Seyoon Ko

The paper introduces HaploADMIXTURE, a method that uses haplotypes to estimate genetic admixture proportions, improving accuracy over SNP-based methods.

This paper introduces a penalized regression algorithm for multivariate GWAS using iterative hard thresholding, showing improved efficiency and reduced false positives compared to existing methods.

This paper introduces an unsupervised framework for selecting ancestry informative markers and estimating admixture proportions in large biobank datasets, demonstrating scalability and effectiveness.

MendelImpute.jl provides a fast, data-driven method for genotype imputation, phasing, and ancestry inference using linear algebra instead of hidden Markov models.

ParProx enables scalable multivariable regression analysis of ultrahigh-dimensional omics data using group lasso with biological priors, producing interpretable models.