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A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
Published on: July 1, 2020
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A MATLAB tool for pathway enrichment using a topology-based pathway regulation score
Maysson Ibrahim1,2, Sabah Jassim3, Michael Anthony Cawthorne4
1Department of Applied Computing, the University of Buckingham, Buckingham, MK18 1EG, UK. maysson.ibrahim@buckingham.co.uk.
BMC Bioinformatics
|November 5, 2014
Summary
This study introduces an enhanced Pathway Regulation Score (PRS) tool for analyzing gene expression data. The tool integrates pathway topology and gene expression levels to identify key biological insights from complex transcriptomic data.
Area of Science:
- Bioinformatics
- Systems Biology
- Computational Biology
Background:
- Genome-wide transcriptional profiling generates vast gene expression data, posing challenges for analysis.
- Traditional methods often fail to fully utilize gene expression data, relationships, and dependencies.
- Previous work introduced a Pathway Regulation Score (PRS) tool for signaling pathways.
Purpose of the Study:
- To extend the PRS tool to include metabolic pathways.
- To develop a graphical user interface (GUI) for the PRS tool.
- To improve the analysis of complex transcriptomic data.
Main Methods:
- Incorporation of metabolic pathway topology into PRS calculations.
- Development of a user-friendly graphical user interface (GUI).
- Calculation of PRS and z-scores for pathway significance.
Main Results:
- The tool accepts input from diverse microarray platforms and species.
- Users can calculate PRS and z-scores for pathway comparison.
- Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway diagrams can be visualized with highlighted impacted genes.
Conclusions:
- The enhanced PRS tool effectively filters complex transcriptomic data.
- It aids in isolating biologically relevant insights.
- The GUI facilitates easier analysis of gene expression data.
