diggit

diggit identifies genetic variants that drive cellular phenotypes in human diseases by prioritizing upstream genes using Driver-gene Inference by Genetical-Genomic Information Theory and de novo regulatory network inference.

Key Features:

• Systematic Discovery: Systematically discovers genetic alterations that are candidate causal determinants of human disease phenotypes.
• Prioritization of Genes: Prioritizes genes upstream of functional disease drivers within regulatory networks inferred de novo from experimental data.
• R-package Implementation: Implemented as an R-package exposing the DIGGIT algorithm for computational analysis.

Scientific Applications:

• Driver Mutation Identification: Identifying driver mutations that contribute to the progression of human diseases by prioritizing genes upstream of known disease drivers.
• Regulatory Network Analysis: Inferring and analyzing de novo regulatory networks to study complex gene interactions in disease contexts.

Methodology:

Employs Driver-gene Inference by Genetical-Genomic Information Theory and infers regulatory networks de novo from experimental data.