Cell-type specific analysis of heterogeneous methylation signal using a Bayesian model-based approach

Motivation Epigenome-wide studies are often performed using heterogeneous methylation samples, especially when there is no prior information as to which cell-types are disease associated. While much work has been done in ascertaining cell-type fractions and removing cell-type heterogeneity variation, relatively little work has been done in identifying cell-type specific variation in heterogeneous samples. Results In this paper, we present a Bayesian model-based approach for making cell-type specific inferences in heterogeneous settings, by using a logit-Normal sampling distribution and incorporating a priori knowledge of cell-type lineage. The method is applied to the detection of cell-type specific sex effects in methylation, where cell-type information is present as an independent verification of the results. Panels derived from this method contained more loci where CD8+T, CD19+B and Natural Killer cell-types were differentially methylated. The analysis suggests that an ensemble approach with this method included could be used for discovering cell-type specific methylation changes. Availability https://github.com/danwkenn/Bayes_CDM