E.PathDash, pathway activation analysis of publicly available pathogen gene expression data

Area of Science:

• Bioinformatics
• Genomics
• Microbiology

Background:

• Chronic respiratory diseases increase susceptibility to severe bacterial infections.
• Public gene expression data offers valuable insights but is time-consuming to analyze.
• Pathogen infections, like those caused by *Pseudomonas aeruginosa* and *Staphylococcus aureus*, contribute significantly to morbidity and mortality.

Purpose of the Study:

• To develop and validate E.PathDash, an application for rapid re-analysis of pathogen gene expression data.
• To enable researchers to quickly assess pathogen responses to various experimental conditions.
• To facilitate the generation of mechanistic hypotheses for pathogen behavior in disease-relevant environments.

Main Methods:

• E.PathDash integrates data from 48 studies, encompassing 548 samples and 404 treatment comparisons.
• The application allows analysis at KEGG pathway or gene ontology levels, as well as individual gene analysis.
• Users can download visualizations (volcano plots, boxplots), differential gene expression results, and raw count data.

Main Results:

• E.PathDash reduces data analysis time from hours to seconds.
• Pathway analysis recapitulated existing findings and revealed new insights into pathogen environmental responses.
• The tool proved useful for cystic fibrosis researchers, validating its utility.

Conclusions:

• E.PathDash significantly accelerates the accessibility and analysis of pathogen gene expression data.
• The application supports reproducible research and hypothesis generation for chronic respiratory diseases.
• Freely accessible software and data promote wider adoption and research advancement.