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VistoSeg: Processing utilities for high-resolution images for spatially resolved transcriptomics data.

Madhavi Tippani1, Heena R Divecha1, Joseph L Catallini1,2

  • 1Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA.

Biological Imaging
|March 21, 2024
PubMed
Summary
This summary is machine-generated.

VistoSeg is a new MATLAB pipeline that processes high-resolution images from spatial transcriptomics (SRT) platforms. This tool integrates gene expression data with tissue morphology, enhancing biological insights.

Keywords:
MATLABVisiumVisium-Spatial Proteogenomicshematoxylin and eosinimmunofluorescencesegmentationspatially resolved transcriptomics

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Spatially resolved transcriptomics (SRT) links gene expression to tissue anatomy.
  • Next-generation sequencing (NGS)-based SRT platforms like 10x Genomics Visium offer gene expression mapping.
  • Limited computational tools exist for integrating image data with gene expression from these platforms.

Purpose of the Study:

  • To develop VistoSeg, a MATLAB pipeline for processing and analyzing high-resolution images from the Visium platform.
  • To enable the integration of image-derived metrics with spatially resolved transcriptomic data.
  • To facilitate downstream analyses in R and Python.

Main Methods:

  • Developed VistoSeg as a MATLAB pipeline.
  • Designed for processing, analyzing, and visualizing high-resolution histological and immunofluorescent images.
  • Outputs are compatible with transcriptomic data for integration.

Main Results:

  • VistoSeg provides user-friendly tools for integrating image metrics with spatial gene expression data.
  • The pipeline processes and visualizes high-resolution images from the Visium platform.
  • Facilitates enhanced understanding of transcriptional landscapes within tissue architecture.

Conclusions:

  • VistoSeg enhances the integration of morphological and transcriptomic data in spatial transcriptomics.
  • The pipeline supports downstream analysis in common programming languages.
  • VistoSeg improves the interpretability of spatial gene expression data within its tissue context.