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Robust Bayesian FDR Control Using Bayes Factors, with Applications to Multi-tissue eQTL Discovery

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  • Xiaoquan Wen

    (University of Michigan)

Abstract

Motivated by the genomic application of expression quantitative trait loci (eQTL) mapping, we propose a new procedure to perform simultaneous testing of multiple hypotheses using Bayes factors as input test statistics. One of the most significant features of this method is its robustness in controlling the targeted false discovery rate even under misspecifications of parametric alternative models. Moreover, the proposed procedure is highly computationally efficient, which is ideal for treating both complex system and big data in genomic applications. We discuss the theoretical properties of the new procedure and demonstrate its power and computational efficiency in applications of single-tissue and multi-tissue eQTL mapping.

Suggested Citation

  • Xiaoquan Wen, 2017. "Robust Bayesian FDR Control Using Bayes Factors, with Applications to Multi-tissue eQTL Discovery," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(1), pages 28-49, June.
    • Handle: RePEc:spr:stabio:v:9:y:2017:i:1:d:10.1007_s12561-016-9153-0
    DOI: 10.1007/s12561-016-9153-0
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    References listed on IDEAS

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    Cited by:

    1. Jingxiong Xu & Wei Xu & Laurent Briollais, 2021. "A Bayes factor approach with informative prior for rare genetic variant analysis from next generation sequencing data," Biometrics, The International Biometric Society, vol. 77(1), pages 316-328, March.

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