Roland Laboulaye

Jun 29, 2024 | biorxiv.org | Roland Laboulaye |Víctor Borda |Shuo Chen |Robert Kaplan

AbstractMotivation: Deep generative models have the potential to overcome difficulties in sharing individual-level genomic data by producing synthetic genomes that preserve the genomic associations specific to a cohort while not violating the privacy of any individual cohort member. However, there is significant room for improvement in the fidelity and usability of existing synthetic genome approaches.