A comparison of reference-based algorithms for correcting cell-type heterogeneity in Epigenome-Wide Association Studies

作者：Andrew E. Teschendorff, Charles E. Breeze, Shijie Zheng, Stephan Beck · 发表于：BMC Bioinformatics · 年份：2017 · DOI：10.1186/s12859-017-1511-5 · 被引用次数：645 · 研究领域：Epigenetics and DNA Methylation、Single-cell and spatial transcriptomics、Genomics and Chromatin Dynamics

BACKGROUND: Intra-sample cellular heterogeneity presents numerous challenges to the identification of biomarkers in large Epigenome-Wide Association Studies (EWAS). While a number of reference-based deconvolution algorithms have emerged, their potential remains underexplored and a comparative evaluation of these algorithms beyond tissues such as blood is still lacking. RESULTS: Here we present a novel framework for reference-based inference, which leverages cell-type specific DNAse Hypersensitive Site (DHS) information from the NIH Epigenomics Roadmap to construct an improved reference DNA methylation database. We show that this leads to a marginal but statistically significant improvement of cell-count estimates in whole blood as well as in mixtures involving epithelial cell-types. Using this framework we compare a widely used state-of-the-art reference-based algorithm (called constrained projection) to two non-constrained approaches including CIBERSORT and a method based on robust partial correlations. We conclude that the widely-used constrained projection technique may not always be optimal. Instead, we find that the method based on robust partial correlations is generally more robust across a range of different tissue types and for realistic noise levels. We call the combined algorithm which uses DHS data and robust partial correlations for inference, EpiDISH (Epigenetic Dissection of Intra-Sample Heterogeneity). Finally, we demonstrate the added value of EpiDISH in an E...