Modeling Cell-Cell Interactions from Spatial Molecular Data with Spatial Variance Component Analysis.

ABSTRACT: Technological advances enable assaying multiplexed spatially resolved RNA and protein expression profiling of individual cells, thereby capturing molecular variations in physiological contexts. While these methods are increasingly accessible, computational approaches for studying the interplay of the spatial structure of tissues and cell-cell heterogeneity are only beginning to emerge. Here, we present spatial variance component analysis (SVCA), a computational framework for the analysis of spatial molecular data. SVCA enables quantifying different dimensions of spatial variation and in particular quantifies the effect of cell-cell interactions on gene expression. In a breast cancer Imaging Mass Cytometry dataset, our model yields interpretable spatial variance signatures, which reveal cel

SUBMITTER: Arnol D 

PROVIDER: S-EPMC6899515 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature