FUSION: a web-based application for in-depth exploration of multi-omics data with brightfield histology
Spatial technologies examining the cell and tissue microenvironment at near single-cell resolution are revealing important molecular insights. However, few tools enable integrated, interactive analysis of spatial-omics with tissue morphology in the same functional tissue unit. Here, we present FUSION (Functional Unit State Identification in Whole Slide Images), a web-based platform for visualizing and analyzing spatial-omics data with high-resolution histology. FUSION provides workflows for assessing cell compositions, quantitative morphometrics, and comparative tissue analyses. We demonstrate applicability across spatial assays, including 10x Visium, Visium HD, 10x Xenium, Cell DIVE, and PhenoCycler, applied to healthy and diseased tissues from kidney, small intestine, lung, and skin in the Human BioMolecular Atlas Program. FUSION is cloud-based, open-source, and accessible at https://fusion.hubmapconsortium.org/ , hosting over 50 paired datasets and tutorials. In a series of use cases, we show its capacity to distinguish renal glomeruli injury states, quantify morphometric changes, and characterize fibrosis with immune infiltration.
Authors
- Gloria Pryhuber (ORCID: https://orcid.org/0000-0002-9185-3994)
- Arivarasan Karunamurthy (ORCID: https://orcid.org/0000-0002-5739-4923)
- Jessica M. Ray (ORCID: https://orcid.org/0000-0003-3410-1507)
- Jeffrey M. Purkerson (ORCID: https://orcid.org/0000-0001-7636-4992)
- Laura Barisoni (ORCID: https://orcid.org/0000-0003-0848-9683)
- Yulia A. Strekalova (ORCID: https://orcid.org/0000-0002-6060-1233)
- Ricardo Melo Ferreira (ORCID: https://orcid.org/0000-0003-2063-9744)
- Avi Z. Rosenberg (ORCID: https://orcid.org/0000-0003-2356-950X)
- Pinaki Sarder (ORCID: https://orcid.org/0000-0003-2450-5233)
- David Manthey (ORCID: https://orcid.org/0000-0002-4580-8770)
- Samuel Border (ORCID: https://orcid.org/0000-0002-8806-6965)
- John W. Hickey (ORCID: https://orcid.org/0000-0001-9961-7673)
- Ying‐Hua Cheng (ORCID: https://orcid.org/0000-0001-7871-8141)
- Michael T. Eadon (ORCID: https://orcid.org/0000-0003-3066-2876)
- Sanjay R. Jain (ORCID: https://orcid.org/0000-0003-2804-127X)
- Bei Wei (ORCID: https://orcid.org/0000-0003-1516-8802)
- Juexin Wang (ORCID: https://orcid.org/0000-0002-2260-4310)
- Fiona Ginty (ORCID: https://orcid.org/0000-0001-6638-683X)
- Nicholas Lucarelli (ORCID: https://orcid.org/0000-0002-5454-7074)
- Suhas Katari Chaluva Kumar
- Jeffrey B. Hodgin (ORCID: https://orcid.org/0000-0003-0534-3048)
- Tarek M. El‐Achkar (ORCID: https://orcid.org/0000-0003-4645-3614)
- Sayat Mimar
- John E. Tomaszewski
- Anindya S. Paul
- Mauminah Raina
Institutions
- Johns Hopkins University (US)
- University of Pittsburgh (US)
- Duke University (US)
- General Electric (Spain) (ES)
- Washington University in St. Louis (US)
- University of Michigan (US)
- Johns Hopkins Medicine (US)
- University of Florida Health (US)
- Indianapolis Zoo (US)
- University of Florida (US)
- Healthcare Technology Innovation Centre (IN)
- Richard L. Roudebush VA Medical Center (US)
- Stanford Medicine (US)
- Indiana University School of Medicine
- University of Rochester (US)
- Indiana University – Purdue University Indianapolis (US)
- University at Buffalo, State University of New York (US)
- Kitware (United States) (US)
Publication Details
- Journal
- Nature Communications
- Published
- 2025-09-25
- DOI
- https://doi.org/10.1038/s41467-025-63050-9
- Citations
- 1
- Primary Topic
- Bioinformatics and Genomic Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.81
Funders
- National Institutes of Health
- National Institute of Diabetes and Digestive and Kidney Diseases