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Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis
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BigTop: a three-dimensional virtual reality tool for GWAS visualization.

Samuel T Westreich1, Maria Nattestad2, Christopher Meyer2

  • 1DNAnexus, Inc., Mountain View, CA, USA. swestreich@dnanexus.com.

BMC Bioinformatics
|February 2, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces BigTop, a virtual reality (VR) framework that transforms traditional 2D Manhattan plots for genome-wide association studies (GWAS) into interactive 3D visualizations, enhancing data exploration.

Keywords:
Data interactionData plottingGWASManhattan plotUser InterfaceVirtual realityVisualization

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Area of Science:

  • Genomics
  • Bioinformatics
  • Data Visualization

Background:

  • Genome-wide association studies (GWAS) traditionally use 2D Manhattan plots.
  • These plots display SNP chromosomal location vs. p-value.
  • Limitations include lack of interactivity and inability to show additional data dimensions.

Purpose of the Study:

  • To develop an interactive 3D visualization framework for GWAS data.
  • To overcome limitations of traditional 2D Manhattan plots.
  • To enhance the exploration of genetic association results.

Main Methods:

  • Developed BigTop, a VR visualization framework.
  • Implemented a 3D Manhattan plot in a cylindrical VR environment.
  • Utilized JavaScript, React, and A-Frame for development.
  • Enabled rendering in VR headsets and 2D browsers.
  • Supported data input via JSON or tab-separated files.

Main Results:

  • BigTop renders GWAS data in an interactive 3D space.
  • The z-axis displays minor allele frequency, aiding in identifying allelic variants.
  • Users can interact with individual SNPs to access detailed information.
  • The framework is accessible via VR and standard web browsers.

Conclusions:

  • BigTop offers a novel, interactive 3D representation of Manhattan plots.
  • This VR approach enhances the display and exploration of GWAS data.
  • The framework provides additional dimensions and interactivity for genetic analysis.