HitWalker2

HitWalker2 prioritizes genetic variants by assessing their weighted proximity to functional assay results within protein-protein interaction networks to support variant interpretation for precision medicine and systems genetics.

Key Features:

• Visualization frameworks: Visualization frameworks that facilitate discovery and interpretation of genetic variants and network relationships.
• Implementation: Programmatic implementation using Python/Django backend, Neo4j graph database, and JavaScript libraries D3.js and jQuery, supporting reproducible analyses.
• Flexibility and Extensibility: Integrates diverse data types and supports multiple prioritization methods adaptable to specific research questions.

Scientific Applications:

• Precision Medicine: Prioritizes patient variants based on their weighted proximity to functional assay results within protein-protein interaction networks to inform individualized variant interpretation.
• Systems Genetics: Facilitates systems-level analyses by incorporating diverse data types and network relationships to analyze genetic interactions in complex diseases.
• Cancer Genomics: Applied to prioritize variants and interpret their network proximity to functional assay data in cancer genomics studies.
• Infectious Disease Studies: Used to prioritize variants and interpret genetic interactions relevant to infectious disease research.
• Psychiatric Disorder Research: Applicable to the prioritization and network-based interpretation of variants in psychiatric disorder research.

Methodology:

HitWalker2 prioritizes patient variants by assessing their weighted proximity to functional assay results within protein-protein interaction networks.