Related Experiment Video
Updated: May 15, 2026
A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
Published on: July 1, 2020
Pathway correlation profile of gene-gene co-expression for identifying pathway perturbation
Allison N Tegge1, Charles W Caldwell, Dong Xu
1Informatics Institute, University of Missouri, Columbia, MO, USA.
Abstract:
Identifying perturbed or dysregulated pathways is critical to understanding the biological processes that change within an experiment. Previous methods identified important pathways that are significantly enriched among differentially expressed genes; however, these methods cannot account for small, coordinated changes in gene expression that amass across a whole pathway. In order to overcome this limitation, we use microarray gene expression data to identify pathway perturbation based on pathway correlation profiles. By identifying the distribution of gene-gene pair correlations within a pathway, we can rank the pathways based on the level of perturbation and dysregulation. We have shown this successfully for differences between two experimental conditions in Escherichia coli and changes within time series data in Saccharomyces cerevisiae, as well as two estrogen receptor response classes of breast cancer. Overall, our method made significant predictions as to the pathway perturbations that are involved in the experimental conditions.
Insights
This study introduces a new method to detect pathway dysregulation by analyzing gene correlation profiles. This approach identifies subtle, coordinated gene expression changes missed by traditional methods, improving biological process understanding.
Area of Science:
- Systems Biology
- Genomics
- Bioinformatics
Background:
- Identifying biological pathway dysregulation is crucial for understanding experimental changes.
- Existing methods focusing on gene enrichment miss subtle, coordinated pathway alterations.
- Pathway correlation profiles offer a novel approach to detect these changes.
Purpose of the Study:
- To develop and validate a novel method for identifying pathway perturbation using gene expression data.
- To overcome the limitations of traditional gene enrichment methods in detecting coordinated expression changes.
- To provide a more sensitive approach for understanding biological processes under experimental conditions.
Main Methods:
- Utilizing microarray gene expression data to compute pathway correlation profiles.
- Analyzing the distribution of gene-pair correlations within biological pathways.
- Ranking pathways based on their perturbation and dysregulation levels.
Main Results:
- Successfully identified pathway perturbations in diverse experimental models, including Escherichia coli and Saccharomyces cerevisiae.
- Demonstrated effectiveness in classifying breast cancer subtypes based on estrogen receptor response.
- The method accurately predicted involved pathway perturbations across different experimental contexts.
Conclusions:
- Pathway correlation profiles offer a powerful tool for detecting subtle, coordinated gene expression changes.
- This method enhances the understanding of biological processes and experimental condition impacts.
- The approach is broadly applicable across various biological systems and research areas.
Related Concept Videos
01:19Interactions Between Signaling Pathways
Convergence and divergence, and cross-talk between signaling pathways
Two distinct signaling pathways can converge on a single functional unit, which may either be a single protein or a complex of proteins. The response is either functionally distinct or synergistic between the two pathways but different from the response...
01:09Epistasis Analysis
01:23Regulation of Expression at Multiple Steps
02:24Regulation of Expression Occurs at Multiple Steps
Transcription results in the generation of precursor (pre-mRNA) that consists of both exons and introns, which needs further processing before being translated to a...
02:24Regulation of Expression Occurs at Multiple Steps
Transcription results in the generation of precursor (pre-mRNA) that consists of both exons and introns, which needs further processing before being translated to a...
02:26Protein Networks
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...