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Updated: Jan 11, 2026

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

Distilling Direct Effects via Conditional Differential Gene Expression Analysis.

Jiaqi Gu¹, Andrew Skelton², James Staley²

¹Department of Mathematics and Statistics, University of South Florida, Tampa, FL 33620, USA.

Biorxiv : the Preprint Server for Biology

|November 19, 2025

Summary

This summary is machine-generated.

Conditional differential gene expression (CDGE) analysis identifies direct effect genes, revealing causal impacts on biological processes. This approach offers more informative conclusions than traditional methods for studying gene expression and disease mechanisms.

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Area of Science:

Genomics
Systems Biology
Bioinformatics

Background:

Gene expression analysis is vital for understanding gene function, interactions, and diseases.
Differential gene expression (DGE) analysis identifies gene expression changes across conditions.
Traditional DGE methods often capture indirect or non-causal associations (marginal associations).

Purpose of the Study:

Introduce conditional differential gene expression (CDGE) analysis to identify direct effect genes.
Distinguish genes with direct causal impact from those with indirect associations.
Enhance biological insights from gene expression data.

Main Methods:

Developed a novel CDGE analysis framework.
Applied CDGE to three RNA sequencing datasets, including a genome-scale perturb-seq dataset.
Evaluated the biological significance of direct effect genes through enrichment analyses.

Main Results:

CDGE analysis identified a small subset of differentially expressed genes as direct effect genes.
These direct effect genes mediate the actions of most other genes.
Direct effect genes provided greater biological insight in protein interaction and pathway enrichment analyses.

Conclusions:

CDGE analysis offers a more informative approach to understanding causal gene effects.
Direct effect genes identified by CDGE are key mediators of biological processes.
CDGE analysis is a valuable tool for studying biological pathways and disease mechanisms.