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Genome display tool: visualizing features in complex data sets.

Lalitha Viswanath1,2, Yue Lu1,3, George E Fox1

  • 1Department of Biology and Biochemistry, 3201 Cullen Boulevard, University of Houston, Houston, Texas 77204-5001, USA.

Source Code for Biology and Medicine
|February 16, 2007
PubMed
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The Genome Display Tool (GDT) software visualizes bacterial genome data, enabling intuitive understanding of feature distribution and correlations. This tool aids in comparing genomic analysis methods and aids in other large dataset studies.

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Large datasets, such as bacterial genomes, present challenges for intuitive understanding.
  • Existing visualization tools for bacterial genomes often focus on global or local features, limiting the visualization of other contextual information.
  • There is a need for software that facilitates the visualization of correlations between diverse properties within a core dataset.

Purpose of the Study:

  • To introduce the Genome Display Tool (GDT), a novel software for visualizing bacterial genome data.
  • To enable simultaneous viewing of multiple attributes related to genes and intragenic regions.
  • To facilitate the intuitive understanding of feature distribution and correlations within large genomic datasets.

Main Methods:

Related Experiment Videos

  • Developed Java-based software, the Genome Display Tool (GDT).
  • Interfaced GDT with a MS-Access relational database for data storage and retrieval.
  • Enabled data input from MS-Excel spreadsheets for flexibility.
  • Utilized dynamic box sizing and zoom features for interactive visualization of genomic data.
  • Demonstrated functionality by comparing two horizontal gene transfer prediction methods in Synechocystis PCC-6803.

    • Main Results:

    • GDT allows simultaneous visualization of multiple genomic attributes using distinct colors and shapes.
    • The software represents genes as boxes correlated with physical genome position, with dynamic sizing based on gene count.
    • GDT successfully visualized the agreement between two horizontal transfer prediction methods and the genomic distribution of categorized genes.
    • The tool facilitates immediate assessment of concordance between different analytical approaches.

    Conclusions:

    • GDT offers a powerful method for developing an intuitive understanding of feature distribution in large datasets.
    • The software's utility expands as more features are incorporated, rapidly increasing visualization possibilities.
    • While demonstrated for bacterial genomics, the underlying principle of GDT is generalizable to other fields, such as patient studies.