ArticleNature biotechnology2024
Integration of spatial and single-cell data across modalities with weakly linked features.
Article in Nature biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
79 citing papers in PubMed, 87 citations in OpenAlex.
- Near-infrared photochromic miniprotein enables photoacoustic molecular imaging of acute inflammation and intracellular antigens.Nature methods · 2026Article
- 3D multi-omics tumour atlases: from technology to biology and clinical translation.Nature reviews. Cancer · 2026Review
- Unifying multimodal single-cell data with a mixture-of-experts β-variational autoencoder framework.Genome research · 2026Article
- Spatial Proteomics and Epigenomics Reveal Cell Morphology and Epigenetic Gene Regulation in Human Hippocampus.Research square · 2026Article
- Single-cell and single-nucleus transcriptomics of the dorsal root ganglion in neuropathic pain: cell-state remodeling and translational prospects.Journal of translational medicine · 2026Review
- A multimodal, all-optical platform for linking cell identity to metabolic function in intact tissues.Nature methods · 2026Article
- All-optical multimodal mapping of single-cell-type-specific metabolic activities via REDCAT.Nature methods · 2026Article
- Integration of imaging-based and sequencing-based spatial omics mapping on the same tissue section via DBiTplus.Nature methods · 2026Article
- Integrated pan-cancer analysis reveals a cancer-associated fibroblast oxidative stress response signature predicting immunotherapy response and prognosis.Apoptosis : an international journal on programmed cell death · 2026Article
- Same-Slide Spatial Multiomics Integration with IN-DEPTH Reveals Tumor Virus-Linked Spatial Reorganization of the Tumor Microenvironment.Cancer discovery · 2026Article
- ARCADIA reveals spatially dependent transcriptional programs through integration of scRNA-seq and spatial proteomics.Bioinformatics (Oxford, England) · 2026Article
- Spatium: A Protein Language Foundation Model for Spatial Proteomics.bioRxiv : the preprint server for biology · 2026Article
- Unifying multimodal single-cell data with a mixture-of-expertsbioRxiv : the preprint server for biology · 2026Article
- A spatial multi-omics atlas of immunosenescence reveals germinal-center B cell dysfunction in human lymph nodes.Cell press blue · 2026Article
- Investigating Spatial Dynamics in Spatial Omics Data with StarTrail.Journal of the American Statistical Association · 2026Article
- Graph-based contrastive learning enables unified integration and niche transfer across single-cell and spatial multi-omics.Briefings in bioinformatics · 2026Article
- Cellular Morphometric Analysis (CellMorph)-a comprehensive imaging-based tool for quantifying cellular phenotype heterogeneity and dynamics across biological processes.The FEBS journal · 2026Article
- Tumor microenvironment-specific nanomedicine: from biology-driven to multi-omics-guided precision engineering.Journal of hematology & oncology · 2026Review
- Cycle-consistent deep generative modeling unifies cellular states across unpaired spatial and single-cell modalities.bioRxiv : the preprint server for biology · 2026Article
- Robust integration of single-cell datasets with imbalanced modality composition.Nature communications · 2026Article
19 more citing papers are in PubMed but not listed here.
Corrections and comments
- Update of
Authors and funding
10 authors at 6 institutions in 1 country.
Funding
Abstract
Although single-cell and spatial sequencing methods enable simultaneous measurement of more than one biological modality, no technology can capture all modalities within the same cell. For current data integration methods, the feasibility of cross-modal integration relies on the existence of highly correlated, a priori 'linked' features. We describe matching X-modality via fuzzy smoothed embedding (MaxFuse), a cross-modal data integration method that, through iterative coembedding, data smoothing and cell matching, uses all information in each modality to obtain high-quality integration even when features are weakly linked. MaxFuse is modality-agnostic and demonstrates high robustness and accuracy in the weak linkage scenario, achieving 20~70% relative improvement over existing methods under key evaluation metrics on benchmarking datasets. A prototypical example of weak linkage is the integration of spatial proteomic data with single-cell sequencing data. On two example analyses of this type, MaxFuse enabled the spatial consolidation of proteomic, transcriptomic and epigenomic information at single-cell resolution on the same tissue section.
Indexed as
Identifiers
What OpenQuestion holds
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.