ArticleNature methods2018
SpatialDE: identification of spatially variable genes.
Article in Nature methods, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 430 papers, 1 of them a synthesis that pooled it.
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
430 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Society for Immunotherapy of Cancer: updates and best practices for multiplex immunohistochemistry (IHC) and immunofluorescence (IF) image analysis and data sharing.Journal for immunotherapy of cancer · 2025Guideline
- Decoding epithelial-mesenchymal transitions with multi-omics.Nature reviews. Genetics · 2026Review
- 3D multi-omics tumour atlases: from technology to biology and clinical translation.Nature reviews. Cancer · 2026Review
- RKMR: A Rapid Kernel Machine Regression Framework for Optimal Marker Detection in Spatial Omics Data.bioRxiv : the preprint server for biology · 2026Article
- Pan-tumor spatial transcriptomics reveals conserved properties of tumor organization.Cell reports. Medicine · 2026Article
- Decoding cell-cell communication in spatial transcriptomics: mechanistic insights, modeling constraints, and analytical caveats.Briefings in bioinformatics · 2026Review
- Accurately Predicting Cell Type Abundance from Spatial Histology Image Through HPCell.Interdisciplinary sciences, computational life sciences · 2026Article
- Spatial isoform sequencing at single-cell resolution reveals cell-type-specific spatial isoform variability in multiple brain cell types.Nature methods · 2026Article
- Ten quick tips for spatial transcriptomics analysis.PLoS computational biology · 2026Review
- STcompare: comparative spatial transcriptomics data analysis of structurally matched tissues to characterize differentially spatially patterned genes.Bioinformatics (Oxford, England) · 2026Article
- scProtoTransformer: Scalable reference mapping across molecules, cells, and donors.Science advances · 2026Article
- PRISM: Prior-enhanced Inference for Spatial Transcriptomic Cell Type Mapping.Bioinformatics (Oxford, England) · 2026Article
- DESpace2: detection of differential spatial patterns in spatial omics data.Bioinformatics (Oxford, England) · 2026Article
- Tissue and cellular spatiotemporal dynamics in colon aging.Nature biotechnology · 2026Article
- Spatial multi-omics analyses of the tumor immune microenvironment: advances and novel therapeutic avenues.Molecular cancer · 2026Review
- Integrative spatial multi-omics reveals the tumor ecosystem: From mechanistic insights to therapeutic strategies.iScience · 2026Review
- D3aist: data-driven detection of atypical interactions in spatial transcriptomics.BMC genomics · 2026Article
- Variational sparse Gaussian-process method for detecting spatially variable genes and cellular interactions in spatial transcriptomics.Briefings in bioinformatics · 2026Article
- ISPAT-3D: Spatially Varying Conditional Volumetric Network Estimation for 3D Tumor Imaging.Research square · 2026Article
- Computational analysis in spatial transcriptomics: methods and perspectives.Briefings in bioinformatics · 2026Review
370 more citing papers are in PubMed but not listed here.
Corrections and comments
- Commented on by
Authors and funding
3 authors.
Funding
Abstract
Technological advances have made it possible to measure spatially resolved gene expression at high throughput. However, methods to analyze these data are not established. Here we describe SpatialDE, a statistical test to identify genes with spatial patterns of expression variation from multiplexed imaging or spatial RNA-sequencing data. SpatialDE also implements 'automatic expression histology', a spatial gene-clustering approach that enables expression-based tissue histology.
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.