GeneTrail

GeneTrail performs statistical analysis of gene sets to detect enrichment of functional categories in high-throughput genomic and proteomic datasets.

Key Features:

• Functional Category Enrichment: Evaluates statistical over-representation of functional categories in input gene sets.
• Comprehensive Biological Categories: Supports KEGG, TRANSPATH, TRANSFAC, and Gene Ontology (GO) as annotation sources.
• Statistical Approaches: Implements Over-Representation Analysis (ORA) comparing a reference set against a test set, and Gene Set Enrichment Analysis (GSEA) scoring ranked gene lists.
• Innovative Statistical Methodology: Incorporates a dynamic-programming algorithm in the statistics module to improve P-value computation for GSEA.

Scientific Applications:

• High-throughput data analysis: Analyzes high-throughput genomic and proteomic datasets to identify enriched functional categories.
• Pathway and process identification: Identifies biological pathways and processes active under specific experimental conditions.
• Hypothesis generation and validation: Highlights statistically significant gene sets and pathways to support hypothesis generation and validation.

Methodology:

Implements Over-Representation Analysis (comparison of reference and test sets), Gene Set Enrichment Analysis (ranking and scoring of gene lists), and a dynamic-programming algorithm for P-value computation in GSEA.