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

被引：8

作者：

Wen X. ^{[1
]}

机构：

[1] Department of Biostatistics, University of Michigan, Ann Arbor

来源：

Statistics in Biosciences | 2017年 / 9卷 / 1期

基金：

美国国家卫生研究院;

关键词：

False Discovery Rate; Null Model; eQTL Mapping; False Discovery Rate Control; False Discovery Rate Level;

D O I：

10.1007/s12561-016-9153-0

中图分类号：

学科分类号：

摘要：

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. © 2016, International Chinese Statistical Association.

引用

页码：28 / 49

页数：21

共 32 条

[1]

Barreiro L.B., Tailleux L., Pai A.A., Gicquel B., Marioni J.C., Gilad Y., Deciphering the genetic architecture of variation in the immune response to Mycobacterium tuberculosis infection, Proc Natl Acad Sci USA, 109, 4, pp. 1204-1209, (2012)

[2]

Benjamini Y., Hochberg Y., Controlling the false discovery rate: a practical and powerful approach to multiple testing, J R Stat Soc Ser B, 57, 1, pp. 289-300, (1995)

[3]

Cox D.R., Hinkley D., Theoretical statistics, (1979)

[4]

De la Cruz O., Wen X., Ke B., Song M., Nicolae D.L., Gene, region and pathway level analyses in whole-genome studies, Genet Epidemiol, 34, 3, pp. 222-231, (2010)

[5]

DiCiccio T.J., Kass R.E., Raftery A., Wasserman L., Computing Bayes factors by combining simulation and asymptotic approximations, J Am Stat Assoc, 92, 439, pp. 903-915, (1997)

[6]

Dimas A.S., Deutsch S., Stranger B.E., Montgomery S.B., Et al., Common regulatory variation impacts gene expression in a cell type-dependent manner, Science, 325, 5945, pp. 1246-1250, (2009)

[7]

Efron B., Tibshirani R., Storey J.D., Tusher V., Empirical bayes analysis of a microarray experiment, J Am Stat Assoc, 96, 456, pp. 1151-1160, (2001)

[8]

Flutre T., Wen X., Pritchard J., Stephens M., A statistical framework for joint eQTL analysis in multiple tissues, PLoS Genet, 9, 5, (2013)

[9]

Genovese C., Wasserman L., A stochastic process approach to false discovery control, Ann Stat, 32, 3, pp. 1035-1061, (2004)

[10]

Good I., The bayes/non-bayes compromise: a brief review, J Am Stat Assoc, 87, 419, pp. 597-606, (1992)

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