On the cross-population generalizability of gene expression prediction models

Kevin L. Keys, Angel C.Y. Mak, Marquitta J. White, Walter L. Eckalbar, Andrew W. Dahl, Joel Mefford, Anna V. Mikhaylova, María G. Contreras, Jennifer R. Elhawary, Celeste Eng, Donglei Hu, Scott Huntsman, Sam S. Oh, Sandra Salazar, Michael A. Lenoir, Jimmie Chun Ye, Timothy A. Thornton, Noah Zaitlen, Esteban G. Burchard & Christopher R. Gignoux
The genetic control of gene expression is a core component of human physiology. For the past several years, transcriptome-wide association studies have leveraged large datasets of linked genotype and RNA sequencing information to create a powerful gene-based test of association that has been used in dozens of studies. While numerous discoveries have been made, the populations in the training data are overwhelmingly of European descent, and little is known about the generalizability of these models...
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