Framework for Interactive Exploration of Spatial Transcriptomics Applications - FIESTA

Spatial transcriptomics is a family of techniques that help scientists understand not only how much specific genes are expressed within a sample, but also precisely where that activity occurs within cells and tissues. Understanding gene expression at this high level of spatial detail is crucial to how living systems develop, respond to disease, and adapt to environmental changes. Combining data from multiple spatial transcriptomics technologies at scale will enable comprehensive reference data resources, fueling new scientific discovery. Spatial transcriptomics has a high barrier to entry due to the need for expensive equipment and advanced computational skills to process and analyse data. Making these datasets widely accessible in user-friendly formats is essential for democratising the field and enabling researchers across disciplines to benefit without costly resources. As the field has grown, the variety and complexity of its methods and data have increased significantly, creating an urgent need for tools to simplify the visualisation and exploration of these datasets. Uniquely, EMBL-EBI provides expertise in the two data domains crucial to effective management of spatial transcriptomics data - gene expression and biological imaging. This strength is reflected in two core resources, which working together can provide a solution to the challenges in analysing and visualising spatial transcriptomics data at scale: Expression Atlas, providing the data on the gene expression and BioImage Archive providing the image data. This project will develop a prototype platform that integrates spatial transcriptomics data from both image and sequencing based technologies into the existing Expression Atlas resource. Publicly available datasets will be used to build this platform, with standardised pipelines transforming data from many different techniques into a unified representation. This common format will build on existing work by the spatial transcriptomics community to standardise data and metadata formats. The platform will be designed to support future scaling and aggregation of higher data volumes and new data types. Once developed, the platform will allow scientists to interactively explore the expression of genes in their spatial context. They will be able to zoom into regions of interest and query by gene, cell type, tissues, organisms, and other features. This will enable user-friendly exploration of genes of interest, comparative analysis, hypothesis generation, and creation of publication-ready visualisations, making it an essential resource for both exploratory research and communication of findings. The design and development of this prototype will be possible due to the unique nature of EMBL-EBI, which provides world-leading expertise in management and analysis of both imaging and expression data, and the consequent connectivity of the data resources housed there. All output from this project - including the platform, code, standardised datasets, and documentation - will be made freely available to the research community. To encourage widespread adoption, the project team will also provide training materials, tutorials, and ongoing support. By addressing critical gaps in the analysis and visualisation of spatial transcriptomics data, this project will establish a foundation for future large-scale reference datasets to drive innovation and discovery, while lowering barriers for researchers worldwide to access and utilise these powerful data resources.