SEAM is a scalable platform combining high resolution imaging mass spectrometry (IMS) and a series of computational algorithms, that can display multiscale/multicolor tissue tomography together with identification and clustering of single nuclei by their in situ metabolic fingerprints.
This repo provides notebooks for tutorial and demonstration, figure regeneration, method comparison, and spatial transcriptome analysis.
Please cite: Yuan Z, Zhou Q, Cai L, et al. SEAM is a spatial single nuclear metabolomics method for dissecting tissue microenvironment[J]. Nature Methods, 2021, 18(10): 1223-1232.