GENS

GENS simulates complex interactions between genetic and environmental factors to generate biologically realistic datasets for studying multifactorial disease risk.

Key Features:

• Simulation of Interactions: Simulates interactions between two genetic factors and one environmental factor, including epistatic (gene-gene) interactions.
• Realistic Data Patterns: Generates data with realistic patterns of linkage disequilibrium.
• Scalability and Flexibility: Imposes no limitations on the number of simulated individuals or on the number of non-predisposing genetic and environmental factors.
• Input Parameterization: Expresses input parameters as standard epidemiological quantities.
• Implementation: Implemented in Python and leverages the simuPOP simulation environment's operators and modules.

Scientific Applications:

• Method benchmarking: Provides biologically realistic datasets with known interactions to assess performance of statistical methods for identifying gene-gene and gene-environment interactions.
• Complex disease research: Enables investigation of multifactorial disease etiology in human genetics, epidemiology, and bioinformatics.
• Risk modeling: Supports development and evaluation of models for disease risk prediction and prevention strategies that incorporate genetic and environmental factors.

Methodology:

Simulations model two genetic factors and one environmental factor with epistatic interactions, generate linkage disequilibrium patterns, accept epidemiological-quantity parameters, and are implemented in Python using simuPOP operators and modules without imposed limits on simulated individuals or non-predisposing factors.