Learning inherent genetic patterns and trait associations with deep generative models for discrete genotype simulation.

Abstract excerpt

BACKGROUND: Deep generative models open new avenues for simulating realistic genomic data while preserving privacy and addressing data accessibility constraints. While previous studies have primarily focused on generating gene expression or haplotype data, this study explores generating genotype data in both unconditioned and phenotype-conditioned settings, which is inherently more challenging due to the discrete...

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