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InterCellDB: A User‐Defined Database for Inferring Intercellular Networks

Recent advances in single cell RNA sequencing (scRNA‐seq) empower insights into cell–cell crosstalk within specific tissues. However, customizable data analysis tools that decipher intercellular communication from gene expression in association with biological functions are lacking. The authors have...

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Detalles Bibliográficos
Autores principales: Jin, Ziyang, Zhang, Xiaotao, Dai, Xuejiao, Huang, Jinyan, Hu, Xiaoming, Zhang, Jianmin, Shi, Ligen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9353444/
https://www.ncbi.nlm.nih.gov/pubmed/35652265
http://dx.doi.org/10.1002/advs.202200045
Descripción
Sumario:Recent advances in single cell RNA sequencing (scRNA‐seq) empower insights into cell–cell crosstalk within specific tissues. However, customizable data analysis tools that decipher intercellular communication from gene expression in association with biological functions are lacking. The authors have developed InterCellDB, a platform that allows a user‐defined analysis of intercellular communication using scRNA‐seq datasets in combination with protein annotation information, including cellular localization and functional classification, and protein interaction properties. The application of InterCellDB in tumor microenvironment research is exemplified using two independent scRNA‐seq datasets from human and mouse and it is demonstrated that InterCellDB‐inferred cell–cell interactions and ligand–receptor pairs are experimentally valid.