CorrespondencePublished: 14 August 2026Wenjie Wei ORCID: orcid.org/0000-0003-4105-96931,2,Lounan Li ORCID: orcid.org/0009-0006-9291-728X1,2,Liyang Song ORCID: orcid.org/0009-0003-4424-172X1,2,Wenhao Chen ORCID: orcid.org/0009-0009-7854-71221,2,Kai Wang1,2,Minmin Guo1,2 &…Jian Yang ORCID: orcid.org/0000-0003-2001-24741,2 Nature Genetics (2026) Cite this articleSave articleView saved researchThe emergence of spatial transcriptomics has fundamentally reshaped the understanding of gene expression within intact tissues by enabling molecular profiles to be localized to precise cellular and anatomical contexts1. More recently, three-dimensional spatial transcriptomics (3D-ST) technologies have extended this paradigm beyond isolated tissue sections, allowing cellular organization to be reconstructed across entire tissue volumes2,3,4. This technological shift opens up new opportunities to investigate spatial gradients, long-range cellular interactions and disease-associated architectures5 that are inherently 3D, particularly in complex organs such as the brain6.To address these limitations, we developed SpatialVista (https://yanglab.westlake.edu.cn/spatialvista), a unified visualization ecosystem designed for the integrated exploration of 3D-ST data throughout the entire analytical workflow. SpatialVista provides a shared set of high-performance visualization capabilities accessible through complementary interfaces, enabling consistent exploration of 3D-ST data across every stage of the analytical pipeline (Fig. 1a).This is a preview of subscription content, access via your institutionAccess options Access through your institutionAccess Nature and 54 other Nature Portfolio journalsGet Nature+, our best-value online-access subscription27,99 € / 30 dayscancel any timeLearn moreSubscribe to this journalReceive 12 print issues and online access269,00 € per yearonly 22,42 € per issueLearn moreBuy this articlePurchase on SpringerLinkInstant access to the full article PDF.39,95 €Prices may be subject to local taxes which are calculated during checkoutFig. 1: SpatialVista ecosystem and comparison with representative spatial omics visualization platforms.SubjectsComputational biology and bioinformaticsSoftwareData processingGene expressionCode availabilityThe SpatialVista online browser, desktop application and documentation are freely available at https://yanglab.westlake.edu.cn/spatialvista. The Jupyter/Python widget and source code are available at https://github.com/JianYang-Lab/spatial-vista-py under a BSD 3-Clause license.ReferencesMoses, L. & Pachter, L. Nat. Methods 19, 534–546 (2022).Article CAS PubMed Google Scholar Schott, M. et al. Cell 187, 3953–3972.e26 (2024).Article CAS PubMed Google Scholar Sui, X. et al. Nat. Methods 22, 2574–2584 (2025).Article CAS PubMed Google Scholar Kern, C. et al. Preprint at bioRxiv https://doi.org/10.1101/2025.11.02.686137 (2025).Song, L., Chen, W., Hou, J., Guo, M. & Yang, J. Nature 641, 932–941 (2025).Article CAS PubMed PubMed Central Google Scholar Zhang, M. et al. Nature 624, 343–354 (2023).Article CAS PubMed PubMed Central Google Scholar Keller, M. S. et al. Nat. Methods 22, 63–67 (2025).Article CAS PubMed Google Scholar Solorzano, L., Partel, G. & Wählby, C. Bioinformatics 36, 4363–4365 (2020).Article CAS PubMed PubMed Central Google Scholar CZI Cell Science Program. Nucleic Acids Res. 53, D886–D900 (2025).Qiu, X. et al. Cell 187, 7351–7373.e61 (2024).Article CAS PubMed Google Scholar Sofroniew, N. et al. Zenodo https://doi.org/10.5281/zenodo.20709435 (2026).Wolf, F. A., Angerer, P. & Theis, F. J. Genome Biol. 19, 15 (2018).Article PubMed PubMed Central Google Scholar Download referencesAcknowledgementsWe thank Y. Wang and D. Yi for helpful discussions and the Westlake University High-Performance Computing Center for their assistance in computing. This work was supported by the National Natural Science Foundation of China (32595482, U23A20165), the National Key R&D Program of China (2024YFC3405800, 2024YFC3405802), the “Pioneer” and “Leading Goose” R&D Programs of Zhejiang (2024SSYS0032) and the New Cornerstone Science Foundation.Author informationAuthors and AffiliationsNew Cornerstone Science Laboratory, School of Life Sciences, Westlake University, Hangzhou, ChinaWenjie Wei, Lounan Li, Liyang Song, Wenhao Chen, Kai Wang, Minmin Guo & Jian YangWestlake Laboratory of Life Sciences and Biomedicine, Hangzhou, ChinaWenjie Wei, Lounan Li, Liyang Song, Wenhao Chen, Kai Wang, Minmin Guo & Jian YangAuthorsWenjie WeiView author publicationsSearch author on:PubMed Google ScholarLounan LiView author publicationsSearch author on:PubMed Google ScholarLiyang SongView author publicationsSearch author on:PubMed Google ScholarWenhao ChenView author publicationsSearch author on:PubMed Google ScholarKai WangView author publicationsSearch author on:PubMed Google ScholarMinmin GuoView author publicationsSearch author on:PubMed Google ScholarJian YangView author publicationsSearch author on:PubMed Google ScholarCorresponding authorCorrespondence to Jian Yang.Ethics declarationsCompeting interestsThe authors declare no competing interests.Peer reviewPeer review informationNature Genetics thanks the anonymous reviewers for their contribution to the peer review of this work.Supplementary informationRights and permissionsReprints and permissionsAbout this article