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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....
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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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. |
format | Online Article Text |
id | pubmed-9502146 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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