SIMVI disentangles intrinsic and spatial-induced cellular states in spatial omics data

• Published in: Nature communications Vol. 16; no. 1; pp. 2990 - 17
• Main Authors: Dong, Mingze, Su, David G., Kluger, Harriet, Fan, Rong, Kluger, Yuval
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 27.03.2025; Nature Publishing Group; Nature Portfolio
• Subjects: 631/114/1305; 631/114/2397; 631/114/2415; 631/114/794; Annotations; B-Lymphocytes - metabolism; Biological activity; Cell Communication; Cellular communication; Computational Biology - methods; Deep Learning; Epigenetics; Gene expression; Germinal Center - cytology; Germinal Center - metabolism; Germinal centers; Humanities and Social Sciences; Humans; Interaction models; Lymphocytes B; Macrophages; Macrophages - metabolism; Melanoma; Melanoma - genetics; Melanoma - pathology; Microenvironments; multidisciplinary; Palatine Tonsil - cytology; Science; Science (multidisciplinary); Single-Cell Analysis - methods; Spatial analysis; Spatial data; Structure-function relationships; Tumor microenvironment; Tumor Microenvironment - genetics; Tumors

Spatial omics technologies enable analysis of gene expression and interaction dynamics in relation to tissue structure and function. However, existing computational methods may not properly distinguish cellular intrinsic variability and intercellular interactions, and may thus fail to reliably captu...