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An Integrated Approach for Microprotein Identification and Sequence Analysis
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Navigating protected genomics data with UCSC Genome Browser in a Box.

Maximilian Haeussler1, Brian J Raney1, Angie S Hinrichs1

  • 1Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA and Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA.

Bioinformatics (Oxford, England)
|October 29, 2014
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Summary

Genome Browser in a Box (GBiB) provides a virtual machine for the UCSC Genome Browser, enabling researchers to analyze personal genomic data locally. This tool facilitates on-demand or downloaded annotation data access for enhanced research capabilities.

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Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • The University of California Santa Cruz (UCSC) Genome Browser is a widely used resource for genomic data visualization and analysis.
  • Researchers often require local computational environments for handling sensitive or large datasets.

Purpose of the Study:

  • To provide a self-contained, locally executable version of the UCSC Genome Browser.
  • To enable researchers to integrate and analyze personal genomic data alongside established annotation tracks.

Main Methods:

  • Genome Browser in a Box (GBiB) is developed as a virtual machine appliance.
  • It utilizes open-source software, including VirtualBox and the UCSC Genome Browser.
  • Users access GBiB via a standard web browser after installation on their local computer.

Main Results:

  • GBiB allows seamless integration of local data files into the familiar UCSC Genome Browser interface.
  • Annotation data can be accessed in real-time from UCSC servers or downloaded for offline use.
  • The virtual machine approach simplifies deployment and ensures compatibility across major operating systems.

Conclusions:

  • GBiB offers a practical solution for researchers needing local, customizable genome browsing capabilities.
  • It enhances data privacy and accessibility for personal genomic data analysis.
  • The tool supports both on-demand and local data loading for flexible research workflows.