graph-GPA 2.0: A Graphical Model for Multi-disease Analysis of GWAS Results with Integration of Functional Annotation Data

no code implementations • 14 Apr 2022 • Qiaolan Deng, Jin Hyun Nam, Ayse Selen Yilmaz, Won Chang, Maciej Pietrzak, Lang Li, Hang J. Kim, Dongjun Chung

These results demonstrate that GGPA 2. 0 can be a powerful tool to identify associated variants associated with each phenotype or those shared across multiple phenotypes, while also promoting understanding of functional mechanisms underlying the associated variants.

Literature Mining

GPA-Tree: Statistical Approach for Functional-Annotation-Tree-Guided Prioritization of GWAS Results

no code implementations • 12 Jun 2021 • Aastha Khatiwada, Bethany J. Wolf, Ayse Selen Yilmaz, Paula S. Ramos, Maciej Pietrzak, Andrew Lawson, Kelly J. Hunt, Hang J. Kim, Dongjun Chung

These results demonstrate that GPA-Tree can be a powerful tool that improves association mapping while facilitating understanding of the underlying genetic architecture of complex traits and potential mechanisms linking risk-associated SNPs with complex traits.