ArticleCell reports methods2024
Combining LIANA and Tensor-cell2cell to decipher cell-cell communication across multiple samples.
Article in Cell reports methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 19 citations in OpenAlex.
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- An integrative single-nucleus multiomic atlas of the human left ventricle identifies gene regulatory network dynamics across cardiac development, aging, and disease.Genome biology · 2026Article
- Bridging cancer cell-intrinsic driver genes and -extrinsic cell-cell communication with Driver2Comm.PLoS computational biology · 2026Article
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- In-silico discovery of druggable molecular signatures that drive dengue fever to severe dengue fever highlighting common pathogenesis through single-cell RNA-Seq analysis.Scientific reports · 2025Article
- Integrating Spatial Omics and Deep Learning: Toward Predictive Models of Cardiomyocyte Differentiation Efficiency.Bioengineering (Basel, Switzerland) · 2025Review
- A Transcriptomic Roadmap of Parkinson's Disease Progression at Single Cell Resolution.medRxiv : the preprint server for health sciences · 2025Article
- Article
- Insights into regulatory T-cell and type-I interferon roles in determining abacavir-induced hypersensitivity or immune tolerance.Frontiers in immunology · 2025Article
- LIANA+ provides an all-in-one framework for cell-cell communication inference.Nature cell biology · 2024Article
- The diversification of methods for studying cell-cell interactions and communication.Nature reviews. Genetics · 2024Review
- Computational cell-cell interaction technologies drive mechanistic and biomarker discovery in the tumor microenvironment.Current opinion in biotechnology · 2024Review
- Multicellular factor analysis of single-cell data for a tissue-centric understanding of disease.eLife · 2023Article
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
Abstract
In recent years, data-driven inference of cell-cell communication has helped reveal coordinated biological processes across cell types. Here, we integrate two tools, LIANA and Tensor-cell2cell, which, when combined, can deploy multiple existing methods and resources to enable the robust and flexible identification of cell-cell communication programs across multiple samples. In this work, we show how the integration of our tools facilitates the choice of method to infer cell-cell communication and subsequently perform an unsupervised deconvolution to obtain and summarize biological insights. We explain how to perform the analysis step by step in both Python and R and provide online tutorials with detailed instructions available at https://ccc-protocols.readthedocs.io/. This workflow typically takes ∼1.5 h to complete from installation to downstream visualizations on a graphics processing unit-enabled computer for a dataset of ∼63,000 cells, 10 cell types, and 12 samples.
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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 OpenQuestion graph.