Abstract
Using Bayesian adaptive shrinkage in the form of the normal-gamma prior we show that causal DNA sequence variants associated with a change in gene expression can be successfully detected. Taking a fully Bayesian approach allows our model to be developed to include uncertainty in gene expression and SNP calls and to include biological information from online databases.
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© 2014 Springer International Publishing Switzerland
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Boggis, E.M., Milo, M., Walters, K. (2014). Exploiting Adaptive Bayesian Regression Shrinkage to Identify Exome Sequence Variants Associated with Gene Expression. In: Lanzarone, E., Ieva, F. (eds) The Contribution of Young Researchers to Bayesian Statistics. Springer Proceedings in Mathematics & Statistics, vol 63. Springer, Cham. https://doi.org/10.1007/978-3-319-02084-6_26
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DOI: https://doi.org/10.1007/978-3-319-02084-6_26
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