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Updated: Jul 5, 2025

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PROST: quantitative identification of spatially variable genes and domain detection in spatial transcriptomics.

Yuchen Liang1, Guowei Shi2, Runlin Cai1

  • 1School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China.

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|January 18, 2024
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Summary

This study introduces PROST, a new computational framework for analyzing spatial transcriptomic data. PROST accurately identifies spatially variable genes (SVGs) and tissue domains, advancing biological discovery.

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Area of Science:

  • Genomics
  • Computational Biology
  • Bioinformatics

Background:

  • Spatially resolved transcriptomics offers insights into tissue architecture and gene function.
  • Existing computational methods struggle with uniform quantification of spatially variable genes (SVGs) and domain delineation.
  • SVGs and spatial domains are often analyzed separately, limiting comprehensive understanding.

Purpose of the Study:

  • To develop a robust computational framework (PROST) for quantitative analysis of spatial transcriptomic patterns.
  • To improve the identification and quantification of SVGs.
  • To integrate SVG analysis with unsupervised spatial domain clustering.

Main Methods:

  • Developed the PROST framework with two core components: the PROST Index for quantifying spatial variations and a self-attention mechanism for unsupervised domain clustering.
  • Applied the framework to diverse spatial transcriptomic datasets across different resolutions (multicellular to cellular).

Main Results:

  • PROST demonstrated superior performance in identifying SVGs compared to existing methods.
  • The framework achieved accurate spatial domain segmentation.
  • The PROST Index effectively prioritized genes with significant spatial expression variations.

Conclusions:

  • PROST provides a flexible and robust framework for analyzing spatial transcriptomic data.
  • The integrated approach enhances the exploration of biological insights from spatial gene expression patterns.
  • This method advances the field of spatial transcriptomics analysis.