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Related Experiment Videos

eQTL Viewer: visualizing how sequence variation affects genome-wide transcription.

Wei Zou1, David L Aylor, Zhao-Bang Zeng

  • 1Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695-7566, USA. wzou@statgen.ncsu.edu <wzou@statgen.ncsu.edu>

BMC Bioinformatics
|January 11, 2007
PubMed
Summary
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A new bioinformatics tool, eQTL Viewer, helps visualize complex genetic data for gene expression. This tool aids researchers in understanding transcriptional regulation and identifying the genetic basis of gene expression variations.

Area of Science:

  • Genomics
  • Bioinformatics
  • Systems Biology

Background:

  • Expression Quantitative Trait Locus (eQTL) mapping identifies genetic factors influencing gene expression.
  • Current eQTL mapping generates vast datasets, complicating the analysis of multi-region and multi-profile relationships.
  • There is a need for advanced bioinformatics tools to interpret complex eQTL mapping results.

Purpose of the Study:

  • To develop an informative bioinformatics tool for visualizing and interpreting eQTL mapping results.
  • To facilitate the exploration of relationships between expression traits and candidate genes within eQTL regions.

Main Methods:

  • Development of a web-based tool named eQTL Viewer.
  • Utilization of Scalable Vector Graphics (SVG) for high-resolution, scalable visualizations.

Related Experiment Videos

  • Dynamic superposition of biological annotations onto eQTL mapping data.

    • Main Results:

    • eQTL Viewer provides an intuitive interface for visualizing eQTL mapping data.
    • The tool generates high-resolution plots adaptable to various scales.
    • Biological annotations can be dynamically overlaid on visualizations.

    Conclusions:

    • eQTL Viewer offers an efficient method for biologists to explore transcriptional regulation.
    • The tool supports hypothesis generation regarding the genetic underpinnings of transcriptional regulation.