An empirical Bayes approach for multiple tissue eQTL analysis - PubMed (original) (raw)

An empirical Bayes approach for multiple tissue eQTL analysis

Gen Li et al. Biostatistics. 2018.

Abstract

Expression quantitative trait locus (eQTL) analyses identify genetic markers associated with the expression of a gene. Most up-to-date eQTL studies consider the connection between genetic variation and expression in a single tissue. Multi-tissue analyses have the potential to improve findings in a single tissue, and elucidate the genotypic basis of differences between tissues. In this article, we develop a hierarchical Bayesian model (MT-eQTL) for multi-tissue eQTL analysis. MT-eQTL explicitly captures patterns of variation in the presence or absence of eQTL, as well as the heterogeneity of effect sizes across tissues. We devise an efficient Expectation-Maximization (EM) algorithm for model fitting. Inferences concerning eQTL detection and the configuration of eQTL across tissues are derived from the adaptive thresholding of local false discovery rates, and maximum a posteriori estimation, respectively. We also provide theoretical justification of the adaptive procedure. We investigate the MT-eQTL model through an extensive analysis of a 9-tissue data set from the GTEx initiative.

PubMed Disclaimer

Figures

Cited by

Cross-species systems analysis identifies gene networks differentially altered by sleep loss and depression.
Scarpa JR, Jiang P, Gao VD, Fitzpatrick K, Millstein J, Olker C, Gotter A, Winrow CJ, Renger JJ, Kasarskis A, Turek FW, Vitaterna MH. Scarpa JR, et al. Sci Adv. 2018 Jul 25;4(7):eaat1294. doi: 10.1126/sciadv.aat1294. eCollection 2018 Jul. Sci Adv. 2018. PMID: 30050989 Free PMC article.
Trans-ancestry, Bayesian meta-analysis discovers 20 novel risk loci for inflammatory bowel disease in an African American, East Asian and European cohort.
Cordero RY, Cordero JB, Stiemke AB, Datta LW, Buyske S, Kugathasan S, McGovern DPB, Brant SR, Simpson CL. Cordero RY, et al. Hum Mol Genet. 2023 Feb 19;32(5):873-882. doi: 10.1093/hmg/ddac269. Hum Mol Genet. 2023. PMID: 36308435 Free PMC article.
Expression Quantitative Trait Loci Analysis in Multiple Tissues.
Li G. Li G. Methods Mol Biol. 2020;2082:231-237. doi: 10.1007/978-1-0716-0026-9_16. Methods Mol Biol. 2020. PMID: 31849019 Free PMC article.
Characterizing the Relation Between Expression QTLs and Complex Traits: Exploring the Role of Tissue Specificity.
Ip HF, Jansen R, Abdellaoui A, Bartels M; UK Brain Expression Consortium; Boomsma DI, Nivard MG. Ip HF, et al. Behav Genet. 2018 Sep;48(5):374-385. doi: 10.1007/s10519-018-9914-2. Epub 2018 Jul 20. Behav Genet. 2018. PMID: 30030655 Free PMC article.
Distributed eQTL analysis with auxiliary information.
Fang Z, Li G, Li W, Pu X, Xiang D. Fang Z, et al. J Stat Plan Inference. 2024 Jan;228:34-45. doi: 10.1016/j.jspi.2023.06.003. Epub 2023 Jun 28. J Stat Plan Inference. 2024. PMID: 38264292 Free PMC article.

References

1. Benjamini Y. and Hochberg Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological) 57, 289–300.
1. Benjamini Y. and Yekutieli D. (2001). The control of the false discovery rate in multiple testing under dependency. Annals of Statistics 29, 1165–1188.
1. Brown C. D., Mangravite L. M. and Engelhardt B. E. (2013). Integrative modeling of eQTLs and cis-regulatory elements suggests mechanisms underlying cell type specificity of eQTLs. PLoS Genetics 9, e1003649. - PMC - PubMed
1. Cai T. T. and Sun W. (2009). Simultaneous testing of grouped hypotheses: finding needles in multiple haystacks. Journal of the American Statistical Association 104, 1467–1481.
1. Dawson J. A. and Kendziorski C. (2012). An empirical Bayesian approach for identifying differential coexpression in high-throughput experiments. Biometrics 68, 455–465. - PMC - PubMed

An empirical Bayes approach for multiple tissue eQTL analysis - PubMed (original) (raw)