ArticleBriefings in bioinformatics2025
Artifacts in spatial transcriptomics data: their detection, importance, prevalence, and prevention.
Article in Briefings in bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
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Who cites it
4 citing papers in PubMed.
- Understanding the spatial determinants of the Oxford Classic prognostic signature for high-grade serous ovarian cancer.Communications medicine · 2026Article
- SpatialArtifacts: a computational framework for tissue artifact detection in spatial transcriptomics data.bioRxiv : the preprint server for biology · 2026Article
- Spotsweeper-py: spatially-aware quality control metrics for spatial omics data in the Python ecosystem.bioRxiv : the preprint server for biology · 2025Article
- MIMYR: Generative modeling of missing tissue in spatial transcriptomics.bioRxiv : the preprint server for biology · 2025Article
Corrections and comments
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Authors and funding
17 authors.
Funding
Abstract
Data artifacts may induce errors in findings from any spatial transcriptomics platform. To provide protection from these errors, we have developed Border, Location, and edge Artifact DEtection (BLADE). BLADE is a novel collection of automated cross-platform statistical methods for detecting and removing three types of artifacts: (i) border effects, where total gene reads is modified at the border of the capture area; (ii) tissue edge effects, where total gene reads is modified at the edge of the tissue; (iii) location batch malfunctions, where there is a zone in the same location on all slides in a batch with substantially decreased sequencing depth. These artifacts are not mutually exclusive. BLADE has been applied to both Visium and CosMx data, and was used to evaluate our library of 37 10x Visium samples of liver and adipose tissue from humans and mice. Artifacts were found to be both common and impactful in those samples, indicating that artifact detection methods are critical for spatial transcriptomics quality control. Our BLADE software is publicly available.
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Registered trials
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