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SpaCcLink: exploring downstream signaling regulations with graph attention network for systematic inference of
Jingtao Liu1, Litian Ma1, Fen Ju2
1School of Computer Science and Technology, Xidian University, Xi'an, 710071, Shaanxi, China.
Background:
Cellular communication is vital for the proper functioning of multicellular organisms. A comprehensive analysis of cellular communication demands the consideration not only of the binding between ligands and receptors but also of a series of downstream signal transduction reactions within cells. Thanks to the advancements in spatial transcriptomics technology, we are now able to better decipher the process of cellular communication within the cellular microenvironment. Nevertheless, the majority of existing spatial cell-cell communication algorithms fail to take into account the downstream signals within cells.
Results:
In this study, we put forward SpaCcLink, a cell-cell communication analysis method that takes into account the downstream influence of individual receptors within cells and systematically investigates the spatial patterns of communication as well as downstream signal networks. Analyses conducted on real datasets derived from humans and mice have demonstrated that SpaCcLink can help in identifying more relevant ligands and receptors, thereby enabling us to systematically decode the downstream genes and signaling pathways that are influenced by cell-cell communication. Comparisons with other methods suggest that SpaCcLink can identify downstream genes that are more closely associated with biological processes and can also discover reliable ligand-receptor relationships.
Conclusions:
By means of SpaCcLink, a more profound and all-encompassing comprehension of the mechanisms underlying cellular communication can be achieved, which in turn promotes and deepens our understanding of the intricate complexity within organisms.
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