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CrossTalkeR: analysis and visualization of ligand–receptorne tworks

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....

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Autores principales: Nagai, James S, Leimkühler, Nils B, Schaub, Michael T, Schneider, Rebekka K, Costa, Ivan G
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9502146/
https://www.ncbi.nlm.nih.gov/pubmed/35032393
http://dx.doi.org/10.1093/bioinformatics/btab370
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author Nagai, James S
Leimkühler, Nils B
Schaub, Michael T
Schneider, Rebekka K
Costa, Ivan G
author_facet Nagai, James S
Leimkühler, Nils B
Schaub, Michael T
Schneider, Rebekka K
Costa, Ivan G
author_sort Nagai, James S
collection PubMed
description 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 visualization 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 versus homeostasis. A case study on scRNA-seq of human myeloproliferative neoplasms reinforces the strengths of CrossTalkeR for characterization of changes in cellular crosstalk in disease. AVAILABILITY AND IMPLEMENTATION: CrosstalkeR is an R package available at: Github: https://github.com/CostaLab/CrossTalkeR. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-95021462022-09-26 CrossTalkeR: analysis and visualization of ligand–receptorne tworks Nagai, James S Leimkühler, Nils B Schaub, Michael T Schneider, Rebekka K Costa, Ivan G Bioinformatics Applications Notes 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 visualization 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 versus homeostasis. A case study on scRNA-seq of human myeloproliferative neoplasms reinforces the strengths of CrossTalkeR for characterization of changes in cellular crosstalk in disease. AVAILABILITY AND IMPLEMENTATION: CrosstalkeR is an R package available at: Github: https://github.com/CostaLab/CrossTalkeR. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2021-05-14 /pmc/articles/PMC9502146/ /pubmed/35032393 http://dx.doi.org/10.1093/bioinformatics/btab370 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Applications Notes
Nagai, James S
Leimkühler, Nils B
Schaub, Michael T
Schneider, Rebekka K
Costa, Ivan G
CrossTalkeR: analysis and visualization of ligand–receptorne tworks
title CrossTalkeR: analysis and visualization of ligand–receptorne tworks
title_full CrossTalkeR: analysis and visualization of ligand–receptorne tworks
title_fullStr CrossTalkeR: analysis and visualization of ligand–receptorne tworks
title_full_unstemmed CrossTalkeR: analysis and visualization of ligand–receptorne tworks
title_short CrossTalkeR: analysis and visualization of ligand–receptorne tworks
title_sort crosstalker: analysis and visualization of ligand–receptorne tworks
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9502146/
https://www.ncbi.nlm.nih.gov/pubmed/35032393
http://dx.doi.org/10.1093/bioinformatics/btab370
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