2013•arXiv (Cornell University)Open access

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

Xia Shen

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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.

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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.

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Available 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.

Key concepts: Heritability, Missing heritability problem, Genetic architecture, Genome-wide association study, Genetic association, Missing data, Association (psychology), Biology

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