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October 3, 2025Open Access

spCorr: flexible and scalable inference of spatially varying correlation in spatial transcriptomics

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Authors

CJChenxin JiangYYYuxin YinPRPaul Robson

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Overview

Spatial correlation analysis detects gene interactions in spatial transcriptomics, highlighting biological significance.

Key Points

  • spCorr identifies how gene correlations vary across spatial locations, offering insights into gene regulation.
  • Extensive simulations show spCorr achieves high detection power while controlling false discovery rates effectively.
  • This flexible framework provides interpretable correlation estimates, enhancing our understanding of tissue environments.
  • Real-data analyses reveal biologically meaningful patterns, improving the exploration of gene functions and interactions.

Cite This Study

Jiang et al. (2025) studied this question.

synapsesocial.com/papers/68e034f7f0e39f13e7fa2fdahttps://doi.org/10.1101/2025.09.30.679684
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Flexible and scalable inference of spatially varying correlation in spatial transcriptomics with spCorr2026
  2. 2HybridSVG: Ensemble Framework for Detecting Spatially Variable Genes in Spatial Transcriptomics using Fusion of Global and Local Autocorrelation <b></b>2025 · 2 citations
  3. 3spVC for the detection and interpretation of spatial gene expression variation2024 · 23 citations
  4. 4Accounting for Spatial Correlation in Graphical Analysis of Spatial Transcriptomics Data2025
  5. 5A flexible Bayesian framework for detecting cross-sample spatial expression variability in heterogeneous tissues2026