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

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• 作者：Maarten van Iterson ; Erik W. van Zwet ; Bastiaan T. Heijmans
• 关键词：Epigenome ; and transcriptome ; wide association studies ; Bias ; Inflation ; Empirical null distribution ; Gibbs sampler ; Meta ; analysis
• 刊名：Genome Biology
• 出版年：2017
• 出版时间：December 2017
• 年：2017
• 卷：18
• 期：1
• 全文大小：1340KB
• 刊物主题：Animal Genetics and Genomics; Human Genetics; Plant Genetics & Genomics; Microbial Genetics and Genomics; Bioinformatics; Evolutionary Biology;
• 出版者：BioMed Central
• ISSN：1474-760X
• 卷排序：18

文摘

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.