Extended Data Fig. 9. Imputation parameter optimization and performance evaluation.

a, Cumulative curves of the imputation performance scores across STARmap PLUS genes in the intermediate mapping using different numbers of scRNA-seq cell nearest neighbors. The upper-left inset shows a zoomed-in view of the rectangular region highlighted in the bottom right. The performance score of a gene was calculated as the Pearson’s correlation coefficient (PCC, across cells) between its imputed values and measured STARmap PLUS expression level. b, Scatter plots of spatial expression heterogeneity (Moran’s I⁶⁸ of the gene’s spatial expression map) versus gene expression level in the STARmap PLUS datasets (left), and single-cell expression heterogeneity (Moran’s I of scRNA-seq UMAP coloured by the gene’s expression) versus gene expression level in the scRNA-seq atlas¹ (right). Each dot represents a gene and is coloured by the gene’s imputation performance score. n = 1016 genes. c, More examples of the comparison of imputed spatial gene expression with measured expression from STARmap PLUS and Allen Mouse Brain ISH database²³. Each dot represents a cell coloured by the expression level of a specified gene. Scale bar, 0.5 mm. The sample slice numbers were labeled in gray. d,e, Imputed spatial gene expression heatmaps of putative marker genes of the ventral part (d) and the dorsal part (e) of medial habenula and the paired ISH images from the Allen Mouse Brain ISH database²³. Data are provided in the accompanying Source Data file.

Source data