ArticleNature communications2024
HEARTSVG: a fast and accurate method for identifying spatially variable genes in large-scale spatial transcriptomics.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 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
23 citing papers in PubMed.
- Article
- Computational analysis in spatial transcriptomics: methods and perspectives.Briefings in bioinformatics · 2026Review
- Diffusion-based representation integration for foundation models improves spatial transcriptomics analysis.Bioinformatics (Oxford, England) · 2026Article
- MLN2SVG: domain-aware spatially variable gene detection using contrastive variational autoencoder and multi-level neighbor search.Briefings in bioinformatics · 2026Article
- Spatial-aware detection of copy number alterations from spatial transcriptomics using SpaCNA.Nature communications · 2026Article
- Castl: robust identification of spatially variable genes in spatial transcriptomics via an ensemble-based framework.Briefings in bioinformatics · 2026Article
- stGrads: decoding spatial gene expression gradients through proximity-driven analysis in complex tissues.Briefings in bioinformatics · 2026Article
- A spectral dimension reduction technique that improves pattern detection in multivariate spatial data.Bioinformatics (Oxford, England) · 2026Article
- Diffusion-based Representation Integration for Foundation Models Improves Spatial Transcriptomics Analysis.bioRxiv : the preprint server for biology · 2026Article
- Spatial transcriptomics on an expanded dataset at the brain-electrode interface: exploration of variability and identification of novel biomarkers.Frontiers in neuroscience · 2026Article
- Mapping safety in space: the emerging role of spatial transcriptomics in safe drug development.Frontiers in toxicology · 2026Review
- Addressing the mean-variance relationship in spatially resolved transcriptomics data with spoon.Biostatistics (Oxford, England) · 2025Article
- Spatial transcriptomics iterative hierarchical clustering (stIHC): A novel method for identifying spatial gene co-expression modules.Quantitative biology (Beijing, China) · 2025Article
- JOINT IDENTIFICATION OF SPATIALLY VARIABLE GENES VIA A NETWORK-ASSISTED BAYESIAN REGULARIZATION APPROACH.The annals of applied statistics · 2025Article
- A unified framework for identification of cell-type-specific spatially variable genes in spatial transcriptomic studies.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Prioritizing perturbation-responsive gene patterns using interpretable deep learning.Nature communications · 2025Article
- Unveiling fine-scale spatial structures and amplifying gene expression signals in ultra-large ST slices with HERGAST.Nature communications · 2025Article
- Categorization of 34 computational methods to detect spatially variable genes from spatially resolved transcriptomics data.Nature communications · 2025Review
- Recent advances in spatially variable gene detection in spatial transcriptomics.Computational and structural biotechnology journal · 2024Review
- Cell-specific priors rescue differential gene expression in spatial spot-based technologies.Briefings in bioinformatics · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
Identifying spatially variable genes (SVGs) is crucial for understanding the spatiotemporal characteristics of diseases and tissue structures, posing a distinctive challenge in spatial transcriptomics research. We propose HEARTSVG, a distribution-free, test-based method for fast and accurately identifying spatially variable genes in large-scale spatial transcriptomic data. Extensive simulations demonstrate that HEARTSVG outperforms state-of-the-art methods with higher
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.