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Context-aware deconvolution of cell-cell communication with Tensor-cell2cell.

Erick Armingol1,2, Hratch M Baghdassarian1,2, Cameron Martino1,2,3

  • 1Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA, 92093, USA.

Nature Communications
|June 27, 2022
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Summary
This summary is machine-generated.

Tensor-cell2cell deciphers context-driven cell-cell communication patterns by analyzing multiple cellular states simultaneously. This novel method enhances understanding of complex biological communication in various conditions, including disease.

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Area of Science:

  • Computational Biology
  • Systems Biology
  • Genomics

Background:

  • Cell interactions and intercellular communication are crucial for determining cellular phenotypes.
  • Cellular context, including disease state and microenvironment, significantly shapes communication.
  • Existing computational tools often overlook cellular context or rely on limited pairwise comparisons.

Purpose of the Study:

  • To develop an unsupervised method, Tensor-cell2cell, for deciphering context-driven intercellular communication.
  • To simultaneously account for multiple cellular stages, states, or locations.
  • To uncover context-driven communication patterns linked to phenotypic states and cell type/ligand-receptor combinations.

Main Methods:

  • Utilized tensor decomposition for an unsupervised approach.
  • Developed Tensor-cell2cell to integrate multi-contextual single-cell data.
  • Applied the method to analyze communication patterns in Coronavirus Disease 2019 and Autism Spectrum Disorder.

Main Results:

  • Tensor-cell2cell identifies context-driven communication modules.
  • Successfully linked distinct communication processes to disease severity in COVID-19 and ASD.
  • Demonstrated robust improvement over existing analytical tools.

Conclusions:

  • Tensor-cell2cell provides an effective strategy for understanding complex intercellular communication.
  • The method accounts for multiple biological contexts, offering deeper insights.
  • Facilitates the study of cell-cell communication across diverse conditions and disease states.