Enables Seamless Overlay of Histology and Spatial Transcriptomics Data to Map Cell-Types and States Within Functional Tissue Units
This integrated spatial-omics and histology visualization platform enables seamless overlay of histology and spatial transcriptomics data to map cell-type states within functional tissue units (FTUs). Spatial molecular-omics technologies enable scientists to examine gene expression at specific locations within tissue samples, providing insight into cellular organization in both healthy and diseased regions. Methods such as spatial transcriptomics capture transcriptome data from defined areas of a tissue section, enabling researchers to study molecular activity alongside anatomical structures. The growing adoption of spatial molecular-omics technologies has created a rapidly expanding market. The global spatial-omics market was estimated at approximately $711 million in 2024 and is projected to reach about $1.7 billion by 2030 , reflecting an increasing demand for tools that analyze molecular data in a spatial context.
While significant advancements have increased the achievable spatial resolution of spatial-omics methods, it remains difficult to integrate these results into biological or pathological studies. This is because a variety of analytical workflows for this data were inherited from single-cell analyses and often do not fully leverage the “spatial” component of spatial-omics assays. Furthermore, there are many possible scales that researchers may be targeting depending on their subject of interest. For example, in most pathology studies, the smallest units of interest are tissues and not individual cells. These tissues may be composed of a highly variable number and arrangement of cells, requiring specialized methods for integration.
Researchers at the University of Florida developed Functional Unit State Identification (FUSION), a software platform that integrates conventional histology and multiplexed immunofluorescence images with spatial transcriptomics data to map gene expression patterns, cell types, and cell states within FTUs. The platform was created through collaborative work involving computational microscopy, kidney anatomy, and molecular data analysis experts, organized in consortia including the Human Biomolecular Atlas Program (HuBMAP) and the Kidney Precision Medicine Project (KPMP). The focus of FUSION is on “interactive analysis,” which we define as analytical steps that require or are enhanced by dynamic visualization and interaction with data. FUSION allows users to explore whole-slide histology images while simultaneously viewing associated molecular and cellular information. Interactive visualization features include interactive annotation and spatial aggregation, plotting of per-structure properties (cells, tissues, new regions of interest, etc.), and creation of labeled datasets for hypothesis generation and data exploration.
Application
Software platform for integrating spatial transcriptomics with whole-slide histology images to analyze functional tissue units and their associated cellular and molecular characteristics
Advantages
- Integrates histology with spatial transcriptomics, combining morphology and molecular signals
- Enables users to define custom regions of interest, facilitating targeted gene-signature analysis
- Provides interactive visualizations of cell type composition and cell state distributions, delivering instant visual insight into cellular makeup
- Supports clustering of functional tissue units, revealing structural or molecular similarities and potential outliers
- Allows researchers to upload their own datasets, enabling personalized comparative studies
Technology
FUSION is a software platform that combines spatial transcriptomics measurements with computational segmentation and morphometric feature-extraction pipelines within an interactive visualization environment for whole-slide histology images. Spatial operations in FUSION are facilitated using a combination of custom workflows and established geographic information systems (GIS) libraries (shapely, geopandas, etc.) in Python. Through a user-friendly API, users can design customized dashboards for interactive analysis of spatial-omics data in both a web browser and a Jupyter Notebook. Built-in components in FUSION include plotting, overlay, labeling, and visualization components, which are extensions to React/Plotly components available through dash, dash-extensions, and other open-source component libraries. Cloud integration has been facilitated through Digital Slide Archive (DSA, Kitware), enabling users to set up custom visualizations of data stored in the cloud and run resource-intensive workflows remotely (through Slicer CLI plugins). A development version is already hosted on Amazon Web Services, offering a scalable, cloud-native environment for users.
Brochure
