Polympact

Polympact characterizes and models interactions among common genetic variants to identify putative functional relationships relevant to complex disease genetics.

Key Features:

• Extensive Variant Characterization: Characterizes over 18 million common genetic variants as a basis for exploring functional interactions among variants.
• Functional Element Landscape Analysis: Leverages the landscape of functional elements associated with each variant to infer potential impacts on gene regulation.
• Transcription Factor Binding Motif Impact: Assesses how genetic variants affect transcription factor binding motifs to infer changes in gene expression regulation.
• Effect on Transcript Levels: Evaluates variant impacts on transcript levels of protein-coding genes to connect genetic variation to molecular outcomes.
• Network Models: Employs clustering analysis together with similarity and interaction network models to explore putative relations among variants.
• Application in Disease Research: Applied to large Genome-Wide Association Studies (GWAS) datasets for Breast Cancer and Alzheimer's disease to identify potential multi-variant interactions.

Scientific Applications:

• Interaction discovery in complex disease genetics: Uncovers interactions among common genetic variants that may contribute to complex disease etiology.
• Multi-layer genomic integration: Integrates genomic data layers — functional elements, transcription factor binding impacts, and transcript level changes — to prioritize variant functional effects.

Methodology:

Combines clustering techniques with similarity and interaction network models to analyze putative relations among variants.