Fig. 1

The workflow of Spall. (1) Data preprocessing: generation of pseudo spots from reference scRNA-seq data and feature selection both on original SRT and scRNA-seq data. (2) Integration and graph construction: data integration followed by graph construction using either KNN or Random Projection Forest, depending on dataset scale. (3) Graph neural network training: implementation of two GATv2 modules and one skip connection module. (4) Downstream analysis: application of decomposition results estimated by Spall to various analytical tasks