Abstract

   Tissues are highly complicated with spatial heterogeneity in gene
   expression. However, the cutting-edge single-cell RNA-seq technology
   eliminates the spatial information of individual cells, which
   contributes to the characterization of cell identities. Herein, we
   propose single-cell spatial position associated co-embeddings
   (scSpace), an integrative method to identify spatially variable cell
   subpopulations by reconstructing cells onto a pseudo-space with spatial
   transcriptome references (Visium, STARmap, Slide-seq, etc.). We