SpatialData : an open and universal data framework for spatial omics
- Author
- Luca Marconato, Giovanni Palla, Kevin A. Yamauchi, Isaac Virshup, Elyas Heidari, Tim Treis, Wouter-Michiel Vierdag, Marcella Toth, Sonja Stockhaus, Rahul B. Shrestha, Benjamin Rombaut (UGent) , Lotte Pollaris (UGent) , Laurens Lehner, Harald Voehringer, Ilia Kats, Yvan Saeys (UGent) , Sinem K. Saka, Wolfgang Huber, Moritz Gerstung, Josh Moore, Fabian J. Theis and Oliver Stegle
- Organization
- Project
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- Unravelling cellular heterogeneity and dynamics in normal and malignant hematopoiesis using singlecell bioinformatics
- Interpretable models for integrative single-cell spatial transcriptomics
- Cell-cell cOmmuNicaTion As a driver of Cancer cell state identiTy - Decoding the impact of cell-cell communications on the identity of tumor states in skin cancers
- Single-cell SPACE, the next frontier
- Onderzoeksprogramma Artificiële Intelligentie - 2023
- Abstract
- Spatially resolved omics technologies are transforming our understanding of biological tissues. However, the handling of uni- and multimodal spatial omics datasets remains a challenge owing to large data volumes, heterogeneity of data types and the lack of flexible, spatially aware data structures. Here we introduce SpatialData, a framework that establishes a unified and extensible multiplatform file-format, lazy representation of larger-than-memory data, transformations and alignment to common coordinate systems. SpatialData facilitates spatial annotations and cross-modal aggregation and analysis, the utility of which is illustrated in the context of multiple vignettes, including integrative analysis on a multimodal Xenium and Visium breast cancer study. SpatialData is a user-friendly computational framework for exploring, analyzing, annotating, aligning and storing spatial omics data that can seamlessly handle large multimodal datasets.
- Keywords
- SINGLE-CELL
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01HY3FM5241PC97AF2F5B5VZQC
- MLA
- Marconato, Luca, et al. “SpatialData : An Open and Universal Data Framework for Spatial Omics.” NATURE METHODS, vol. 22, no. 1, 2025, pp. 58–62, doi:10.1038/s41592-024-02212-x.
- APA
- Marconato, L., Palla, G., Yamauchi, K. A., Virshup, I., Heidari, E., Treis, T., … Stegle, O. (2025). SpatialData : an open and universal data framework for spatial omics. NATURE METHODS, 22(1), 58–62. https://doi.org/10.1038/s41592-024-02212-x
- Chicago author-date
- Marconato, Luca, Giovanni Palla, Kevin A. Yamauchi, Isaac Virshup, Elyas Heidari, Tim Treis, Wouter-Michiel Vierdag, et al. 2025. “SpatialData : An Open and Universal Data Framework for Spatial Omics.” NATURE METHODS 22 (1): 58–62. https://doi.org/10.1038/s41592-024-02212-x.
- Chicago author-date (all authors)
- Marconato, Luca, Giovanni Palla, Kevin A. Yamauchi, Isaac Virshup, Elyas Heidari, Tim Treis, Wouter-Michiel Vierdag, Marcella Toth, Sonja Stockhaus, Rahul B. Shrestha, Benjamin Rombaut, Lotte Pollaris, Laurens Lehner, Harald Voehringer, Ilia Kats, Yvan Saeys, Sinem K. Saka, Wolfgang Huber, Moritz Gerstung, Josh Moore, Fabian J. Theis, and Oliver Stegle. 2025. “SpatialData : An Open and Universal Data Framework for Spatial Omics.” NATURE METHODS 22 (1): 58–62. doi:10.1038/s41592-024-02212-x.
- Vancouver
- 1.Marconato L, Palla G, Yamauchi KA, Virshup I, Heidari E, Treis T, et al. SpatialData : an open and universal data framework for spatial omics. NATURE METHODS. 2025;22(1):58–62.
- IEEE
- [1]L. Marconato et al., “SpatialData : an open and universal data framework for spatial omics,” NATURE METHODS, vol. 22, no. 1, pp. 58–62, 2025.
@article{01HY3FM5241PC97AF2F5B5VZQC,
abstract = {{Spatially resolved omics technologies are transforming our understanding of biological tissues. However, the handling of uni- and multimodal spatial omics datasets remains a challenge owing to large data volumes, heterogeneity of data types and the lack of flexible, spatially aware data structures. Here we introduce SpatialData, a framework that establishes a unified and extensible multiplatform file-format, lazy representation of larger-than-memory data, transformations and alignment to common coordinate systems. SpatialData facilitates spatial annotations and cross-modal aggregation and analysis, the utility of which is illustrated in the context of multiple vignettes, including integrative analysis on a multimodal Xenium and Visium breast cancer study.
SpatialData is a user-friendly computational framework for exploring, analyzing, annotating, aligning and storing spatial omics data that can seamlessly handle large multimodal datasets.}},
author = {{Marconato, Luca and Palla, Giovanni and Yamauchi, Kevin A. and Virshup, Isaac and Heidari, Elyas and Treis, Tim and Vierdag, Wouter-Michiel and Toth, Marcella and Stockhaus, Sonja and Shrestha, Rahul B. and Rombaut, Benjamin and Pollaris, Lotte and Lehner, Laurens and Voehringer, Harald and Kats, Ilia and Saeys, Yvan and Saka, Sinem K. and Huber, Wolfgang and Gerstung, Moritz and Moore, Josh and Theis, Fabian J. and Stegle, Oliver}},
issn = {{1548-7091}},
journal = {{NATURE METHODS}},
keywords = {{SINGLE-CELL}},
language = {{eng}},
number = {{1}},
pages = {{58--62}},
title = {{SpatialData : an open and universal data framework for spatial omics}},
url = {{http://doi.org/10.1038/s41592-024-02212-x}},
volume = {{22}},
year = {{2025}},
}
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