Fig. 2

Spatial spot deconvolution using scRNAseq. Overview of the deconvolution of spatial spots. First, scRNAseq data and spatial data are collected from the same or similar tissue. Second, scRNAseq data and spatial transcriptomics are then fed to three different deconvolution algorithms: Cell2Location, Seurat, and CellTrek. Cell2Location uses a Bayesian model to decompose the spatial expression count matrix into cell type signatures. Seurat employs bulk gene expression deconvolution based on a single-cell reference. CellTrek maps single cells to spatial locations. Finally, prediction results of the cell type abundance at each spatial spot are generated from the three algorithms