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Expressionview: visualization of quantitative trait loci and gene-expression data in Ensembl.
Gertrud Fischer1, Saleh M Ibrahim, Gudrun A Brockmann
1University of Rostock, Institute of Immunology, Joachim-Jungius-Strasse 9, 18059 Rostock, Germany.
Genome Biology
|November 13, 2003
Summary
This study introduces a software tool for visualizing gene expression data alongside quantitative trait loci (QTL). The tool aids in identifying candidate genes for complex traits by integrating gene expression with genomic information.
Area of Science:
- Genomics
- Bioinformatics
- Systems Biology
Background:
- Gene expression profiling and quantitative trait loci (QTL) mapping are crucial for understanding complex traits.
- Integrating these datasets presents a significant challenge in biological research.
Purpose of the Study:
- To develop a novel software tool for the integrated visualization of gene expression data and QTL.
- To facilitate the transition from experimental expression data to genomic context within the Ensembl framework.
Main Methods:
- The software is implemented as an extension to the Ensembl project.
- It enables direct visualization of gene and protein expression levels alongside QTL data.
- Supports visualization of gene clusters and selection of candidate genes.
Main Results:
- The tool provides a unified platform for exploring gene expression and QTL data.
- It simplifies the identification of potential candidate genes associated with complex traits.
- Enhances the interpretation of microarray experiment results in a genomic context.
Conclusions:
- This software tool enhances the analysis of complex traits by integrating gene expression and QTL data.
- It offers a valuable resource for researchers studying the genetic basis of phenotypic variation.
- The Ensembl extension streamlines the process of candidate gene discovery.