Literature DB >> 34331449

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

Yang Zhang1, Tianyuan Liu1, Xuesong Hu2, Mei Wang2, Jing Wang1, Bohao Zou3, Puwen Tan1, Tianyu Cui1, Yiying Dou1, Lin Ning1, Yan Huang1, Shuan Rao4, Dong Wang1, Xiaoyang Zhao2,5,6.   

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.
© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.

Entities:  

Year:  2021        PMID: 34331449     DOI: 10.1093/nar/gkab638

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  14 in total

1.  Analyzing network diversity of cell-cell interactions in COVID-19 using single-cell transcriptomics.

Authors:  Xinyi Wang; Axel A Almet; Qing Nie
Journal:  Front Genet       Date:  2022-08-29       Impact factor: 4.772

2.  Comparison of methods and resources for cell-cell communication inference from single-cell RNA-Seq data.

Authors:  Alberto Valdeolivas; Aurélien Dugourd; Daniel Dimitrov; Dénes Türei; Martin Garrido-Rodriguez; Paul L Burmedi; James S Nagai; Charlotte Boys; Ricardo O Ramirez Flores; Hyojin Kim; Bence Szalai; Ivan G Costa; Julio Saez-Rodriguez
Journal:  Nat Commun       Date:  2022-06-09       Impact factor: 17.694

3.  Dysregulation of Circadian Clock Genes as Significant Clinic Factor in the Tumorigenesis of Hepatocellular Carcinoma.

Authors:  Youfang Liang; Shaoxiang Wang; Xin Huang; Ruihuan Chai; Qian Tang; Rong Yang; Xiaoqing Huang; Xiao Wang; Kai Zheng
Journal:  Comput Math Methods Med       Date:  2021-10-29       Impact factor: 2.238

4.  Prediction of New Risk Genes and Potential Drugs for Rheumatoid Arthritis from Multiomics Data.

Authors:  Anteneh M Birga; Liping Ren; Huaichao Luo; Yang Zhang; Jian Huang
Journal:  Comput Math Methods Med       Date:  2022-01-31       Impact factor: 2.238

5.  Investigating the Intercellular Communication Network of Immune Cell in Acute Respiratory Distress Syndrome with Sepsis.

Authors:  Pei Tao; Jinzhou He; Tao Ai; Yinghong Fan; Wei Zeng
Journal:  Comput Math Methods Med       Date:  2022-02-16       Impact factor: 2.238

Review 6.  Extracellular citrate and metabolic adaptations of cancer cells.

Authors:  E Kenneth Parkinson; Jerzy Adamski; Grit Zahn; Andreas Gaumann; Fabian Flores-Borja; Christine Ziegler; Maria E Mycielska
Journal:  Cancer Metastasis Rev       Date:  2021-12-21       Impact factor: 9.264

Review 7.  Computational exploration of cellular communication in skin from emerging single-cell and spatial transcriptomic data.

Authors:  Suoqin Jin; Raul Ramos
Journal:  Biochem Soc Trans       Date:  2022-02-28       Impact factor: 4.919

8.  Knowledge-graph-based cell-cell communication inference for spatially resolved transcriptomic data with SpaTalk.

Authors:  Xin Shao; Chengyu Li; Haihong Yang; Xiaoyan Lu; Jie Liao; Jingyang Qian; Kai Wang; Junyun Cheng; Penghui Yang; Huajun Chen; Xiao Xu; Xiaohui Fan
Journal:  Nat Commun       Date:  2022-07-30       Impact factor: 17.694

9.  Cell Layers: uncovering clustering structure in unsupervised single-cell transcriptomic analysis.

Authors:  Andrew P Blair; Robert K Hu; Elie N Farah; Neil C Chi; Katherine S Pollard; Pawel F Przytycki; Irfan S Kathiriya; Benoit G Bruneau
Journal:  Bioinform Adv       Date:  2022-08-04

10.  Transcriptional and Immune Landscape of Cardiac Sarcoidosis.

Authors:  Jing Liu; Pan Ma; Lulu Lai; Ana Villanueva; Andrew Koenig; Gregory R Bean; Dawn E Bowles; Carolyn Glass; Michael Watson; Kory J Lavine; Chieh-Yu Lin
Journal:  Circ Res       Date:  2022-09-16       Impact factor: 23.213

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