Gene-set enrichment analysis and visualization on the web using EnrichmentMap:RNASeq.

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Gene-set enrichment analysis (GSEA) is crucial for interpreting RNA sequencing (RNA-Seq) data.
• Existing GSEA tools can be computationally intensive and require software installation, posing a barrier for biologists.
• There is a need for accessible and efficient GSEA tools tailored for specific experimental designs like two-case RNA-Seq.

Purpose of the Study:

• To introduce EnrichmentMap: RNASeq, a novel web-based application for gene-set enrichment analysis.
• To provide a simplified and faster alternative to desktop software for RNA-Seq data analysis.
• To enhance the accessibility of GSEA for biologists with limited computational expertise.

Main Methods:

• Development of a web-based application, EnrichmentMap: RNASeq.
• Implementation of a simplified user interface for intuitive operation.
• Integration with Cytoscape as a web app for interoperability.

Main Results:

• EnrichmentMap: RNASeq provides an intuitive platform for gene-set enrichment analysis and visualization.
• The application offers faster processing times compared to traditional desktop workflows.
• It eliminates the need for software installation, making it readily accessible.

Conclusions:

• EnrichmentMap: RNASeq effectively supports two-case RNA-Seq experiments for Homo sapiens.
• The tool democratizes GSEA by catering to biologists with minimal computational background.
• It represents a significant advancement in web-based bioinformatics tools for genomic data analysis.