Fig. 4

Evaluation of GraphPCA on murine liver data generated by 10X Visium. a An anatomic reference atlas displays the structure of the murine liver lobule area. b Manual annotation provided by the original study. c Spatial domains detected by GraphPCA. d Visualization of spatial domains identified by SpaGCN, STAGATE, and SpatialPCA. The clustering results of PCA, NMF, BayesSpace, and DR-SC are shown in Additional file 1: Fig. S28a. e Barplots illustrating spatial domain detection ARI by different methods on the murine liver data. f Expression of zonation marker genes identified by GraphPCA in the ROI. g Line plots illustrating expression level of zonation marker genes identified by GraphPCA along the portal–central lobule axis (x-axis) in the ROI. Error bars indicate 95% confidence intervals across each layer spots. h Spatial trajectory and pseudo-time of the ROI based on low-dimensional embeddings obtained by GraphPCA. Trajectories are inferred by Slingshot under default parameters. Arrows point from tissue locations with low pseudo-time to those with high pseudo-time. Color represents different tissue regions