bulk-rnaseq-gsea-master-tables

Normalize heterogeneous GSEA results into a unified master_gsea_table.csv schema.

1|Updated Nov 20, 2025

Search Tags:#workflow #data-wrangling #gsea #master-table #clusterprofiler #r-to-python

Ready to run

npx skills add https://github.com/tony-zhelonkin/SciAgent-toolkit --skill bulk-rnaseq-gsea-master-tables

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: bulk-rnaseq-gsea-master-tables
Source: https://github.com/tony-zhelonkin/SciAgent-toolkit/tree/main/skills/.deprecated/bulk-rnaseq-gsea-master-tables
Command: npx skills add https://github.com/tony-zhelonkin/SciAgent-toolkit --skill bulk-rnaseq-gsea-master-tables

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

GSEA results from multiple sources are normalized and assembled into a unified CSV schema suitable for downstream visualization and reproducible reporting. It bridges R-based normalization with Python-based visualization by producing a stable master_gsea_table.csv and enabling idempotent appends for new databases or modules.

Core Features & Use Cases

Normalize gseaResult objects into a 13-column master schema and append to the master table
Support derived tables such as master_gsea_significant.csv and gsea_summary_stats.csv
Provide idempotent update patterns to avoid duplicates across re-runs
Assist debugging column-name mismatches between R and Python consumers

Quick Start

Load checkpoints and run the master table assembly to produce master_gsea_table.csv.

Frequently Asked Questions about bulk-rnaseq-gsea-master-tables

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I combine multiple GSEA results into a single master table?▼

To combine GSEA results into a master table, this Skill normalizes heterogeneous gseaResult objects from MSigDB and custom databases into a consistent 13-column schema. It appends outputs idempotently to produce a unified master_gsea_table.csv without duplicates.

Why do my R and Python GSEA outputs have column name mismatches?▼

R and Python GSEA outputs have column mismatches due to schema differences across consumers. This Skill bridges R-based normalization with Python-based visualization by enforcing schema validation and aligning columns into a stable master_gsea_table.csv format.

How do I prevent duplicate entries when appending new GSEA results to an existing table?▼

To prevent duplicates when appending GSEA results, this Skill implements an idempotent append mechanism with schema validation. This ensures reproducible results across re-runs without creating duplicate rows when adding new databases or modules.

Can I generate summary statistics and significant gene sets from a unified GSEA table?▼

Yes, you can generate derived tables from a unified GSEA table. This Skill supports creating outputs such as master_gsea_significant.csv and gsea_summary_stats.csv to prepare filtered data for downstream visualization and reproducible reporting.

What is the best way to normalize clusterProfiler GSEA outputs for visualization?▼

The best way to normalize clusterProfiler GSEA outputs is to apply a consistent schema transformation. This Skill converts R-based gseaResult objects into a standardized 13-column CSV format, enabling seamless Python-based visualization and reporting.