title: Controlling bias and inflation in epigenome- and transcriptome-wide association studies using the empirical null distribution.
abstract: We show that epigenome- and transcriptome-wide association studies (EWAS and TWAS) are prone to significant inflation and bias of test statistics, an unrecognized phenomenon introducing spurious findings if left unaddressed. Neither GWAS-based methodology nor state-of-the-art confounder adjustment methods completely remove bias and inflation. We propose a Bayesian method to control bias and inflation in EWAS and TWAS based on estimation of the empirical null distribution. Using simulations and real data, we demonstrate that our method maximizes power while properly controlling the false positive rate. We illustrate the utility of our method in large-scale EWAS and TWAS meta-analyses of age and smoking.
authors.affiliation: Molecular Epidemiology section, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, the Netherlands. m.van_iterson@lumc.nl.
authors.forename: Maarten
authors.identifier: 0000-0002-8754-6158
authors.initials: M
authors.lastname: van Iterson
authors.affiliation: Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, the Netherlands.
authors.forename: Erik W
authors.initials: EW
authors.lastname: van Zwet
authors.affiliation: Molecular Epidemiology section, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, the Netherlands.
authors.forename: Bastiaan T
authors.initials: BT
authors.lastname: Heijmans
mesh_terms: D000367:Age Factors; D001499:Bayes Theorem; D015982:Bias; D044127:Epigenesis, Genetic; D057890:Epigenomics / Q000379:methods* / Q000592:standards; D055106:Genome-Wide Association Study / Q000379:methods*; D006801:Humans; D015201:Meta-Analysis as Topic; D012907:Smoking; D059467:Transcriptome
keywords: Bias; Empirical null distribution; Epigenome- and transcriptome-wide association studies; Gibbs sampler; Inflation; Meta-analysis