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    Optimal multiple testing under a Gaussian prior on the effect sizes (2015)
    Oxford University Press
    Details
    Publication Date: 2015-11-28
    Description: We develop a new method for large-scale frequentist multiple testing with Bayesian prior information. We find optimal $p$ -value weights that maximize the average power of the weighted Bonferroni method. Due to the nonconvexity of the optimization problem, previous methods that account for uncertain prior information are suitable for only a small number of tests. For a Gaussian prior on the effect sizes, we give an efficient algorithm that is guaranteed to find the optimal weights nearly exactly. Our method can discover new loci in genome-wide association studies and compares favourably to competitors. An open-source implementation is available.
    Print ISSN: 0006-3444
    Electronic ISSN: 1464-3510
    Topics: Biology , Mathematics , Medicine
    Published by Oxford University Press
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