CellCall: integrating paired ligand–receptor and transcription factor activities for cell–cell communication

Author:

Zhang Yang1,Liu Tianyuan1,Hu Xuesong2,Wang Mei2,Wang Jing1,Zou Bohao3,Tan Puwen1,Cui Tianyu1,Dou Yiying1,Ning Lin1,huang Yan1,Rao Shuan4,Wang Dong1ORCID,Zhao Xiaoyang256

Affiliation:

1. Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China

2. State Key Laboratory of Organ Failure Research, Department of Developmental Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China

3. Department of Statistics, University of California Davis, Davis, CA, USA

4. Department of Thoracic Surgery, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China

5. Guangdong Key Laboratory of Construction and Detection in Tissue Engineering, Southern Medical University, Guangzhou 510515, China

6. Department of Gynecology, Zhujiang Hospital, Southern Medical University, Guangzhou 510280, China

Abstract

Abstract With the dramatic development of single-cell RNA sequencing (scRNA-seq) technologies, the systematic decoding of cell-cell communication has received great research interest. To date, several in-silico methods have been developed, but most of them lack the ability to predict the communication pathways connecting the insides and outsides of cells. Here, we developed CellCall, a toolkit to infer inter- and intracellular communication pathways by integrating paired ligand-receptor and transcription factor (TF) activity. Moreover, CellCall uses an embedded pathway activity analysis method to identify the significantly activated pathways involved in intercellular crosstalk between certain cell types. Additionally, CellCall offers a rich suite of visualization options (Circos plot, Sankey plot, bubble plot, ridge plot, etc.) to present the analysis results. Case studies on scRNA-seq datasets of human testicular cells and the tumor immune microenvironment demonstrated the reliable and unique functionality of CellCall in intercellular communication analysis and internal TF activity exploration, which were further validated experimentally. Comparative analysis of CellCall and other tools indicated that CellCall was more accurate and offered more functions. In summary, CellCall provides a sophisticated and practical tool allowing researchers to decipher intercellular communication and related internal regulatory signals based on scRNA-seq data. CellCall is freely available at https://github.com/ShellyCoder/cellcall.

Funder

National Key Research and Development Project of China

National Natural Science Foundation of China

Guangdong Basic and Applied Basic Research Foundation

China Postdoctoral Science Foundation

Guangzhou Science and Technology

Publisher

Oxford University Press (OUP)

Subject

Genetics

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