Journal article

Simultaneous Discovery, Estimation and Prediction Analysis of Complex Traits Using a Bayesian Mixture Model

Gerhard Moser, Sang Hong Lee, Ben J Hayes, Michael E Goddard, Naomi R Wray, Peter M Visscher

PLoS Genetics | PUBLIC LIBRARY SCIENCE | Published : 2015

Abstract

Gene discovery, estimation of heritability captured by SNP arrays, inference on genetic architecture and prediction analyses of complex traits are usually performed using different statistical models and methods, leading to inefficiency and loss of power. Here we use a Bayesian mixture model that simultaneously allows variant discovery, estimation of genetic variance explained by all variants and prediction of unobserved phenotypes in new samples. We apply the method to simulated data of quantitative traits and Welcome Trust Case Control Consortium (WTCCC) data on disease and show that it provides accurate estimates of SNP-based heritability, produces unbiased estimators of risk in new sampl..

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University of Melbourne Researchers

Grants

Awarded by National Institutes of Health


Awarded by Belgian Science Policy Office Interuniversity Attraction Poles (BELSPO-IAP) programme


Awarded by NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES


Funding Acknowledgements

This work was supported by grants P01 GM 099568 from the National Institutes of Health (to PMV) and IAP P7/43-BeMGI from the Belgian Science Policy Office Interuniversity Attraction Poles (BELSPO-IAP) programme (to PMV). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.