Modeling intercellular communication in tissues using spatial graphs of cells

Models of intercellular communication in tissues are based on molecular profiles of dissociated cells, are limited to receptor–ligand signaling and ignore spatial proximity in situ. We present node-centric expression modeling, a method based on graph neural networks that estimates the effects of nic...

Descripción completa

Detalles Bibliográficos
Autores principales: Fischer, David S., Schaar, Anna C., Theis, Fabian J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group US 2022
Materias:
Brief Communication
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10017508/
https://www.ncbi.nlm.nih.gov/pubmed/36302986
http://dx.doi.org/10.1038/s41587-022-01467-z
_version_ 1784907602438651904
author Fischer, David S.
Schaar, Anna C.
Theis, Fabian J.
author_facet Fischer, David S.
Schaar, Anna C.
Theis, Fabian J.
author_sort Fischer, David S.
collection PubMed
description Models of intercellular communication in tissues are based on molecular profiles of dissociated cells, are limited to receptor–ligand signaling and ignore spatial proximity in situ. We present node-centric expression modeling, a method based on graph neural networks that estimates the effects of niche composition on gene expression in an unbiased manner from spatial molecular profiling data. We recover signatures of molecular processes known to underlie cell communication.
format Online
Article
Text
id pubmed-10017508
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Nature Publishing Group US
record_format MEDLINE/PubMed
spelling pubmed-100175082023-03-17 Modeling intercellular communication in tissues using spatial graphs of cells Fischer, David S. Schaar, Anna C. Theis, Fabian J. Nat Biotechnol Brief Communication Models of intercellular communication in tissues are based on molecular profiles of dissociated cells, are limited to receptor–ligand signaling and ignore spatial proximity in situ. We present node-centric expression modeling, a method based on graph neural networks that estimates the effects of niche composition on gene expression in an unbiased manner from spatial molecular profiling data. We recover signatures of molecular processes known to underlie cell communication. Nature Publishing Group US 2022-10-27 2023 /pmc/articles/PMC10017508/ /pubmed/36302986 http://dx.doi.org/10.1038/s41587-022-01467-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Brief Communication
Fischer, David S.
Schaar, Anna C.
Theis, Fabian J.
Modeling intercellular communication in tissues using spatial graphs of cells
title Modeling intercellular communication in tissues using spatial graphs of cells
title_full Modeling intercellular communication in tissues using spatial graphs of cells
title_fullStr Modeling intercellular communication in tissues using spatial graphs of cells
title_full_unstemmed Modeling intercellular communication in tissues using spatial graphs of cells
title_short Modeling intercellular communication in tissues using spatial graphs of cells
title_sort modeling intercellular communication in tissues using spatial graphs of cells
topic Brief Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10017508/
https://www.ncbi.nlm.nih.gov/pubmed/36302986
http://dx.doi.org/10.1038/s41587-022-01467-z
work_keys_str_mv AT fischerdavids modelingintercellularcommunicationintissuesusingspatialgraphsofcells
AT schaarannac modelingintercellularcommunicationintissuesusingspatialgraphsofcells
AT theisfabianj modelingintercellularcommunicationintissuesusingspatialgraphsofcells

Ejemplares similares