Spatial charting of single cell transcriptomes in tissues

Single cell RNA sequencing (scRNA-seq) methods can profile the transcriptomes of single cells but cannot preserve spatial information. Conversely, spatial transcriptomics (ST) assays can profile spatial regions in tissue sections, but do not have single cell genomic resolution. Here, we developed a computational approach called SChart, that combines these two datasets to achieve single cell spatial mapping of cell types, cell states and continuous phenotypes. We applied SChart to reconstruct cellular spatial structures in existing datasets from normal mouse brain and kidney tissues to validate our approach. We also performed scRNA-seq and ST experiments on two ductal carcinoma in situ (DCIS) tissues and applied SChart to identify subclones that were restricted to different ducts, and specific T cell states adjacent to the tumor areas. Our data shows that SChart can accurately map single cells in diverse tissue types to resolve their spatial organization into cellular neighborhoods and tissue structures.