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Updated: May 31, 2026

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
Published on: July 29, 2022
Construct and Compare Gene Coexpression Networks with DAPfinder and DAPview.
Jeff Skinner1, Yuri Kotliarov, Sudhir Varma
1Bioinformatics and Computational Biosciences Branch (BCBB), Office of Cyber Infrastructure and Computational Biology (OCICB), National Institute of Allergy and Infectious Disease (NIAID), National Institutes if Health (NIH), Bethesda, Maryland, USA.
DAPfinder and DAPview tools construct gene coexpression networks and identify differences between phenotypes. These Differentially Associated Pair (DAP) analyses aid biological network reconstruction and comparison.
Area of Science:
- Bioinformatics
- Systems Biology
- Computational Biology
Background:
- Novel BRB-ArrayTools plug-ins, DAPfinder and DAPview, are introduced for biological network analysis.
- These tools facilitate the construction of gene coexpression networks.
- They identify significant differences in pairwise gene-gene coexpression between distinct phenotypes.
Purpose of the Study:
- To develop user-friendly tools for reconstructing and comparing biological networks.
- To identify Differentially Associated Pairs (DAPs) representing significant changes in gene-gene associations.
- To provide flexible analysis options for gene coexpression studies.
Main Methods:
- DAPfinder and DAPview offer multiple filtering methods, gene-gene association metrics, and statistical testing approaches.
- The tools incorporate various multiple comparison adjustments for robust analysis.
- Network visualization is integrated with Cytoscape for intuitive display.
Main Results:
- The analysis of glioma experiments revealed significant differences in gene-gene associations.
- Microarray simulations demonstrated the utility and accuracy of the developed tools.
- Differentially Associated Pairs (DAPs) were identified, highlighting key biological variations.
Conclusions:
- DAPfinder provides a user-friendly interface for biological network reconstruction.
- The tools enable effective comparison of gene coexpression patterns across different conditions.
- These plug-ins enhance the analysis of complex biological systems.
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