SOTIP is a versatile method for microenvironment modeling with spatial omics data.
Nat Commun
; 13(1): 7330, 2022 11 28.
Article
em En
| MEDLINE
| ID: mdl-36443314
ABSTRACT
The rapidly developing spatial omics generated datasets with diverse scales and modalities. However, most existing methods focus on modeling dynamics of single cells while ignore microenvironments (MEs). Here we present SOTIP (Spatial Omics mulTIPle-task analysis), a versatile method incorporating MEs and their interrelationships into a unified graph. Based on this graph, spatial heterogeneity quantification, spatial domain identification, differential microenvironment analysis, and other downstream tasks can be performed. We validate each module's accuracy, robustness, scalability and interpretability on various spatial omics datasets. In two independent mouse cerebral cortex spatial transcriptomics datasets, we reveal a gradient spatial heterogeneity pattern strongly correlated with the cortical depth. In human triple-negative breast cancer spatial proteomics datasets, we identify molecular polarizations and MEs associated with different patient survivals. Overall, by modeling biologically explainable MEs, SOTIP outperforms state-of-art methods and provides some perspectives for spatial omics data exploration and interpretation.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Voo Espacial
/
Córtex Cerebral
Idioma:
En
Ano de publicação:
2022
Tipo de documento:
Article