Spatial Transcriptomics

Our lab develops innovative analytical methods to advance the study of spatial transcriptomics, enabling a deeper and more comprehensive understanding of gene expression within intact tissues. Traditional single-cell RNA sequencing, while powerful, often fails to capture key transcriptomic signals—such as those located in neurites, extracellular spaces, or fragile and rare cell types—due to the need for tissue dissociation. To address these limitations, we focus on designing computational frameworks that can identify and recover these overlooked components directly from spatial transcriptomics data. Our approaches allow for the detection of subtle transcriptional patterns, the separation of somatic and non-somatic gene expression, and the characterization of cell types or biological structures that are underrepresented in conventional analyses. We also develop tools to investigate the spatial relationships between individual RNA molecules within cells, uncovering patterns of subcellular organization and potential regulatory interactions. Complementing these computational efforts, we integrate high-resolution imaging technologies that provide nanoscale localization of transcripts, offering unprecedented insight into the spatial dynamics of gene regulation. Together, these analytical advancements enable a more accurate and nuanced interpretation of spatial omics data, with broad applications in neuroscience, cancer biology, and developmental systems.