PT - JOURNAL ARTICLE AU - Annika Faucon AU - Julian Samaroo AU - Tian Ge AU - Lea K Davis AU - Nancy J Cox AU - Ran Tao AU - Megan M Shuey TI - Improving the computation efficiency of polygenic risk score modeling: faster in Julia AID - 10.26508/lsa.202201382 DP - 2022 Dec 01 TA - Life Science Alliance PG - e202201382 VI - 5 IP - 12 4099 - https://www.life-science-alliance.org/content/5/12/e202201382.short 4100 - https://www.life-science-alliance.org/content/5/12/e202201382.full SO - Life Sci. Alliance2022 Dec 01; 5 AB - To enable large-scale application of polygenic risk scores (PRSs) in a computationally efficient manner, we translate a widely used PRS construction method, PRS–continuous shrinkage, to the Julia programming language, PRS.jl. On nine different traits with varying genetic architectures, we demonstrate that PRS.jl maintains accuracy of prediction while decreasing the average runtime by 5.5×. Additional programmatic modifications improve usability and robustness. This freely available software substantially improves work flow and democratizes usage of PRSs by lowering the computational burden of the PRS–continuous shrinkage method.