ArticleNature methods2022
Identifying temporal and spatial patterns of variation from multimodal data using MEFISTO.
Article in Nature methods, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 120 papers, 2 of them syntheses that pooled it.
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Who cites it
120 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Multi-omics time-series analysis in microbiome research: a systematic review.Briefings in bioinformatics · 2025Pooled it
- Deep learning in single-cell and spatial transcriptomics data analysis: advances and challenges from a data science perspective.Briefings in bioinformatics · 2025Pooled it
- Longitudinal multiomic signatures of ARDS and sepsis inflammatory phenotypes identify pathways associated with mortality.The Journal of clinical investigation · 2026Trial
- Multiomics insights into the effects of prebiotics on physical function and metabolism in adults with obesity and knee osteoarthritis.Gut microbes · 2026Article
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- Alterations of the host-lung microbiome metasystem in systemic inflammatory response syndrome is associated with secondary pneumonia.Cell reports. Medicine · 2026Article
- Omics Approaches in Hantavirus Research: Current Advances, Challenges, and Future Perspectives.Biotech (Basel (Switzerland)) · 2026Review
- Spatial multi-omics imputation and embedding with SpaMIE.Cell reports methods · 2026Article
- Multimodal spatial omics: From data acquisition to computational integration.Patterns (New York, N.Y.) · 2026Review
- Scalable multi-group nonnegative spatial factorization for spatial genomics data with cell-type heterogeneity.bioRxiv : the preprint server for biology · 2026Article
- Interpretable spatial multi-omics data integration and dimensionality reduction with SpaMV.Nature communications · 2026Article
- Innate immune responsiveness predicts enhanced cellular immunity and symptomatic disease after controlled human influenza infection.Nature medicine · 2026Article
- Extracting host-specific developmental signatures from longitudinal microbiome data.PLoS computational biology · 2026Article
- Epigenetic biomarkers in inflammatory bowel diseases-computational challenges and opportunities.Journal of Crohn's & colitis · 2026Review
- Trajectory-guided dimensionality reduction for multi-sample single-cell RNA-seq data reveals biologically relevant sample-level heterogeneity.Bioinformatics (Oxford, England) · 2026Article
- Interpretation, extrapolation and perturbation of single cells.Nature reviews. Genetics · 2026Review
- Redox rhythms promote fitness by modulating ageing-dependent reprogramming.Nature metabolism · 2026Article
- Longitudinal Sparse Single-Omics Factor Analysis for High-Dimensional Blood Biomarkers in Alzheimer's Disease.Statistics in medicine · 2026Article
- Navigating multi-omic integration methods for human microbiome research.Nature microbiology · 2026Review
60 more citing papers are in PubMed but not listed here.
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8 authors.
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Abstract
Factor analysis is a widely used method for dimensionality reduction in genome biology, with applications from personalized health to single-cell biology. Existing factor analysis models assume independence of the observed samples, an assumption that fails in spatio-temporal profiling studies. Here we present MEFISTO, a flexible and versatile toolbox for modeling high-dimensional data when spatial or temporal dependencies between the samples are known. MEFISTO maintains the established benefits of factor analysis for multimodal data, but enables the performance of spatio-temporally informed dimensionality reduction, interpolation, and separation of smooth from non-smooth patterns of variation. Moreover, MEFISTO can integrate multiple related datasets by simultaneously identifying and aligning the underlying patterns of variation in a data-driven manner. To illustrate MEFISTO, we apply the model to different datasets with spatial or temporal resolution, including an evolutionary atlas of organ development, a longitudinal microbiome study, a single-cell multi-omics atlas of mouse gastrulation and spatially resolved transcriptomics.
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