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Deciphering tissue structure and function using spatial transcriptomics
The rapid development of spatial transcriptomics (ST) techniques has allowed the measurement of transcriptional levels across many genes together with the spatial positions of cells. This has led to an explosion of interest in computational methods and techniques for harnessing both spatial and tran...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8913632/ https://www.ncbi.nlm.nih.gov/pubmed/35273328 http://dx.doi.org/10.1038/s42003-022-03175-5 |
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author | Walker, Benjamin L. Cang, Zixuan Ren, Honglei Bourgain-Chang, Eric Nie, Qing |
author_facet | Walker, Benjamin L. Cang, Zixuan Ren, Honglei Bourgain-Chang, Eric Nie, Qing |
author_sort | Walker, Benjamin L. |
collection | PubMed |
description | The rapid development of spatial transcriptomics (ST) techniques has allowed the measurement of transcriptional levels across many genes together with the spatial positions of cells. This has led to an explosion of interest in computational methods and techniques for harnessing both spatial and transcriptional information in analysis of ST datasets. The wide diversity of approaches in aim, methodology and technology for ST provides great challenges in dissecting cellular functions in spatial contexts. Here, we synthesize and review the key problems in analysis of ST data and methods that are currently applied, while also expanding on open questions and areas of future development. |
format | Online Article Text |
id | pubmed-8913632 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-89136322022-03-30 Deciphering tissue structure and function using spatial transcriptomics Walker, Benjamin L. Cang, Zixuan Ren, Honglei Bourgain-Chang, Eric Nie, Qing Commun Biol Review Article The rapid development of spatial transcriptomics (ST) techniques has allowed the measurement of transcriptional levels across many genes together with the spatial positions of cells. This has led to an explosion of interest in computational methods and techniques for harnessing both spatial and transcriptional information in analysis of ST datasets. The wide diversity of approaches in aim, methodology and technology for ST provides great challenges in dissecting cellular functions in spatial contexts. Here, we synthesize and review the key problems in analysis of ST data and methods that are currently applied, while also expanding on open questions and areas of future development. Nature Publishing Group UK 2022-03-10 /pmc/articles/PMC8913632/ /pubmed/35273328 http://dx.doi.org/10.1038/s42003-022-03175-5 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 | Review Article Walker, Benjamin L. Cang, Zixuan Ren, Honglei Bourgain-Chang, Eric Nie, Qing Deciphering tissue structure and function using spatial transcriptomics |
title | Deciphering tissue structure and function using spatial transcriptomics |
title_full | Deciphering tissue structure and function using spatial transcriptomics |
title_fullStr | Deciphering tissue structure and function using spatial transcriptomics |
title_full_unstemmed | Deciphering tissue structure and function using spatial transcriptomics |
title_short | Deciphering tissue structure and function using spatial transcriptomics |
title_sort | deciphering tissue structure and function using spatial transcriptomics |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8913632/ https://www.ncbi.nlm.nih.gov/pubmed/35273328 http://dx.doi.org/10.1038/s42003-022-03175-5 |
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