Democratizing Discovery in Spatial Transcriptomics Through the Brain Image Library.

About This Grant

ABSTRACT The Brain Image Library (BIL) serves as a central repository for advanced microscopy data, ensuring valuable neuroscience datasets are preserved and shared following FAIR principles. While BIL successfully handles traditional microscopy data, it currently lacks specialized tools for spatial transcriptomics datasets, which present unique computational challenges due to their high dimensionality and complex metadata structures. This project will develop essential computational infrastructure to make spatial transcriptomics data in BIL more accessible and analyzable for the broader neuroscience community. We will implement four key components: (1) standardization of data submission and storage using the community-supported Spatialdata format, enabling efficient handling of large-scale molecular data with coordinate system transformations and alignment capabilities, (2) development of an intuitive browser-based visualization system that allows researchers to explore gene expression patterns through interactive scatter plots and maps with density-based rendering, (3) creation of a natural language search interface leveraging Large Language Models for complex queries across molecular and anatomical parameters, and (4) integration of foundational models for automated cell type annotation and metadata generation. By standardizing data organization and providing intuitive exploration tools, this work will maximize the reuse potential of these valuable datasets and lay the groundwork for future cross-modality analyses that combine molecular and imaging data to generate new biological insights.