Efficient and Adaptive Gaussian smoothing applied to high-resolved spatial transcriptomics

EAGS is a smoothing approach for spatial transcriptome data with ultrahigh resolution. Through the principal component information of the profiling of gene expression and the personally identifiable information between cells, it uses a two-factor adaptive smoothing weight mechanism to determine the neighborhood relationship of cells. Then it uses the self-developed smoothing weight formula to calculate the smoothing contribution and recalculate the gene expression of each cell.