Spatial-linked alignment tool (SLAT) for aligning heterogenous slices

Abstract

Spatially resolved omics technologies reveal the spatial organization of cells in various biological systems. Here we propose SLAT (Spatially-Linked Alignment Tool), a graph-based algorithm for efficient and effective alignment of spatial slices. Adopting a graph adversarial matching strategy, SLAT is the first algorithm capable of aligning heterogenous spatial data across distinct technologies and modalities. Systematic benchmarks demonstrate SLAT’s superior precision, robustness, and speed over existing state-of-the-arts. Applications to multiple real-world datasets further show SLAT’s utility in enhancing cell-typing resolution, integrating multiple modalities for regulatory inference, and mapping fine-scale spatial-temporal changes during development. The full SLAT package is available at https://github.com/gao-lab/SLAT.

Spatial omics technologies reveal the organisation of cells in various biological systems. Here, authors propose SLAT, a graph-based algorithm for aligning heterogenous data across technologies, modalities and timepoints, enabling spatiotemporal reconstruction of complex developmental processes.