GeneSetCart: assembling, augmenting, combining, visualizing, and analyzing gene sets

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Multiomics datasets require effective gene set management for integrated analysis and knowledge discovery.
• Existing tools often lack comprehensive management capabilities for gene sets from diverse sources.

Purpose of the Study:

• To introduce GeneSetCart, an interactive web-based platform for comprehensive gene set management and analysis.
• To enable biologists, regardless of programming expertise, to integrate and analyze multiomics data.

Main Methods:

• GeneSetCart allows gathering gene sets from various sources, augmenting them with coexpression and interaction data.
• It supports set operations (union, intersection, consensus) and visualization using Venn diagrams, heatmaps, UMAP, SuperVenn, and UpSet plots.
• The platform integrates with external tools for enrichment analysis and uses a large language model (LLM) for interpreting overlapping gene sets and generating reports.

Main Results:

• GeneSetCart provides a centralized environment for gene set manipulation, visualization, and analysis.
• It facilitates the identification of similarities and overlaps between gene sets from different sources.
• The platform successfully demonstrated its utility through two use cases, including LLM-assisted interpretation of gene set overlaps.

Conclusions:

• GeneSetCart empowers biologists to perform complex gene set analyses, promoting data integration and hypothesis generation.
• The platform enhances accessibility to advanced bioinformatics tools for researchers without coding skills.
• GeneSetCart serves as a valuable resource for advancing biological research through integrated multiomics data analysis.