Shiny-DEG: A Web Application to Analyze and Visualize Differentially Expressed Genes in RNA-seq

Area of Science:

• Genomics and Bioinformatics
• Molecular Biology and Genetics

Background:

• RNA sequencing (RNA-seq) is crucial for large-scale gene expression analysis in biological and medical research.
• Biologists often face challenges interpreting complex RNA-seq data due to limited programming and statistical expertise.
• Existing tools for next-generation sequencing (NGS) data analysis and visualization have notable limitations.

Purpose of the Study:

• To develop Shiny-DEG, a user-friendly web application for exploring and visualizing differentially expressed genes from RNA-seq data.
• To provide biologists, including students and faculty, with an accessible tool for RNA-seq data interpretation.
• To support multi-factor experimental designs and interactive parameter modification for tailored analysis.

Main Methods:

• Development of Shiny-DEG, a web application integrating RNA-seq data analysis and visualization.
• Implementation of interactive features for parameter adjustment based on experimental objectives.
• Facilitation of direct download for all analysis results to aid interpretation.

Main Results:

• Shiny-DEG enables intuitive exploration and visualization of differentially expressed genes from RNA-seq experiments.
• The application supports complex, multi-factor experimental designs.
• Users can interactively adjust analysis parameters and download results for deeper biological insights.

Conclusions:

• Shiny-DEG significantly lowers the barrier for biologists to interpret RNA-seq data, regardless of programming background.
• The tool enhances the understanding of transcriptome differences and underlying biological mechanisms.
• It serves as a valuable resource for advancing biological research through accessible gene expression analysis.