Winners curse correction and variable thresholding improve performance of polygenic risk modeling based on summary-level data from genome-wide association studies
Jianxin Shi, Ju-Hyun Park, Jubao Duan, Sonja Berndt, Winton Moy, Kai Yu, Lei Song, William Wheeler, Xing Hua, Debra Silverman, Montserrat Garcia-Closas, Chao Agnes Hsiung, Jonine D Figueroa, Victoria K Cortessis, Núria Malats, , Nilanjan Chatterjee
This paper improves polygenic risk scores by applying winners curse correction and variable thresholds to GWAS summary data, enhancing prediction accuracy for some diseases.
bioRxiv · Jan 10, 2016 · PreprintGenetics