Following the widespread use of deep learning for genomics, deep generative modeling is
also becoming a viable methodology for the broad field. Deep generative models (DGMs) …

Admixed individuals offer unique opportunities for addressing limited transferability in
polygenic scores (PGSs), given the substantial trans-ancestry genetic correlation in many …

Recent advancements in generative approaches in AI have opened up the prospect of
synthetic tabular clinical data generation. From filling in missing values in real-world data …

Ancestral recombination graphs (ARGs) encode the ensemble of correlated genealogical
trees arising from recombination in a compact and efficient structure, and are of fundamental …

In 1997, then-governor of Massachusetts Bill Weld received a nasty surprise in the mail: his
medical records, sent by computer scientist Latanya Sweeney. It was a stunt to demonstrate …

Objective The performances of popular genome-wide association study (GWAS) models
have not been examined yet in a consistent manner under the scenario of genetic …

Synthetic data generation via generative modeling has recently become a prominent
research field in genomics, with applications ranging from functional sequence design to …

For many genome-wide association studies, imputing genotypes from a haplotype reference
panel is a necessary step. Over the past 15 years, reference panels have become larger and …

Motivation Genome-wide association studies (GWAS) have been successful in identifying
genomic loci associated with complex traits. Genetic fine-mapping aims to detect …

In this paper, we introduce the first diffusion model designed to generate complete synthetic
human genotypes, which, by standard protocols, one can straightforwardly expand into full …