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Updated: Jul 27, 2025
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Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
Published on: July 29, 2022
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ACDC: a general approach for detecting phenotype or exposure associated co-expression.
Katelyn Queen1, My-Nhi Nguyen1, Frank D Gilliland1
1Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States.
Frontiers in Medicine
|June 5, 2023
Summary
This study introduces a new method to analyze gene co-expression across multiple factors, revealing gene associations with asthma control. The approach enhances understanding of complex biological relationships.
Area of Science:
- Genomics
- Bioinformatics
- Systems Biology
Background:
- Current differential co-expression methods are limited to single, binary, or categorical variables.
- This restricts the analysis of gene-gene relationships across complex phenotypes or exposures.
Purpose of the Study:
- To develop a novel approach for differential co-expression analysis that accommodates multiple phenotypes or exposures.
- To enable analysis with binary, ordinal, or continuous data types simultaneously.
Main Methods:
- A new method, ACDC (Analysis of Co-expression across Different Conditions), was developed.
- The method was applied to two asthma patient cohorts with varying asthma control levels.
Main Results:
- Gene co-expression analysis identified associations between gene expression levels and asthma control.
- Specific genes, including ADORA3, ALOX15, and IDO1, showed significant associations with asthma control scores.
Conclusions:
- ACDC offers a flexible extension to existing differential co-expression methodologies.
- The approach effectively detects differential co-expression across diverse external variables, advancing biological insights.
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