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Spatial-Live: A lightweight and versatile tool for single cell spatial-omics data visualization

Single cell spatial-omics data visualization plays a pivotal role in unraveling the intricate spatial organization and heterogeneity of cellular systems. Although various software tools and packages have been developed for this purpose, challenges persist in terms of user-friendly accessibility, dat...

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Detalles Bibliográficos
Autores principales: Ye, Zhenqing, Lai, Zhao, Zheng, Siyuan, Chen, Yidong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10592799/
https://www.ncbi.nlm.nih.gov/pubmed/37873441
http://dx.doi.org/10.1101/2023.09.24.559173
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author Ye, Zhenqing
Lai, Zhao
Zheng, Siyuan
Chen, Yidong
author_facet Ye, Zhenqing
Lai, Zhao
Zheng, Siyuan
Chen, Yidong
author_sort Ye, Zhenqing
collection PubMed
description Single cell spatial-omics data visualization plays a pivotal role in unraveling the intricate spatial organization and heterogeneity of cellular systems. Although various software tools and packages have been developed for this purpose, challenges persist in terms of user-friendly accessibility, data integration, and interactivity. In this study, we introduce Spatial-Live, a lightweight and versatile viewer tool designed for flexible single-cell spatial-omics data visualization. Spatial-Live overcomes the fundamental limitations of two-dimensional (2D) orthographic modes by employing a layer-stacking strategy, enabling efficient rendering of diverse data types with interactive features, and enhancing visualization with richer information in a unified three-dimensional (3D) space.
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spelling pubmed-105927992023-10-24 Spatial-Live: A lightweight and versatile tool for single cell spatial-omics data visualization Ye, Zhenqing Lai, Zhao Zheng, Siyuan Chen, Yidong bioRxiv Article Single cell spatial-omics data visualization plays a pivotal role in unraveling the intricate spatial organization and heterogeneity of cellular systems. Although various software tools and packages have been developed for this purpose, challenges persist in terms of user-friendly accessibility, data integration, and interactivity. In this study, we introduce Spatial-Live, a lightweight and versatile viewer tool designed for flexible single-cell spatial-omics data visualization. Spatial-Live overcomes the fundamental limitations of two-dimensional (2D) orthographic modes by employing a layer-stacking strategy, enabling efficient rendering of diverse data types with interactive features, and enhancing visualization with richer information in a unified three-dimensional (3D) space. Cold Spring Harbor Laboratory 2023-10-04 /pmc/articles/PMC10592799/ /pubmed/37873441 http://dx.doi.org/10.1101/2023.09.24.559173 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.
spellingShingle Article
Ye, Zhenqing
Lai, Zhao
Zheng, Siyuan
Chen, Yidong
Spatial-Live: A lightweight and versatile tool for single cell spatial-omics data visualization
title Spatial-Live: A lightweight and versatile tool for single cell spatial-omics data visualization
title_full Spatial-Live: A lightweight and versatile tool for single cell spatial-omics data visualization
title_fullStr Spatial-Live: A lightweight and versatile tool for single cell spatial-omics data visualization
title_full_unstemmed Spatial-Live: A lightweight and versatile tool for single cell spatial-omics data visualization
title_short Spatial-Live: A lightweight and versatile tool for single cell spatial-omics data visualization
title_sort spatial-live: a lightweight and versatile tool for single cell spatial-omics data visualization
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10592799/
https://www.ncbi.nlm.nih.gov/pubmed/37873441
http://dx.doi.org/10.1101/2023.09.24.559173
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