ArticleGenome biology2024
StaVia: spatially and temporally aware cartography with higher-order random walks for cell atlases.
Article in Genome biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- MultistageOT: Multistage optimal transport infers trajectories from a snapshot of single-cell data.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- High-Dimensional Single-Cell Analysis Reveals Coordinated Age-Dependent Neuroinflammatory Microglia-T cell Circuits in the Brain.bioRxiv : the preprint server for biology · 2025Article
- Generalizable morphological profiling of cells by interpretable unsupervised learning.Nature communications · 2025Article
- STIFT: spatiotemporal transcriptomics integration through spatially informed multi-timepoint bridging.Briefings in bioinformatics · 2025Article
- Article
- Identifying Myeloid-Derived Suppressor Cells and Lipocalin-2 as Therapeutic Targets for Intervertebral Disc Degeneration.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Oligodendroglia vulnerability in the human dorsal striatum in Parkinson's disease.Acta neuropathologica · 2025Article
- Optimized inner ear organoids for efficient hair cell generation and ototoxicity response modeling.Science China. Life sciences · 2025Article
- Article
- Single-cell genomics and spatial transcriptomics in islet transplantation for diabetes treatment: advancing towards personalized therapies.Frontiers in immunology · 2025Review
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Single-cell atlases pose daunting computational challenges pertaining to the integration of spatial and temporal information and the visualization of trajectories across large atlases. We introduce StaVia, a computational framework that synergizes multi-faceted single-cell data with higher-order random walks that leverage the memory of cells' past states, fused with a cartographic Atlas View that offers intuitive graph visualization. This spatially aware cartography captures relationships between cell populations based on their spatial location as well as their gene expression and developmental stage. We demonstrate this using zebrafish gastrulation data, underscoring its potential to dissect complex biological landscapes in both spatial and temporal contexts.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.