ArticlebioRxiv : the preprint server for biology2023
scResolve: Recovering single cell expression profiles from multi-cellular spatial transcriptomics.
Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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.
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.
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Who cites it
2 citing papers in PubMed.
- 16p11.2 duplication and NMDA receptor antagonism have distinct impacts on reward learning and decision making.Psychopharmacology · 2026Article
- Applications of AI to single-cell and spatial transcriptomics: current state-of-the-art and challenges.Frontiers in bioinformatics · 2025Review
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Authors and funding
8 authors.
Funding
Abstract
Many popular spatial transcriptomics techniques lack single-cell resolution. Instead, these methods measure the collective gene expression for each location from a mixture of cells, potentially containing multiple cell types. Here, we developed scResolve, a method for recovering single-cell expression profiles from spatial transcriptomics measurements at multi-cellular resolution. scResolve accurately restores expression profiles of individual cells at their locations, which is unattainable from cell type deconvolution. Applications of scResolve on human breast cancer data and human lung disease data demonstrate that scResolve enables cell type-specific differential gene expression analysis between different tissue contexts and accurate identification of rare cell populations. The spatially resolved cellular-level expression profiles obtained through scResolve facilitate more flexible and precise spatial analysis that complements raw multi-cellular level analysis.
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Registered trials
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