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CrossTalkeR: Analysis and Visualisation of Ligand Receptor Networks

View ORCID ProfileJames S. Nagai, View ORCID ProfileNils B. Leimkühler, View ORCID ProfileMichael T. Schaub, View ORCID ProfileRebekka K. Schneider, View ORCID ProfileIvan G. Costa
doi: https://doi.org/10.1101/2021.01.20.427390
James S. Nagai
1Institute for Computational Genomics, Joint Research Center for Computational Biomedicine, RWTH Aachen University Medical School, Germany
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Nils B. Leimkühler
2Department of Hematology and Stem Cell Transplantation, University Hospital Essen, Germany
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Michael T. Schaub
3Department of Computer Science, RWTH Aachen University, Germany
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Rebekka K. Schneider
4Department of Hematology, Erasmus Medical Center, the Netherlands
5Department of Cell Biology, Institute for Biomedical Engineering, Faculty of Medicine, RWTH Aachen University, Germany
6Oncode Institute, Erasmus Medical Center, the Netherlands
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Ivan G. Costa
1Institute for Computational Genomics, Joint Research Center for Computational Biomedicine, RWTH Aachen University Medical School, Germany
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ABSTRACT

Motivation Ligand-receptor (LR) network analysis allows the characterization of cellular crosstalk based on single cell RNA-seq data. However, current methods typically provide a list of inferred LR interactions and do not allow the researcher to focus on specific cell types, ligands or receptors. In addition, most of these methods cannot quantify changes in crosstalk between two biological phenotypes.

Results CrossTalkeR is a framework for network analysis and visualisation of LR interactions. CrossTalkeR identifies relevant ligands, receptors and cell types contributing to changes in cell communication when contrasting two biological phenotypes, i.e. disease vs. homeostasis. A case study on scRNA-seq of human myeloproliferative neoplasms reinforces the strengths of CrossTalkeR for characterisation of changes in cellular crosstalk in disease.

Availability and Implementation CrosstalkeR is an R package available at https://github.com/CostaLab/CrossTalkeR.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • ↵* ivan.costa{at}rwth-aachen.de

  • https://github.com/CostaLab/CrossTalkeR

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted April 18, 2021.
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CrossTalkeR: Analysis and Visualisation of Ligand Receptor Networks
James S. Nagai, Nils B. Leimkühler, Michael T. Schaub, Rebekka K. Schneider, Ivan G. Costa
bioRxiv 2021.01.20.427390; doi: https://doi.org/10.1101/2021.01.20.427390
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CrossTalkeR: Analysis and Visualisation of Ligand Receptor Networks
James S. Nagai, Nils B. Leimkühler, Michael T. Schaub, Rebekka K. Schneider, Ivan G. Costa
bioRxiv 2021.01.20.427390; doi: https://doi.org/10.1101/2021.01.20.427390

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