ReactomePA

ReactomePA performs pathway enrichment and gene set analyses using the REACTOME pathway database to interpret high-throughput and sequencing-derived genomic data.

Key Features:

• R/Bioconductor package: Implemented as an R/Bioconductor package for integration with Bioconductor analysis workflows.
• Enrichment Analysis: Implements statistical enrichment analysis using the hypergeometric test to identify significantly enriched REACTOME pathways.
• Gene Set Enrichment Analysis (GSEA): Performs gene set enrichment analysis (GSEA) to assess whether predefined gene sets show statistically significant differences between biological states.
• Functional Analysis: Supports functional analysis of genomic loci from sequencing experiments, including cis-regulatory elements and non-coding regions.
• Comparative Analysis: Facilitates comparison of enriched pathways across experimental datasets to identify shared or divergent pathway perturbations.
• Visualization Capabilities: Provides functions to generate customizable, publication-quality figures for pathway analysis results.

Scientific Applications:

• Pathway interpretation of high-throughput data: Enables interpretation of biological pathways underlying differential signals from high-throughput experiments.
• Gene expression analysis: Supports analysis of pathway-level changes derived from differential gene expression studies.
• Epigenetics and regulatory genomics: Applies to studies of epigenetic marks and regulatory genomics by linking genomic loci to REACTOME pathways.
• Functional analysis of genomic loci: Assesses functional significance of cis-regulatory elements and non-coding regions identified by sequencing.
• Comparative pathway analysis: Allows identification of common or distinct pathway-level responses across experimental conditions or datasets.

Methodology:

Leverages REACTOME pathway annotations to perform enrichment analyses by applying statistical tests such as the hypergeometric test and gene set enrichment analysis (GSEA).