Evidence map›Paper›PMID 40133495›Full record

ReviewNature protocols2025

CellPhoneDB v5: inferring cell-cell communication from single-cell multiomics data.

Kevin Troulé, Robert Petryszak, Batuhan Cakir, James Cranley, Alicia Harasty, Martin Prete, Zewen Kelvin Tuong, Sarah A Teichmann, Luz Garcia-Alonso, Roser Vento-Tormo

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature protocols, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 120 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
120citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

120 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  6. IGF2-associated tumor cells and APOE-positive macrophages define an imatinib resistance-associated niche in gastrointestinal stromal tumors.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2026
    Article
  7. Upadacitinib Restrains the Pathogenic Fitness of CD4Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
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60 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Kevin TrouléWellcome Sanger Institute, Cambridge, UK.
Robert PetryszakWellcome Sanger Institute, Cambridge, UK.
Batuhan CakirWellcome Sanger Institute, Cambridge, UK.ORCID 0000-0003-4513-606X
James CranleyWellcome Sanger Institute, Cambridge, UK.ORCID 0000-0002-0408-5801
Alicia HarastyIan Frazer Centre for Children's Immunotherapy Research, Child Health Research Centre, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia.
Martin PreteWellcome Sanger Institute, Cambridge, UK.ORCID 0000-0002-5946-821X
Zewen Kelvin TuongWellcome Sanger Institute, Cambridge, UK.ORCID 0000-0002-6735-6808
Sarah A TeichmannWellcome Sanger Institute, Cambridge, UK.ORCID 0000-0002-6294-6366
Luz Garcia-AlonsoWellcome Sanger Institute, Cambridge, UK. lg18@sanger.ac.uk.ORCID 0000-0002-7863-9619
Roser Vento-TormoWellcome Sanger Institute, Cambridge, UK. rv4@sanger.ac.uk.ORCID 0000-0002-9870-8474

Funding

Chan Zuckerberg Initiative DAFWellcome Trust (Wellcome) Grant 220540/Z/20/A
6 · The paper itself

Abstract

Cell-cell communication is essential for tissue development, function and regeneration. The revolution of single-cell genomics technologies offers an unprecedented opportunity to uncover how cells communicate in vivo within their tissue niches and how disruption of these niches can lead to diseases and developmental abnormalities. CellPhoneDB is a bioinformatics toolkit designed to infer cell-cell communication by combining a curated repository of bona fide ligand-receptor interactions with methods to integrate these interactions with single-cell genomics data. Here we present a protocol for the latest version of CellPhoneDB (v5), offering several new features. First, the repository has been expanded by one-third with the addition of new interactions, including ~1,000 interactions mediated by nonpeptidic ligands such as steroidogenic hormones, neurotransmitters and small G-protein-coupled receptor (GPCR)-binding ligands. Second, we outline a new way of using the database that allows users to tailor queries to their experimental designs. Third, the update incorporates novel strategies to prioritize specific cell-cell interactions, leveraging information from other modalities such as tissue microenvironments derived from spatial transcriptomics technologies or transcription factor activities derived from a single-cell assay for transposase accessible chromatin assays. Finally, we describe the new CellPhoneDBViz module to interactively visualize and share results. Altogether, CellPhoneDB v5 enhances the precision of cell-cell communication inference, offering new insights into tissue biology in physiological microenvironments. This protocol typically takes ~15 min and requires basic knowledge of python.

Indexed as

Cell CommunicationComputational BiologyGenomicsSingle-Cell AnalysisSoftwareAnimalsHumansMultiomics

Identifiers

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.