HAPNEST

HAPNEST generates synthetic genotype and phenotype datasets for large-scale genetic analyses by producing individual-level genotypic and phenotypic data that preserve key statistical properties while controlling relatedness to reference panels.

Key Features:

• Scalability and Efficiency: Capable of producing synthetic datasets for up to 1 million individuals with faster computational performance compared to alternative methods.
• Statistical Fidelity: Preserves essential statistical properties of real genotype and phenotype data to support valid research analyses.
• Low Relatedness: Generates synthetic datasets with a lower degree of relatedness to existing reference panels to enhance dataset diversity.
• Versatility in Data Generation: Can simulate 6.8 million common variants and nine phenotypes with varying degrees of heritability and polygenicity.

Scientific Applications:

• Biobank-scale analyses: Facilitates comparison of methods for generating polygenic risk scores across multiple ancestry groups and varied genetic architectures.
• Benchmarking and method development: Provides synthetic data for evaluating synthetic data quality and benchmarking polygenic risk score methodologies for complex traits and diseases.

Methodology:

Implemented in Julia and C.