ErmineJ

ErmineJ performs gene set enrichment analysis on gene lists from microarray and other high-throughput gene expression profiling studies to identify functionally significant pathways and gene classes.

Key Features:

• Pathway and Gene Class Enrichment Analysis: Evaluates enrichment of pathways and gene classes in gene lists derived from microarray and gene expression profiling data.
• Customizable Analyses: Implements overrepresentation analysis, genes score resampling, and correlation resampling for flexible gene set evaluation.
• Resampling-Based Statistics: Incorporates resampling techniques to assess statistical significance of gene sets.
• Custom Gene Sets Creation: Supports definition and use of custom gene sets for targeted analyses.
• High-Level Visualization: Provides visualization capabilities to aid interpretation of gene set analysis results.
• Statistical Methods Variety: Includes a variety of statistical approaches for robust interpretation of genomic data.

Scientific Applications:

• Pathway discovery: Identifying key pathways and gene classes involved in disease mechanisms.
• Functional interpretation: Understanding gene function and interaction networks from large gene lists.
• Differential expression analysis support: Interpreting differential gene expression across different conditions or treatments.

Methodology:

Data formatting, selection of analysis type, creation of custom gene sets, and execution of analyses such as overrepresentation analysis and resampling (genes score resampling and correlation resampling).