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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
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Meta-analysis of candidate gene effects using bayesian parametric and non-parametric approaches

Xiao-Lin Wu1, Daniel Gianola2, Guilherme J M Rosa3

  • 11. Department of Dairy Science, University of Wisconsin, Madison, WI 53706, USA; ; 2. Department of Animal Sciences, University of Wisconsin, Madison, WI 53706, USA;

Journal of Genomics
|July 25, 2014
PubMed
Summary

Meta-analysis improves candidate gene studies for complex traits by pooling data. A non-parametric model using Dirichlet process priors better captures gene effect variations than parametric methods.

Keywords:
Bayesian modelsDirichlet process priorMarkov chain Monte Carlocandidate genesmeta-analysis.

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