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A Rapid, Scalable Method for the Isolation, Functional Study, and Analysis of Cell-derived Extracellular Matrix
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Protocol for unsupervised inference of cell-cell communication using matrix decomposition.

Yi Liu1, Xiao Chang2, Xiaoping Liu3

  • 1Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China; Institute of Statistics and Applied Mathematics, Anhui University of Finance and Economics, Bengbu 233030, China; Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610054, China.

STAR Protocols
|April 11, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces Matrix Decomposition to Infer Cell-Cell Communication (MDIC3), a new method for unsupervised analysis of cell-cell signaling. MDIC3 identifies crucial ligand-receptor interactions in single-cell data for any species.

Keywords:
BioinformaticsCell BiologyGene ExpressionSingle Cell

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Area of Science:

  • Cellular Biology
  • Bioinformatics
  • Genomics

Background:

  • Understanding multicellular life requires exploring cell-cell communication.
  • Identifying signaling pathways is crucial for biological research.

Purpose of the Study:

  • To present a novel protocol for unsupervised cell-cell communication inference.
  • To detail the use of matrix decomposition for this purpose.

Main Methods:

  • The study details a protocol using Matrix Decomposition to Infer Cell-Cell Communication (MDIC3).
  • Python scripts are provided to deduce cell-cell communication from single-cell gene expression data.
  • The method identifies ligand-receptor pairs between specific cell types.

Main Results:

  • MDIC3 enables unsupervised inference of cell-cell communication.
  • Key ligand-receptor pairs can be identified between cell types.
  • The protocol is applicable to single-cell gene expression datasets.

Conclusions:

  • MDIC3 offers a robust method for cell-cell communication inference.
  • This protocol can be applied across different species.
  • The findings advance the understanding of intercellular signaling in biological systems.