Based on an extensive simulation study, McGregor and colleagues recently recommended the use of surrogate variable analysis (SVA) to control for the confounding effects of cell-type heterogeneity in DNA methylation association studies in scenarios where no cell-type proportions are available. As their recommendation was mainly based on simulated data, we sought to replicate findings in two large-scale empirical studies. In our empirical data, SVA did not fully correct for cell-type effects, its performance was somewhat unstable, and it carried a risk of missing true signals caused by removing variation that might be linked to actual disease processes. By contrast, a reference-based correction method performed well and did not show these limitations. A disadvantage of this approach is that if reference methylomes are not (publicly) available, they will need to be generated once for a small set of samples. However, given the notable risk we observed for cell-type confounding, we argue that, to avoid introducing false-positive findings into the literature, it could be well worth making this investment. Please see related Correspondence article: https://genomebiology.biomedcentral.com/articles/10/1186/s13059-017-1149-7and related Research article: https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0935-y
CITATION STYLE
Hattab, M. W., Shabalin, A. A., Clark, S. L., Zhao, M., Kumar, G., Chan, R. F., … van den Oord, E. J. C. G. (2017, January 30). Correcting for cell-type effects in DNA methylation studies: Reference-based method outperforms latent variable approaches in empirical studies. Genome Biology. BioMed Central Ltd. https://doi.org/10.1186/s13059-017-1148-8
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