Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Spatial transcriptomic and proteomic technologies have provided new opportunities to investigate cells in their native microenvironment. Here we present Giotto, a comprehensive and open-source toolbox for spatial data analysis and visualization. The analysis module provides end-to-end analysis by im...

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Autores principales: Dries, Ruben, Zhu, Qian, Dong, Rui, Eng, Chee-Huat Linus, Li, Huipeng, Liu, Kan, Fu, Yuntian, Zhao, Tianxiao, Sarkar, Arpan, Bao, Feng, George, Rani E., Pierson, Nico, Cai, Long, Yuan, Guo-Cheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Method
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7938609/
https://www.ncbi.nlm.nih.gov/pubmed/33685491
http://dx.doi.org/10.1186/s13059-021-02286-2
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author Dries, Ruben
Zhu, Qian
Dong, Rui
Eng, Chee-Huat Linus
Li, Huipeng
Liu, Kan
Fu, Yuntian
Zhao, Tianxiao
Sarkar, Arpan
Bao, Feng
George, Rani E.
Pierson, Nico
Cai, Long
Yuan, Guo-Cheng
author_facet Dries, Ruben
Zhu, Qian
Dong, Rui
Eng, Chee-Huat Linus
Li, Huipeng
Liu, Kan
Fu, Yuntian
Zhao, Tianxiao
Sarkar, Arpan
Bao, Feng
George, Rani E.
Pierson, Nico
Cai, Long
Yuan, Guo-Cheng
author_sort Dries, Ruben
collection PubMed
description Spatial transcriptomic and proteomic technologies have provided new opportunities to investigate cells in their native microenvironment. Here we present Giotto, a comprehensive and open-source toolbox for spatial data analysis and visualization. The analysis module provides end-to-end analysis by implementing a wide range of algorithms for characterizing tissue composition, spatial expression patterns, and cellular interactions. Furthermore, single-cell RNAseq data can be integrated for spatial cell-type enrichment analysis. The visualization module allows users to interactively visualize analysis outputs and imaging features. To demonstrate its general applicability, we apply Giotto to a wide range of datasets encompassing diverse technologies and platforms. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-021-02286-2.
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spelling pubmed-79386092021-03-09 Giotto: a toolbox for integrative analysis and visualization of spatial expression data Dries, Ruben Zhu, Qian Dong, Rui Eng, Chee-Huat Linus Li, Huipeng Liu, Kan Fu, Yuntian Zhao, Tianxiao Sarkar, Arpan Bao, Feng George, Rani E. Pierson, Nico Cai, Long Yuan, Guo-Cheng Genome Biol Method Spatial transcriptomic and proteomic technologies have provided new opportunities to investigate cells in their native microenvironment. Here we present Giotto, a comprehensive and open-source toolbox for spatial data analysis and visualization. The analysis module provides end-to-end analysis by implementing a wide range of algorithms for characterizing tissue composition, spatial expression patterns, and cellular interactions. Furthermore, single-cell RNAseq data can be integrated for spatial cell-type enrichment analysis. The visualization module allows users to interactively visualize analysis outputs and imaging features. To demonstrate its general applicability, we apply Giotto to a wide range of datasets encompassing diverse technologies and platforms. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-021-02286-2. BioMed Central 2021-03-08 /pmc/articles/PMC7938609/ /pubmed/33685491 http://dx.doi.org/10.1186/s13059-021-02286-2 Text en © The Author(s) 2021 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/. The Creative Commons Public Domain Dedication waiver (http://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 Method
Dries, Ruben
Zhu, Qian
Dong, Rui
Eng, Chee-Huat Linus
Li, Huipeng
Liu, Kan
Fu, Yuntian
Zhao, Tianxiao
Sarkar, Arpan
Bao, Feng
George, Rani E.
Pierson, Nico
Cai, Long
Yuan, Guo-Cheng
Giotto: a toolbox for integrative analysis and visualization of spatial expression data
title Giotto: a toolbox for integrative analysis and visualization of spatial expression data
title_full Giotto: a toolbox for integrative analysis and visualization of spatial expression data
title_fullStr Giotto: a toolbox for integrative analysis and visualization of spatial expression data
title_full_unstemmed Giotto: a toolbox for integrative analysis and visualization of spatial expression data
title_short Giotto: a toolbox for integrative analysis and visualization of spatial expression data
title_sort giotto: a toolbox for integrative analysis and visualization of spatial expression data
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7938609/
https://www.ncbi.nlm.nih.gov/pubmed/33685491
http://dx.doi.org/10.1186/s13059-021-02286-2
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