Spatial omics technologies at multimodal and single cell/subcellular level

Spatial omics technologies enable a deeper understanding of cellular organizations and interactions within a tissue of interest. These assays can identify specific compartments or regions in a tissue with differential transcript or protein abundance, delineate their interactions, and complement othe...

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Autores principales: Park, Jiwoon, Kim, Junbum, Lewy, Tyler, Rice, Charles M., Elemento, Olivier, Rendeiro, André F., Mason, Christopher E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Review
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9746133/
https://www.ncbi.nlm.nih.gov/pubmed/36514162
http://dx.doi.org/10.1186/s13059-022-02824-6
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author Park, Jiwoon
Kim, Junbum
Lewy, Tyler
Rice, Charles M.
Elemento, Olivier
Rendeiro, André F.
Mason, Christopher E.
author_facet Park, Jiwoon
Kim, Junbum
Lewy, Tyler
Rice, Charles M.
Elemento, Olivier
Rendeiro, André F.
Mason, Christopher E.
author_sort Park, Jiwoon
collection PubMed
description Spatial omics technologies enable a deeper understanding of cellular organizations and interactions within a tissue of interest. These assays can identify specific compartments or regions in a tissue with differential transcript or protein abundance, delineate their interactions, and complement other methods in defining cellular phenotypes. A variety of spatial methodologies are being developed and commercialized; however, these techniques differ in spatial resolution, multiplexing capability, scale/throughput, and coverage. Here, we review the current and prospective landscape of single cell to subcellular resolution spatial omics technologies and analysis tools to provide a comprehensive picture for both research and clinical applications. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-022-02824-6.
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spelling pubmed-97461332022-12-14 Spatial omics technologies at multimodal and single cell/subcellular level Park, Jiwoon Kim, Junbum Lewy, Tyler Rice, Charles M. Elemento, Olivier Rendeiro, André F. Mason, Christopher E. Genome Biol Review Spatial omics technologies enable a deeper understanding of cellular organizations and interactions within a tissue of interest. These assays can identify specific compartments or regions in a tissue with differential transcript or protein abundance, delineate their interactions, and complement other methods in defining cellular phenotypes. A variety of spatial methodologies are being developed and commercialized; however, these techniques differ in spatial resolution, multiplexing capability, scale/throughput, and coverage. Here, we review the current and prospective landscape of single cell to subcellular resolution spatial omics technologies and analysis tools to provide a comprehensive picture for both research and clinical applications. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-022-02824-6. BioMed Central 2022-12-13 /pmc/articles/PMC9746133/ /pubmed/36514162 http://dx.doi.org/10.1186/s13059-022-02824-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Review
Park, Jiwoon
Kim, Junbum
Lewy, Tyler
Rice, Charles M.
Elemento, Olivier
Rendeiro, André F.
Mason, Christopher E.
Spatial omics technologies at multimodal and single cell/subcellular level
title Spatial omics technologies at multimodal and single cell/subcellular level
title_full Spatial omics technologies at multimodal and single cell/subcellular level
title_fullStr Spatial omics technologies at multimodal and single cell/subcellular level
title_full_unstemmed Spatial omics technologies at multimodal and single cell/subcellular level
title_short Spatial omics technologies at multimodal and single cell/subcellular level
title_sort spatial omics technologies at multimodal and single cell/subcellular level
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9746133/
https://www.ncbi.nlm.nih.gov/pubmed/36514162
http://dx.doi.org/10.1186/s13059-022-02824-6
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