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Protocol for unsupervised inference of cell-cell communication using matrix decomposition.
Liu, Yi; Chang, Xiao; Liu, Xiaoping.
Afiliación
  • Liu Y; Key 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.
  • Chang X; Institute of Statistics and Applied Mathematics, Anhui University of Finance and Economics, Bengbu 233030, China. Electronic address: chxlaugh@aufe.edu.cn.
  • Liu X; Key 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. Electronic address: xpliu@ucas.ac.cn.
STAR Protoc ; 5(2): 103006, 2024 Jun 21.
Article en En | MEDLINE | ID: mdl-38602871
ABSTRACT
Exploring cell-cell communication is pivotal for understanding biological processes in multicellular life forms. Here, we present a protocol that details the use of matrix decomposition to infer cell-cell communication (MDIC3) for unsupervised cell-cell communication inference. We describe steps for using the MDIC3 Python scripts to deduce cell-cell communication and identify key ligand-receptor pairs between a specific cell type pair from a single-cell gene expression dataset. This protocol has potential application in cell-cell communication inference on any species. For complete details on the use and execution of this protocol, please refer to Liu et al.1.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Comunicación Celular Límite: Animals / Humans Idioma: En Revista: STAR Protoc Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Comunicación Celular Límite: Animals / Humans Idioma: En Revista: STAR Protoc Año: 2024 Tipo del documento: Article País de afiliación: China