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Analysis and Visualization of Spatial Transcriptomic Data
Human and animal tissues consist of heterogeneous cell types that organize and interact in highly structured manners. Bulk and single-cell sequencing technologies remove cells from their original microenvironments, resulting in a loss of spatial information. Spatial transcriptomics is a recent techn...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8829434/ https://www.ncbi.nlm.nih.gov/pubmed/35154244 http://dx.doi.org/10.3389/fgene.2021.785290 |
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author | Liu, Boxiang Li, Yanjun Zhang, Liang |
author_facet | Liu, Boxiang Li, Yanjun Zhang, Liang |
author_sort | Liu, Boxiang |
collection | PubMed |
description | Human and animal tissues consist of heterogeneous cell types that organize and interact in highly structured manners. Bulk and single-cell sequencing technologies remove cells from their original microenvironments, resulting in a loss of spatial information. Spatial transcriptomics is a recent technological innovation that measures transcriptomic information while preserving spatial information. Spatial transcriptomic data can be generated in several ways. RNA molecules are measured by in situ sequencing, in situ hybridization, or spatial barcoding to recover original spatial coordinates. The inclusion of spatial information expands the range of possibilities for analysis and visualization, and spurred the development of numerous novel methods. In this review, we summarize the core concepts of spatial genomics technology and provide a comprehensive review of current analysis and visualization methods for spatial transcriptomics. |
format | Online Article Text |
id | pubmed-8829434 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-88294342022-02-11 Analysis and Visualization of Spatial Transcriptomic Data Liu, Boxiang Li, Yanjun Zhang, Liang Front Genet Genetics Human and animal tissues consist of heterogeneous cell types that organize and interact in highly structured manners. Bulk and single-cell sequencing technologies remove cells from their original microenvironments, resulting in a loss of spatial information. Spatial transcriptomics is a recent technological innovation that measures transcriptomic information while preserving spatial information. Spatial transcriptomic data can be generated in several ways. RNA molecules are measured by in situ sequencing, in situ hybridization, or spatial barcoding to recover original spatial coordinates. The inclusion of spatial information expands the range of possibilities for analysis and visualization, and spurred the development of numerous novel methods. In this review, we summarize the core concepts of spatial genomics technology and provide a comprehensive review of current analysis and visualization methods for spatial transcriptomics. Frontiers Media S.A. 2022-01-27 /pmc/articles/PMC8829434/ /pubmed/35154244 http://dx.doi.org/10.3389/fgene.2021.785290 Text en Copyright © 2022 Liu, Li and Zhang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Liu, Boxiang Li, Yanjun Zhang, Liang Analysis and Visualization of Spatial Transcriptomic Data |
title | Analysis and Visualization of Spatial Transcriptomic Data |
title_full | Analysis and Visualization of Spatial Transcriptomic Data |
title_fullStr | Analysis and Visualization of Spatial Transcriptomic Data |
title_full_unstemmed | Analysis and Visualization of Spatial Transcriptomic Data |
title_short | Analysis and Visualization of Spatial Transcriptomic Data |
title_sort | analysis and visualization of spatial transcriptomic data |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8829434/ https://www.ncbi.nlm.nih.gov/pubmed/35154244 http://dx.doi.org/10.3389/fgene.2021.785290 |
work_keys_str_mv | AT liuboxiang analysisandvisualizationofspatialtranscriptomicdata AT liyanjun analysisandvisualizationofspatialtranscriptomicdata AT zhangliang analysisandvisualizationofspatialtranscriptomicdata |