Ben Raphael, Princeton University

Tissues contain multiple cell types whose spatial arrangement facilitates specific biological functions.  Recent spatial transcriptomics technologies measure spatial variation in gene expression, but these measurements are typically sparse with high rates of missing data.  This talk will describe algorithms to model the latent geometry of individual tissue slices and to integrate measurements from multiple slices.  We apply these algorithms to analyze variation of cell types and gene expression in normal and cancer tissues; reconstruct 3D tissues; and describe spatiotemporal changes in expression during development.

Hybrid URL: https://wse.zoom.us/j/91599586169