gsGator: an integrated web platform for cross-species gene set analysis

Area of Science:

• Bioinformatics
• Systems Biology
• Genomics

Background:

• Gene set analysis (GSA) aids in interpreting biological significance of gene lists using predefined sets like Gene Ontology (GO) or pathways.
• Phenotypic data is limited for human genes but abundant for model organisms, necessitating cross-species approaches.
• Effective GSA often requires interactive manipulation of gene lists and exploration of molecular networks.

Purpose of the Study:

• To develop gsGator, a web-based platform for interactive and cross-species functional interpretation of gene sets.
• To enhance GSA by integrating diverse biological annotations and network visualization tools.
• To enable flexible gene list manipulation and interactive exploration of molecular interactions.

Main Methods:

• Developed gsGator, a platform offering cross-species GSA and simultaneous analysis of multiple gene sets.
• Integrated comprehensive annotations: GO, pathways, genomic data, protein-protein interactions, TF-target, miRNA targeting, and cross-species phenotypes.
• Implemented interactive functionalities: Set Creator, Set Operator, and Network Navigator for gene list manipulation and network-based gene expansion.

Main Results:

• gsGator provides a fully integrated network viewer for GSA results and molecular networks.
• Users can create new gene lists via set operations (intersection, union, difference) and interactively explore molecular networks.
• Demonstrated utility of gsGator for interpreting genome-wide association study (GWAS) results through usage examples.

Conclusions:

• gsGator significantly expands the scope and utility of GSA through interactive and cross-species analysis.
• The platform facilitates discovery of novel biological insights by identifying conserved functional gene modules across species.
• Interactive GSA in gsGator enhances the interpretation of complex genomic datasets.