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ENACT: End-to-End Analysis of Visium High Definition (HD) Data.

Mena Kamel1, Yiwen Song1, Ana Solbas2

  • 1Digital R&D, Sanofi, Toronto, ON M5V 1V6, Canada.

Bioinformatics (Oxford, England)
|March 7, 2025
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Summary

ENACT is a new pipeline for high-definition spatial transcriptomics. It accurately maps transcripts to cells, enabling precise cell type identification in tissues.

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Area of Science:

  • Histopathology
  • Molecular Biology
  • Bioinformatics

Background:

  • Spatial transcriptomics (ST) allows gene expression analysis in tissue context.
  • Current ST resolution limits detailed cellular analysis.
  • Visium High Definition (HD) technology offers cell-level resolution, but transcript mapping and cell type assignment remain challenging.

Purpose of the Study:

  • To develop a computational pipeline for cell-resolution spatial transcriptomics.
  • To accurately map transcripts to individual cells within histopathology samples.
  • To enable robust cell type inference from Visium HD data.

Main Methods:

  • Developed ENACT, a self-contained pipeline integrating advanced cell segmentation with Visium HD data.
  • Incorporated novel bin-to-cell assignment methods for improved transcript quantification.
  • Validated the pipeline on diverse synthetic and real-world datasets.

Main Results:

  • ENACT accurately infers cell types across whole tissue sections at single-cell resolution.
  • The pipeline enhances the accuracy of single-cell transcript estimates.
  • Demonstrated scalability to samples with hundreds of thousands of cells.

Conclusions:

  • ENACT provides a robust solution for spatially resolved transcriptomics analysis.
  • The pipeline overcomes limitations in transcript mapping and cell type assignment for Visium HD data.
  • Enables deeper insights into tissue architecture and cellular heterogeneity.