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Modeling intercellular communication in tissues using spatial graphs of cells.


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.

SUBMITTER: Fischer DS 

PROVIDER: S-EPMC10017508 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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Modeling intercellular communication in tissues using spatial graphs of cells.

Fischer David S DS   Schaar Anna C AC   Theis Fabian J FJ  

Nature biotechnology 20221027 3


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. ...[more]

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