The inference of cell–cell communication (CCC) is crucial for a better understanding of complex cellular dynamics and regulatory mechanisms in biological systems. However, accurately inferring spatial CCCs at single-cell resolution remains a significant
Spatially resolved transcriptomics provides genetic information in space toward elucidation of the spatial architecture in intact organs and the spatially resolved cell-cell communications mediating tissue homeostasis, development, and disease. To facili
The lack of information on the actual spatial location leads us to speculate on the strength of cellular communication only through quantitative analysis, so we need to combine scRNA-seq data and spatial transcriptome data to elucidate the landscape of CCCs in the future. Our study underscores ...
Knowledge-graph-based cell-cell communication inference for spatially resolved transcriptomic data knowledge-graph single-cell spatial-data-analysis spatial-transcriptomics graph-network cell-cell-interaction cell-cell-communication ligand-receptor-interaction spatially-resolved-transcriptomics Updated Nov 8, 2024...
Deciphering cell-cell communication from spatially resolved transcriptomic data at single-cell resolution with subgraph-based attentional graph neural network - JiangBioLab/DeepTalk
often exhibiting significant curvature within a single organelle to enable their parallel alignment with cristae of the neighboring mitochondria (Figure 4). Information about the spatial orientation or mitochondrialultrastructureis thus exchanged across mitochondria. IMJs and trans-mitochondrial cristae alignme...
The spatial organization of communities provides organisms with advantages for growth and adaptation in fluctuating environmental conditions.doi:10.1007/978-1-4939-1402-9_4James Q. BoedickerKatie BrennerDouglas B. WeibelSpringer New York
Evaluation results in the mouse cortex dataset.aSpatial cell type annotation result of mouse cortex dataset’s ST data. Color indicates the spot’s cell type.bThe dot plot of tools’ average distance enrichment scores (DES), sorted by the DESs.cThe dot plots of tools’ average relative accur...
where the cell proximity is determined by the ligand–receptor interaction strength. Therefore, CSOmap can reconstruct cell spatial organizationsde novofrom scRNA-seq data. Similarly, NovoSpaRc[225]can also perform spatial reconstruction, although by expression profile similarity instead of interaction stren...
To characterize cell-cell communication networks, we used CellPhoneDB54, allowing to integrate a repository of ligands, receptors, heteromeric complexes, and their interactions, to infer crosstalk pairs, especially spatial-dependent intra-cluster ligand-receptor complexes (Fig. 6f). Considering spatial di...