RIPPLE (Replicate-Aware Inference of Paracrine Profiles via Likelihood Estimation), an R package that takes a query cell type and scans all other cell types for genes whose expression varies with distance to it, delivers ranked, cell-type-resolved paracrine candidates for experimental follow-up.
Cellular transcriptional states are shaped by local tissue context, yet quantifying how cellular gene expression varies with proximity to different cell types remains challenging. Cell-resolved spatial transcriptomics data are typically sparse and susceptible to contamination from neighbouring cells through diffusion,...
Elijah Willie, Shreya Rao, J. Ormerod et al.· bioRxiv· 0 citations
Tissue function depends on signals exchanged between cells and the responses they elicit. Yet whether diverse cell-cell interactions in situ form recurrent sender-receiver programs remains un-clear. We present SpiderNet, an interpretable representation-learning framework that discovers such directed programs as a compa...
Jun-Jie Tang, Shao-Heng Liang, Shahul Alam et al.· bioRxiv· 0 citations
This study demonstrates that while no single annotation method is universally optimal, multi-method integration enables the identification of robust multi-layer spatial regulatory programs and provides a more reliable framework for interpreting ST data in complex tumor ecosystems.
Mingke Wu, Yi Ting Zhou, Ding-Jie Xu· Frontiers in Bioinformatics· 0 citations
Cell-cell communication is essential for tissue homeostasis and disease-associated microenvironment remodeling. Spatial transcriptomics enables the study of communication events in situ, but single-cell-resolution inference from spot-based data remains challenging because of uncertain cell-to-spot mapping, limited use...
Cell-cell communication (CCC) is involved in regulating cellular behavior in tissues. Spatial transcriptomics adds local context to gene expression, enabling more biologically grounded CCC inference than single-cell RNA-seq alone. Rapid method development has yielded diverse CCC methods, each addressing distinct biolog...
Zlatka Fischer, Katharina Imkeller, Marcel H. Schulz et al.· Trends in Genetics· 2 citations
Technologies for estimating RNA expression at high throughput, in intact tissue slices and with high spatial resolution (spatial transcriptomics) shed new light on how cells communicate and tissues function. A fundamental step in analyzing data generated by subcellular resolution spatial transcriptomics technologies is...
Can Ergen, Nir Yosef· Nature Methods· 0 citations
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