2022
DOI: 10.1371/journal.pcbi.1010366
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De novo spatiotemporal modelling of cell-type signatures in the developmental human heart using graph convolutional neural networks

Abstract: With the emergence of high throughput single cell techniques, the understanding of the molecular and cellular diversity of mammalian organs have rapidly increased. In order to understand the spatial organization of this diversity, single cell data is often integrated with spatial data to create probabilistic cell maps. However, targeted cell typing approaches relying on existing single cell data achieve incomplete and biased maps that could mask the true diversity present in a tissue slide. Here we applied a d… Show more

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“…In this respect, LAMA3, FGF10, EFNA1, and LGR4 ( Figure 4 C) have been implicated in epithelial-to-mesenchymal transition 57 , 58 , 59 , 60 that may, in the atrial wall of venous origin, contribute to its myocardialization. 41 , 61 , 62 , 63 , 64
Figure 4 Colocalized non-CM cell types with conduit CMs and relative ligand-receptor crosstalk (A) Heatmap showing numbers of L-R interactions between conduit atrial CM clusters and six non-CM clusters. (B) Specific highly expressed L-R crosstalk between conduit and colocalized non-CMs.
…”
Section: Resultsmentioning
confidence: 99%
“…In this respect, LAMA3, FGF10, EFNA1, and LGR4 ( Figure 4 C) have been implicated in epithelial-to-mesenchymal transition 57 , 58 , 59 , 60 that may, in the atrial wall of venous origin, contribute to its myocardialization. 41 , 61 , 62 , 63 , 64
Figure 4 Colocalized non-CM cell types with conduit CMs and relative ligand-receptor crosstalk (A) Heatmap showing numbers of L-R interactions between conduit atrial CM clusters and six non-CM clusters. (B) Specific highly expressed L-R crosstalk between conduit and colocalized non-CMs.
…”
Section: Resultsmentioning
confidence: 99%