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Talk Title:

Comparative spatial omics analysis across length scales

Abstract:

Spatially resolved omics technologies provide molecular profiling of cells while preserving their organization within tissues. Such technologies provide the opportunity to evaluate spatial molecular comparisons across healthy versus diseased tissues. In this talk, I will highlight two tools my lab has recently developed for such comparative spatial omics analysis. First, for structurally similar tissues, we developed STalign to enable structural alignment within and across spatial transcriptomic technologies using diffeomorphic metric mapping. As such, STalign enables comparing molecular and cell-type compositions at aligned structurally-matched spatial locations across samples. I will demonstrate how we applied STalign to align ST datasets within and across technologies as well as to align ST datasets to a 3D common coordinate framework. I will highlight how STalign achieves high gene expression and cell-type correspondence across matched spatial locations that is significantly improved over manual and landmark-based affine alignments. Second, we developed CRAWDAD to quantify cell-type spatial relationships across length scales to advance our understanding of the association between cell-type organization and tissue function. I will highlight the utility of such multi-scale characterization on simulated data, recapitulate expected cell-type spatial relationships in tissues such as the mouse brain and embryo, and delineate functionally relevant spatial-defined cell-type subsets in the human spleen.