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Using R, Seurat, and CellChat to Analyze a Single-Cell Transcriptomics Dataset of Mouse Skin Wound Healing

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New avenues for systematically inferring cell-cell communication: through single-cell transcriptomics data.

Xin Shao¹, Xiaoyan Lu¹, Jie Liao¹

¹College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China.

|May 22, 2020

Summary

This summary is machine-generated.

Single-cell RNA sequencing (scRNA-seq) advances understanding of cell-cell communication in multicellular organisms. This study reviews methods, applications, and challenges for analyzing these vital biological interactions at a high resolution.

Keywords:

cell-cell communication chemical signal-dependent communication ligand-receptor interaction network biology physical contact-dependent communication single-cell RNA sequencing

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Area of Science:

Molecular Biology
Genomics
Bioinformatics

Background:

Cell-cell communication is fundamental for multicellular organism development and function.
Single-cell RNA sequencing (scRNA-seq) provides unprecedented resolution for studying cellular heterogeneity and tissue composition.
scRNA-seq enables systematic analysis of cell-cell communication at the single-cell level.

Purpose of the Study:

To summarize the workflow for cell-cell communication studies using scRNA-seq data.
To review common strategies for uncovering cell-cell communications.
To discuss current challenges, applications, and future perspectives in single-cell resolution communication studies.

Main Methods:

Data preparation and processing for scRNA-seq datasets.
Construction of cell-cell communication networks.
Review of physically vicinal structure-based and ligand-receptor interaction-based strategies.

Main Results:

A common workflow for scRNA-seq based cell-cell communication analysis is outlined.
Two primary strategies for identifying intercellular communication pathways are presented.
Key challenges and existing applications of single-cell communication studies are detailed.

Conclusions:

scRNA-seq is a powerful tool for dissecting complex cell-cell communication networks.
Understanding these interactions is crucial for numerous biological processes.
Future research directions and potential applications are proposed to advance the field.