B0183
Title: Integrative and reference-informed spatial domain detection for spatial transcriptomics
Authors: Xiang Zhou - University of Michigan (United States) [presenting]
Abstract: Spatially resolved transcriptomics (SRT) studies are becoming increasingly common and increasingly large, offering unprecedented opportunities to characterize the spatial and functional organization of complex tissues. A computational method is introduced, IRIS, that characterizes the spatial organization of complex tissues through accurate and efficient detection of spatial domains. IRIS uniquely leverage the widespread availability of single-cell RNA-seq data for reference-informed spatial domain detection, integrates multiple SRT tissue slices jointly while explicitly considering correlation both within and across slices, produces biologically interpretable spatial domains, and benefits from multiple algorithmic innovations for highly scalable computation. The advantages of IRIS are demonstrated through an in-depth analysis of six SRT datasets from different technologies across various tissues, species, and spatial resolutions. In these applications, IRIS uncovers the fine-scale structures of brain regions, reveals the spatial heterogeneity of distinct tumour microenvironments, and characterizes the structural changes of the seminiferous tubes in the testis associated with diabetes, all at a speed and accuracy unachievable by existing approaches.
