An assessment of compositional methods for the analysis of DNA methylation-based deconvolution estimates.
Alexander AlsupEmily NissenLucas A SalasAnnette M MolinaroAlexander P ReinerSimin LiuTracy E MadsenLongjian LiuPaul L AuerBrock C ChristensenJohn K WienckeKarl T KelseyDevin C KoestlerPublished in: Epigenomics (2024)
DNA methylation (DNAm)-based deconvolution estimates contain relative data, forming a composition, that standard methods (testing directly on cell proportions) are ill-suited to handle. In this study we examined the performance of an alternative method, analysis of compositions of microbiomes (ANCOM), for the analysis of DNAm-based deconvolution estimates. We performed two different simulation studies comparing ANCOM to a standard approach (two sample t -test performed directly on cell proportions) and analyzed a real-world data from the Women's Health Initiative to evaluate the applicability of ANCOM to DNAm-based deconvolution estimates. Our findings indicate that ANCOM can effectively account for the compositional nature of DNAm-based deconvolution estimates. ANCOM adequately controls the false discovery rate while maintaining statistical power comparable to that of standard methods.