao X; Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde Foshan), Foshan 528308, China.
  • Wang D; Department of Developmental Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China.
Bioinformatics ; 2021 Jan 20.
Article in English | MEDLINE | ID: covidwho-1038279
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 manually curated resource 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 3,700 human and 3,200 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 16 L-R PPIs involved in CoV-human interactions (including 12 L-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:

Cellinker is available at http//www.rna-society.org/cellinker/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Full text: Available Collection: International databases Database: MEDLINE Language: English Journal subject: Medical Informatics Year: 2021 Document Type: Article Affiliation country: Bioinformatics

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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal subject: Medical Informatics Year: 2021 Document Type: Article Affiliation country: Bioinformatics