RE-GOA

Re-GOA: Functional enrichment analysis of non-coding genomic regions

Re-GOA performs functional enrichment analysis of non-coding genomic regions by annotating regulatory elements, including enhancers and promoters, with Gene Ontology (GO) terms using network embedding of heterogeneous biological networks.

Key Features:

• Systematic Gene Ontology Annotation: Annotates regulatory elements by constructing a heterogeneous network integrating context-specific regulations, protein-protein interactions, and Gene Ontology (GO) terms.
• Network Embedding: Applies network embedding techniques derived from natural language processing to project network relationships into a low-dimensional vector space and quantify similarity between regulatory elements and GO terms.
• ChIP-seq TF Binding Site Annotation: Annotates transcription factor binding sites from ChIP-seq data.
• ATAC-seq Peak Enrichment Analysis: Performs functional enrichment analysis of differentially accessible peaks from ATAC-seq data.
• GWAS Genetic Correlation Analysis: Reveals genetic correlations among phenotypes using GWAS summary statistics.

Scientific Applications:

• Gene Regulation Analysis: Characterizes functional roles of transcription factor binding sites identified by ChIP-seq.
• Chromatin Accessibility Studies: Identifies functional enrichment of regulatory elements from ATAC-seq accessible regions.
• Complex Trait Genetics: Investigates phenotype correlations and disease associations using GWAS summary statistics.

Methodology:

Re-GOA constructs a heterogeneous network integrating context-specific regulatory interactions, protein-protein interactions, and Gene Ontology (GO) terms. Network embedding maps nodes into a reduced-dimensional vector space, and similarity metrics associate regulatory elements with relevant GO terms to enable functional enrichment analysis.