PT - JOURNAL ARTICLE AU - E. Andres Houseman AU - Molly L. Kile AU - David C. Christiani AU - Tan A. Ince AU - Karl T. Kelsey AU - Carmen J. Marsit TI - Reference-free deconvolution of DNA methylation data and mediation by cell composition effects AID - 10.1101/037671 DP - 2016 Jan 01 TA - bioRxiv PG - 037671 4099 - http://biorxiv.org/content/early/2016/01/23/037671.short 4100 - http://biorxiv.org/content/early/2016/01/23/037671.full AB - We propose a simple method for reference-free deconvolution that provides both proportions of putative cell types defined by their underlying methylomes, the number of these constituent cell types, as well as a method for evaluating the extent to which the underlying methylomes reflect specific types of cells. We have demonstrated these methods in an analysis of 23 Infinium data sets from 13 distinct data collection efforts; these empirical evaluations show that our algorithm can reasonably estimate the number of constituent types, return cell proportion estimates that demonstrate anticipated associations with underlying phenotypic data; and methylomes that reflect the underlying biology of constituent cell types. Thus the methodology permits an explicit quantitation of the mediation of phenotypic associations with DNA methylation by cell composition effects. Although more work is needed to investigate functional information related to estimated methylomes, our proposed method provides a novel and useful foundation for conducting DNA methylation studies on heterogeneous tissues lacking reference data.