GPA-Tree: statistical approach for functional-annotation-tree-guided prioritization of GWAS results.

ABSTRACT:

Motivation

In spite of great success of genome-wide association studies (GWAS), multiple challenges still remain. First, complex traits are often associated with many single nucleotide polymorphisms (SNPs), each with small or moderate effect sizes. Second, our understanding of the functional mechanisms through which genetic variants are associated with complex traits is still limited. To address these challenges, we propose GPA-Tree and it simultaneously implements association mapping and identifies key combinations of functional annotations related to risk-associated SNPs by combining a decision tree algorithm with a hierarchical modeling framework.

Results

First, we implemented simulation studies to evaluate the proposed GPA-Tree method and compared its performance with ex

SUBMITTER: Khatiwada A 

PROVIDER: S-EPMC10060690 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature