To adapt the Diff-ST framework to other spatial omics data, such as spatial metabolomics or spatial epigenomics, the model architecture and data processing steps can be modified to accommodate the unique characteristics of these data types and enable a comprehensive understanding of spatial organization and regulation in biological systems.
Spatial Metabolomics: For spatial metabolomics data, which provides information on the spatial distribution of metabolites within tissues, the model can be extended to predict metabolite levels alongside gene expression. By incorporating metabolomic features and designing specific conditioning mechanisms, the model can learn to generate super-resolved spatial metabolomics maps. This integration can offer insights into the metabolic landscape of tissues and their interactions with gene expression patterns.
Spatial Epigenomics: Spatial epigenomics data reveals the epigenetic modifications and regulatory elements present in different spatial locations. By adapting the model to incorporate epigenomic features and capture the spatial relationships between epigenetic markers and gene expression, researchers can uncover the regulatory mechanisms that govern spatial gene expression patterns. This extension can provide a deeper understanding of the epigenetic landscape and its impact on spatial transcriptomics.
Multimodal Fusion: To enable a more comprehensive analysis of spatial omics data, the framework can incorporate multimodal fusion techniques to integrate gene expression, metabolomic profiles, and epigenetic markers. By leveraging fusion strategies such as multimodal attention mechanisms or graph-based fusion, the model can capture the complex interplay between different omics layers and reveal the intricate spatial regulation of biological systems.
By adapting the Diff-ST framework to spatial metabolomics and spatial epigenomics data, researchers can gain a holistic view of the spatial organization and regulation of biological systems, facilitating deeper insights into the molecular mechanisms underlying tissue function and disease processes.