Modeling intercellular communication in tissues using spatial graphs of cells
David S Fischer1,2, Anna C Schaar1,3, Fabian J Theis4,5,6
1Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany.
Nature Biotechnology
|October 27, 2022
Abstract:
Models of intercellular communication in tissues are based on molecular profiles of dissociated cells, are limited to receptor-ligand signaling and ignore spatial proximity in situ. We present node-centric expression modeling, a method based on graph neural networks that estimates the effects of niche composition on gene expression in an unbiased manner from spatial molecular profiling data. We recover signatures of molecular processes known to underlie cell communication.
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