SEAM is a spatial single nuclear metabolomics method for dissecting tissue microenvironment - Yuan, Zhiyuan; Zhou, Qiming; Cai, Lesi; Pan, Lin; Sun, Weiliang; Qumu, Shiwei; Yu, Si; Feng, Jiaxin; Zhao, Hansen; Zheng, Yongchang; Shi, Minglei; Li, Shao; et al. (Nature methods, 2021)
Keywords: 631/114/2391; 631/1647/1407/1555; 631/61/320; Algorithms; Animals; Bioinformatics; Biological Microscopy; Biological research; Biological Techniques; Biology, Experimental; Biomedical and Life Sciences; Biomedical Engineering/Biotechnology; Cellular Microenvironment; Clustering; Composition; Computational Biology - methods; Computer applications; Fibrosis; Hepatocytes; Hepatocytes - physiology; Heterogeneity; Histology; Humans; Life Sciences; Liver; Liver - cytology; Liver - physiology; Liver Cirrhosis - metabolism; Mass spectrometry; Mass spectroscopy; Metabolism; Metabolomics; Metabolomics - methods; Methods; Mice; Microenvironments; Proteomics; Reproducibility of Results; Scientific imaging; Secondary ion mass spectrometry; Single Molecule Imaging; Spectroscopy; Subpopulations; Tissues; Transcriptome; Zonation; China