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CellCall: integrating paired ligand–receptor and transcription factor activities for cell–cell communication
- Source :
- Nucleic Acids Research
- Publication Year :
- 2021
- Publisher :
- Oxford University Press (OUP), 2021.
-
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.
- Subjects :
- 0301 basic medicine
Cell type
Cell signaling
AcademicSubjects/SCI00010
Cell Communication
Computational biology
Biology
Ligands
Plot (graphics)
03 medical and health sciences
0302 clinical medicine
Single-cell analysis
RNA, Small Cytoplasmic
Genetics
Humans
Transcription factor
Base Sequence
Sequence Analysis, RNA
Computational Biology
Crosstalk (biology)
030104 developmental biology
Gene Expression Regulation
030220 oncology & carcinogenesis
DECIPHER
Communication Analysis
Single-Cell Analysis
Algorithms
Transcription Factors
Subjects
Details
- ISSN :
- 13624962 and 03051048
- Volume :
- 49
- Database :
- OpenAIRE
- Journal :
- Nucleic Acids Research
- Accession number :
- edsair.doi.dedup.....54ad112f7f8449cad41b327077034267
- Full Text :
- https://doi.org/10.1093/nar/gkab638