ArticleNature biotechnology2024
Stabilized mosaic single-cell data integration using unshared 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 69 papers.
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Who cites it
69 citing papers in PubMed.
- Longitudinal alignments and syntheses of multimodal clinical data for personalized medicine with the PULSE framework.Nature computational science · 2026Article
- MultiSpaceNet: graph-based joint representation learning for paired spatial transcriptome-proteome data.Bioinformatics (Oxford, England) · 2026Article
- Spatial multi-omics imputation and embedding with SpaMIE.Cell reports methods · 2026Article
- A deep learning architecture for combining and imputing heterogeneous metabolomics datasets.BMC bioinformatics · 2026Article
- CTMAP: an adversarial cross-modal learning framework for accurate and robust cell-type annotation in single-cell resolution spatial transcriptomics.Briefings in bioinformatics · 2026Article
- SpaMode: A Broadly Applicable Framework for Deciphering Spatial Multi-Omics Using Multimodal Mixture of Disentangled Experts.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Integrating single-cell RNA sequencing with multi-omics to decode disease microenvironments.Molecular biology reports · 2026Review
- MIND: multimodal integration with neighbourhood-aware distributions.Nature communications · 2026Article
- 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
- Mosaic integration of spatial multi-omics with SpaMosaic.Nature genetics · 2026Article
- Transitive prediction of small-molecule function through alignment of high-content screening resources.Nature biotechnology · 2026Article
- A comprehensive benchmarking study on computational tools for cross-omics label transfer from single-cell RNA to ATAC data.G3 (Bethesda, Md.) · 2026Article
- SMART: spatial multi-omic aggregation using graph neural networks and metric learning.Nature communications · 2026Article
- Dissecting spatial patterning and signaling with directional diffusion in spatial multi-omics.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Toward Computationally Complete Spatial Omics.bioRxiv : the preprint server for biology · 2026Article
- Longitudinal peripheral blood multi-omic profiling in seropositive individuals identifies immune endotypes and predictive models for future rheumatoid arthritis conversion.medRxiv : the preprint server for health sciences · 2026Article
- Decoding Alzheimer's Disease One Cell Class at a Time.Cellular and molecular neurobiology · 2026Review
- Bridging unpaired single-cell multimodal data for integrative analyses with SuperMap.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- A hitchhiker's guide to single-cell epigenomics: Methods and applications for cancer research.International journal of cancer · 2026Review
9 more citing papers are in PubMed but not listed here.
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3 authors.
Funding
Abstract
Currently available single-cell omics technologies capture many unique features with different biological information content. Data integration aims to place cells, captured with different technologies, onto a common embedding to facilitate downstream analytical tasks. Current horizontal data integration techniques use a set of common features, thereby ignoring non-overlapping features and losing information. Here we introduce StabMap, a mosaic data integration technique that stabilizes mapping of single-cell data by exploiting the non-overlapping features. StabMap first infers a mosaic data topology based on shared features, then projects all cells onto supervised or unsupervised reference coordinates by traversing shortest paths along the topology. We show that StabMap performs well in various simulation contexts, facilitates 'multi-hop' mosaic data integration where some datasets do not share any features and enables the use of spatial gene expression features for mapping dissociated single-cell data onto a spatial transcriptomic reference.
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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.