CellPhoneDB: inferring cell–cell communication from combined expression of multi-subunit ligand–receptor complexes
Top Cited Papers
- 26 February 2020
- journal article
- research article
- Published by Springer Science and Business Media LLC in Nature Protocols
- Vol. 15 (4), 1484-1506
- https://doi.org/10.1038/s41596-020-0292-x
Abstract
CellPhoneDB combines an interactive database and a statistical framework for the exploration of ligand-receptor interactions inferred from single-cell transcriptomics measurements. Cell-cell communication mediated by ligand-receptor complexes is critical to coordinating diverse biological processes, such as development, differentiation and inflammation. To investigate how the context-dependent crosstalk of different cell types enables physiological processes to proceed, we developed CellPhoneDB, a novel repository of ligands, receptors and their interactions. In contrast to other repositories, our database takes into account the subunit architecture of both ligands and receptors, representing heteromeric complexes accurately. We integrated our resource with a statistical framework that predicts enriched cellular interactions between two cell types from single-cell transcriptomics data. Here, we outline the structure and content of our repository, provide procedures for inferring cell-cell communication networks from single-cell RNA sequencing data and present a practical step-by-step guide to help implement the protocol. CellPhoneDB v.2.0 is an updated version of our resource that incorporates additional functionalities to enable users to introduce new interacting molecules and reduces the time and resources needed to interrogate large datasets. CellPhoneDB v.2.0 is publicly available, both as code and as a user-friendly web interface; it can be used by both experts and researchers with little experience in computational genomics. In our protocol, we demonstrate how to evaluate meaningful biological interactions with CellPhoneDB v.2.0 using published datasets. This protocol typically takes similar to 2 h to complete, from installation to statistical analysis and visualization, for a dataset of similar to 10 GB, 10,000 cells and 19 cell types, and using five threads.Keywords
Funding Information
- Wellcome Trust (211276/Z/18/Z)
- Wellcome Trust (WT206194)
- Wellcome Trust (211276/Z/18/Z)
- Wellcome Trust (WT206194)
- Wellcome Trust (211276/Z/18/Z)
- Wellcome Trust (WT206194)
- Wellcome Trust (211276/Z/18/Z)
This publication has 35 references indexed in Scilit:
- Single-cell in situ RNA profiling by sequential hybridizationNature Methods, 2014
- Pfam: the protein families databaseNucleic Acids Research, 2013
- The MIntAct project—IntAct as a common curation platform for 11 molecular interaction databasesNucleic Acids Research, 2013
- International Union of Basic and Clinical Pharmacology. LXXXIX. Update on the Extended Family of Chemokine Receptors and Introducing a New Nomenclature for Atypical Chemokine ReceptorsPharmacological Reviews, 2013
- Proteomics Standards Initiative Common Query InterfacePublished by Springer Science and Business Media LLC ,2013
- InnateDB: systems biology of innate immunity and beyond—recent updates and continuing curationNucleic Acids Research, 2012
- Protein interaction data curation: the International Molecular Exchange (IMEx) consortiumNature Methods, 2012
- MINT, the molecular interaction database: 2012 updateNucleic Acids Research, 2011
- Unequal evolutionary conservation of human protein interactions in interologous networksGenome Biology, 2007
- Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction NetworksGenome Research, 2003