NIH R01 · 2024
Statistical Methods for Data Integration and Applications to Genome-wide Association Studies
Abstract Large-scale epidemiologic studies, including biobanks and genome-wide association studies (GWAS), are now rapidly leading to the identification of novel risk factors for complex diseases. There is increasing opportunity to develop comprehensive models for disease risk incorporating genetic markers, other biomarkers, life-style factors and sociodemographic indicators. There are, however, major challenges as information on all of the potential risk factors are often not available in a single adequately large study. Instead, information may be available from different studies, each of which may include some subsets of the desired variables. Further, because of privacy concerns with…
From the public funding record at NIH RePORTER. Describes the funded project, not the reviews below.