David Bonet

This study uses multi-ancestry admixture mapping in the UK Biobank to identify ancestry-associated disease loci, finding 13 genome-wide significant associations and four novel risk loci.

ARGformer uses transformers to learn embeddings from ancestral recombination graphs, enabling population structure analysis and ancestry inference without genotype data.

ARGMix uses a graph transformer to infer local ancestry from ancient DNA, showing continuity between Otzi the Iceman and present-day Europeans.

This paper introduces Combine, a framework for polygenic prediction in admixed populations using local ancestry and group lasso, showing improved performance over existing methods.

snputils provides a high-performance Python library for handling genetic variation and population structure data, improving efficiency and integration in genomic research.

The paper analyzes a Mexican FH cohort to show rare and common alleles in FH genes and a novel locus contribute to disease risk, with replication in UK Biobank.

This paper introduces a machine learning toolkit to improve phenotype prediction accuracy for underrepresented populations using SNP data from diverse genomic datasets.