Protocol for analyzing functional gene module perturbation during the progression of diseases using a single-cell...

Area of Science:

• Genomics
• Systems Biology
• Computational Biology

Background:

• Complex disease pathogenesis involves intricate gene regulation across diverse cell types.
• Understanding these regulatory networks is crucial for disease mechanism elucidation.
• Existing methods may not fully capture cell-type-specific gene expression dynamics.

Purpose of the Study:

• To present a protocol for analyzing functional gene module (FGM) perturbation during disease progression.
• To introduce a single-cell Bayesian biclustering (scBC) framework for this analysis.
• To provide a reproducible method for exploring gene regulation in complex diseases.

Main Methods:

• Detailed steps for setting up the scBC workspace and preparing input data.
• Procedures for training the scBC model and reconstructing the data matrix.
• Methods for Bayesian biclustering, result exploration, and pathway perturbation identification.

Main Results:

• The scBC framework enables the analysis of FGMs in single-cell data.
• The protocol facilitates the identification of perturbed pathways during disease progression.
• This approach allows for a comprehensive understanding of gene regulation across cell types.

Conclusions:

• The presented scBC protocol offers a robust framework for dissecting complex disease mechanisms.
• It enables the identification of cell-type-specific gene regulatory perturbations.
• This methodology advances the study of functional gene modules in disease pathogenesis.