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Performant web-based interactive visualization tool for spatially-resolved transcriptomics experiments.

Chaichontat Sriworarat1, Annie Nguyen2, Nicholas J Eagles2

  • 1Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD, USA.

Biological Imaging
|March 15, 2024
PubMed
Summary
This summary is machine-generated.

Samui is a new web-based tool for visualizing large biological images quickly. It allows researchers to easily share, explore, and annotate complex imaging data, accelerating scientific discovery.

Keywords:
georeferencinginteractive image viewermulti-dimensional imagesingle-cell transcriptomicsspatially resolved transcriptomicsweb-based browser

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Area of Science:

  • Biology
  • Bioinformatics
  • Computational Biology

Background:

  • High-resolution and multiplexed imaging generate large, complex multidimensional datasets.
  • Visualizing and sharing these large biological images presents significant challenges for researchers.
  • Existing tools may lack the performance and interactivity needed for efficient exploration.

Purpose of the Study:

  • To introduce Samui, a novel, performant, and interactive web-based image visualization tool.
  • To enable fast visualization and annotation of large multidimensional biological images.
  • To facilitate seamless sharing and exploration of complex imaging data.

Main Methods:

  • Development of a web browser-based application, Samui.
  • Implementation of efficient algorithms for fast image rendering and data handling.
  • Testing with datasets from Vizgen MERFISH and 10x Genomics Visium Spatial Gene Expression platforms.

Main Results:

  • Samui provides rapid visualization of large multidimensional images directly in the web browser.
  • Users can browse through extensive image datasets and specific features within seconds.
  • The tool supports interactive annotation, enhancing data exploration capabilities.

Conclusions:

  • Samui addresses the critical challenge of visualizing and sharing large-scale biological imaging data.
  • Its performance and accessibility accelerate the analysis and interpretation of complex spatial omics datasets.
  • The tool is readily available for use with example datasets.