FORGEPHAST: A fast, haplotype-first complex population and phenotype simulator for biobank-scale simulation

Authors

Gupta, H. V., Raj, S. M.

Abstract

Motivation: Simulation frameworks for statistical and population genetics often separate reference-panel genotype generation, admixture modeling, phenotype simulation, and scalable genomic storage. This limits construction and evaluation of large synthetic cohorts with controlled donor composition, local ancestry, and phenotype architecture. Results: We developed FORGEPHAST, a Python framework for reference-panel-based synthetic haplotype and phenotype generation. FORGEPHAST supports homogeneous mosaic and pulse-admixture generation from user-defined donor panels, integrated genotype quality control, and phenotype simulation with population- and local-ancestry-specific genetic effects. Its HapStore backend provides haplotype-native, Zarr-based storage for scalable numerical analysis. We demonstrate preservation of key donor-panel population-genetic properties and use FORGEPHAST to compare polygenic risk score methods across 54 simulated phenotypic architectures at biobank scales, showing that relative performance depends on phenotype architecture, ancestry, and implementation-specific variant coverage. Availability and implementation: FORGEPHAST is implemented in Python and is available as an open-source package at https://github.com/sriraj-lab/forgephast.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 06 Aug 2026.

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