Revealing the missing heritability via cross-validated genome-wide association studies

TL;DR

This paper introduces a cross-validated GWAS method that improves phenotype prediction and uncovers significant missing heritability by identifying key loci, offering new insights into complex trait genetics.

Contribution

A simple cross-validated GWAS approach that effectively reveals missing heritability and enhances understanding of genetic architecture.

Findings

Identifies a small set of loci with predictive ability

Reveals substantial missing heritability in complex traits

Provides new insights into genetic architecture

Abstract

Presented here is a simple method for cross-validated genome-wide association studies (cvGWAS). Focusing on phenotype prediction, the method is able to reveal a significant amount of missing heritability by properly selecting a small number of loci with implicit predictive ability. The results provide new insights into the missing heritability problem and the underlying genetic architecture of complex traits.