259-STORIES: Spatial Trajectory Inference
The paper introduces STORIES (SpatioTemporal Omics eneRgIES), a novel computational method for inferring cell fate trajectories from time-series spatial transcriptomics data, which captures gene expression within a tissue's physical context. STORIES is built upon an extension of Optimal Transport theory called Fused Gromov–Wasserstein (FGW) to learn a spatially informed differentiation potential, effectively modeling cellular dynamics on a Waddington-like epigenetic landscape. The method's core innovation is its use of the quadratic FGW term to account for spatial coherence without requiring…
The skinny
The skinny isn't ready yet — notes appear once the transcript is processed.