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June 19, 2026Genome Research

Flexible and scalable inference of spatially varying correlation in spatial transcriptomics with spCorr

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Authors

CJChenxin Flora JiangYYYuxin YinPRPaul Robson

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Overview

Randomized trial finds that spCorr effectively detects spatially varying correlations in gene expression, indicating novel insights into gene regulation.

Key Points

  • The aim is to develop a method for analyzing spatially varying correlations in gene expression within tissue contexts.
  • Developed spCorr, a regression framework for estimating spatially varying correlations.
  • Conducted extensive simulations and real-data analyses to evaluate performance.
  • Assessed detection power and false discovery rate control in various scenarios.
  • spCorr demonstrates high detection power for spatially varying correlations in gene expression.
  • Successfully controls the False Discovery Rate across tests.
  • Reveals biologically meaningful patterns that enhance understanding of tissue structure and gene interactions.

Cite This Study

Jiang et al. (2026) studied this question.

synapsesocial.com/papers/6a34dff765a5b0777af2ef1fhttps://doi.org/10.1101/gr.281559.125
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Also Consider

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

  1. 1spCorr: flexible and scalable inference of spatially varying correlation in spatial transcriptomics2025
  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. 3InSituCor: exploring spatially correlated genes conditional on the cell type landscape2025 · 7 citations
  4. 4spVC for the detection and interpretation of spatial gene expression variation2024 · 23 citations
  5. 5Accounting for Spatial Correlation in Graphical Analysis of Spatial Transcriptomics Data2025