ArticleGenome biology2026
Differential expression analysis for spatially correlated data using smiDE.
Article in Genome biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed.
- Spatial co-expression and cell-cell communication inference from spatially resolved transcriptomics with CONCISE.bioRxiv : the preprint server for biology · 2026Article
- Single-cell Spatial Transcriptional Profiling Uncovers Heterogeneous Cellular Responses to Pathogenic Tau in a Mouse Model of Neurodegeneration.bioRxiv : the preprint server for biology · 2025Article
- Using transcripts to refine image based cell segmentation with FastReseg.Scientific reports · 2025Article
- Segger: Fast and accurate cell segmentation of imaging-based spatial transcriptomics data.bioRxiv : the preprint server for biology · 2025Article
- Single-cell spatial transcriptomics unravels cell states and ecosystems associated with clinical response to immunotherapy.Journal for immunotherapy of cancer · 2025Article
- The local cellular response to Human Papillomavirus focuses on basal layer restoration as visualizedFrontiers in immunology · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Differential expression is a key application of imaging spatial transcriptomics, moving analysis beyond cell type localization to examining cell state responses to microenvironments. However, spatial data poses new challenges to differential expression: segmentation errors cause bias in fold-change estimates, and correlation among neighboring cells leads standard models to inflate statistical significance. We find that ignoring these issues can result in considerable false discoveries that greatly outnumber true findings. We present a suite of solutions to these fundamental challenges, and implement them in the R package smiDE.
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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.