bulk-rnaseq-gsea-visualization

To visualize GSEA results from RNA-seq data for publication, you can generate publication-quality figures including dotplots, NES bars, and running sums using R-based plotting with clusterProfiler and enrichplot. This workflow uses defined color palettes and schema validation to ensure consistent output.

A master GSEA table (master_gsea_table.csv) is a consolidated file of GSEA results that powers an interactive Python-based pathway explorer dashboard. It enables dynamic investigation and reporting of enriched pathways by feeding pooled or per-database data directly into the UI.

Yes, you can pool GSEA results across multiple databases for visualization. The workflow supports both per-database visualizations and cross-database pooled analyses, allowing you to investigate and report enriched pathways from various sources simultaneously.

To create an interactive dashboard from RNA-seq pathway analysis results, you launch the Python-based pathway explorer UI. This dashboard is fed by the master_gsea_table.csv file, allowing you to interactively explore and filter GSEA outputs.

Yes, you need both R and Python to run the full workflow. R is required for generating publication-quality GSEA visualizations using clusterProfiler and enrichplot, while Python is needed to launch and power the interactive pathway explorer dashboard.