PAGER Web APP: An Interactive, Online Gene Set and Network Interpretation Tool for Functional Genomics.

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Functional genomics studies utilize omics profiling to identify gene expression signatures and biological pathways.
• Existing geneset, network, and pathway analysis (GNPA) web servers lack automated integrative downstream analysis capabilities.

Purpose of the Study:

• To develop a novel web-based interactive application, PAGER Web APP, for online R scripting of integrative GNPA.
• To demonstrate the utility of PAGER Web APP in discovering relevant pathways and network modules for biological insights.

Main Methods:

• Development of an interactive web application supporting online R scripting for GNPA.
• Comparative analysis of PAGER Web APP against existing tools (PAGER, EnrichR, WebGestaltR) using a melanoma drug resistance case study.

Main Results:

• The PAGER Web APP enables automated integrative GNPA, facilitating the discovery of highly relevant pathways and network modules.
• A case study on melanoma drug resistance revealed novel biological insights through the application.
• PAGER Web APP demonstrated advantages in integrative GNPA compared to PAGER, EnrichR, and WebGestaltR.

Conclusions:

• PAGER Web APP provides a powerful platform for integrative functional genomic analysis.
• The tool enhances the discovery of biological pathways and network modules, advancing functional genomics research.
• The web application is publicly accessible, promoting wider adoption and research collaboration.