ERSAtool: A User-Friendly R/Shiny Comprehensive Transcriptomic Analysis Interface Suitable for Education

Area of Science:

• Bioinformatics
• Genomics
• Computational Biology

Background:

• RNA sequencing (RNA-seq) is crucial for gene expression analysis but requires significant bioinformatics expertise.
• The complexity of RNA-seq data analysis presents a barrier for many students and researchers.
• A need exists for user-friendly tools to facilitate advanced transcriptomic analyses.

Purpose of the Study:

• To introduce ERSAtool, an R/Shiny interface designed to simplify RNA sequencing data analysis.
• To provide an intuitive graphical visualization of the entire RNA-seq workflow.
• To enhance accessibility of sophisticated transcriptomic analyses for educational and research purposes.

Main Methods:

• Developed ERSAtool as a comprehensive R/Shiny application.
• Integrated established Bioconductor packages for high-standard analyses.
• Supported various input formats and direct integration with Gene Expression Omnibus (GEO) for metadata.
• Guided users through normalization, visualization, differential expression, and functional enrichment analyses (GO, GSEA).

Main Results:

• ERSAtool offers an intuitive graphical interface for RNA-seq analysis.
• The tool simplifies complex steps like normalization, differential expression, and functional interpretation.
• Generated comprehensive, downloadable reports for enhanced reproducibility and knowledge sharing.
• Facilitated educational use in transcriptomics courses.

Conclusions:

• ERSAtool significantly lowers the technical barrier for RNA-seq data analysis.
• The tool improves accessibility to advanced transcriptomic capabilities for a wider audience.
• ERSAtool has the potential to accelerate discoveries in various biological fields by democratizing RNA-seq analysis.