Controlling bias and inflation in epigenome- and transcriptome-wide association studies using the empirical null distribution

Maarten van Iterson*, Erik W van Zwet, Bastiaan T Heijmans, Peter a.C ’t Hoen, Joyce B J van Meurs, Rick Jansen, Lude Franke, Dorret I. Boomsma, René Pool, Jenny van Dongen, Jouke J. Hottenga, Marleen J. Van Greevenbroek, Coen D A Stehouwer, Carla J H van der Kallen, Casper G Schalkwijk, Cisca Wijmenga, Sasha Zhernakova, Ettje F Tigchelaar, P. Eline Slagboom, Marian BeekmanJoris Deelen, Diana van Heemst, Jan H Veldink, Leonard H van den Berg, Cornelia M van Duijn, Bert A. Hofman, Aaron Isaacs, André G Uitterlinden, P Mila Jhamai, Michael Verbiest, H. Eka D. Suchiman, Marijn Verkerk, Ruud van der Breggen, Jeroen van Rooij, Nico Lakenberg, Hailiang Mei, Michiel van Galen, Jan Bot, Dasha V. Zhernakova, Peter van 't Hof, Patrick Deelen, Irene Nooren, Matthijs Moed, Martijn Vermaat, René Luijk, Marc Jan Bonder, Freerk van Dijk, Wibowo Arindrarto, Szymon M Kielbasa, Morris a. Swertz, Peter Bram 't Hoen

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

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.

Original languageEnglish
Article number19
JournalGenome Biology
Volume18
Issue number1
DOIs
Publication statusPublished - 27 Jan 2017

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Keywords

  • Bias
  • Empirical null distribution
  • Epigenome- and transcriptome-wide association studies
  • Gibbs sampler
  • Inflation
  • Meta-analysis

Cite this

van Iterson, M., van Zwet, E. W., Heijmans, B. T., ’t Hoen, P. A. C., van Meurs, J. B. J., Jansen, R., ... 't Hoen, P. B. (2017). Controlling bias and inflation in epigenome- and transcriptome-wide association studies using the empirical null distribution. Genome Biology, 18(1), [19]. https://doi.org/10.1186/s13059-016-1131-9