De Los Campos Lab

Research focus

NIH R01 · 2024

Improving PGS Prediction for Underrepresented Groups Through Transfer Learning

In the last two decades, thousands of Genome-Wide Association Studies (GWAS) have been published. Increasingly, the findings reported by these studies inform the development of Polygenic Scores (PGS) that can be used to predict phenotypes and disease risk. The Polygenic Scores Catalog includes more than 3,700 PGS. However, the overwhelming majority of the PGS were derived using data from Europeans and have poor predictive performance when used to predict phenotypes of individuals of non-European ancestry. Transfer Learning (TL) is a technique by which knowledge gained in one data set is used to improve the model’s performance in another data set. Our overarching goal is to develop novel TL…

From the public funding record at NIH RePORTER. Describes the funded project, not the reviews below.