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Updated: Jun 25, 2026
06:38
Pattern-based Search of Epigenomic Data Using GeNemo
Published on: October 8, 2017
gcExplorer: interactive exploration of gene clusters.
Theresa Scharl1, Friedrich Leisch
1Department of Biotechnology, Universität für Bodenkultur, Vienna, Austria. theresa.scharl@ci.tuwien.ac.at
Bioinformatics (Oxford, England)
|February 20, 2009
Summary
Gene expression data analysis uses cluster analysis to find gene groups. The new R package, gcExplorer, offers interactive visualization for exploring these gene clusters and their associated data.
Area of Science:
- Bioinformatics
- Computational Biology
- Genomics
Background:
- Cluster analysis is crucial for interpreting gene expression data from microarray studies.
- Identifying genes with similar expression patterns aids biological discovery.
- Effective visualization of clustering results is essential for user comprehension.
Purpose of the Study:
- Introduce gcExplorer, a novel R package for interactive gene cluster exploration.
- Enhance the interpretability of gene clustering outcomes.
- Provide tools for in-depth investigation of cluster-specific information.
Main Methods:
- Development of the gcExplorer R package.
- Implementation of interactive visualization techniques for cluster analysis.
- Integration of extensive data exploration features for gene clusters.
Main Results:
- gcExplorer enables interactive exploration of gene clusters.
- The package facilitates the interpretation of complex clustering results.
- Users can investigate comprehensive information related to identified gene clusters.
Conclusions:
- gcExplorer significantly improves the usability and interpretability of gene expression cluster analysis.
- The R package offers a powerful platform for researchers to explore and understand gene expression patterns.
- Interactive visualization is key to unlocking the full potential of gene clustering in biological research.
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