RT Journal Article
SR Electronic
T1 Improving the computation efficiency of polygenic risk score modeling: faster in Julia
JF Life Science Alliance
JO Life Sci. Alliance
FD Life Science Alliance LLC
SP e202201382
DO 10.26508/lsa.202201382
VO 5
IS 12
A1 Annika Faucon
A1 Julian Samaroo
A1 Tian Ge
A1 Lea K Davis
A1 Nancy J Cox
A1 Ran Tao
A1 Megan M Shuey
YR 2022
UL https://www.life-science-alliance.org/content/5/12/e202201382.abstract
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.