A Bayesian model-based approach to finding cell-type level associations in heterogeneous methylation samples

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• Daniel Kennedy, Queensland University of Technology
• Thursday 14 September 2017, 14:30-15:30
• Small Seminar Room, 1st Floor, Institute of Public Health, University Forvie Site, Robinson Way, Cambridge.

If you have a question about this talk, please contact Alison Quenault.

Epigenome-wide association 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 on estimating cell-type fractions and removing cell-type heterogeneity variation, relatively little work has been done on identifying cell-type

specific variation in heterogeneous samples. In this talk I present a Bayesian model-based approach for making cell-type specific inferences in heterogeneous settings, by utilising a logistic transform to properly constrain parameters, and incorporating a prior knowledge of cell-type lineage via prior covariance structure. The approach was applied to the determination of sex-specific cell-type effects in methylation, where cell-type information was present as an independent verification of the results. The approach showed significant improvement in performance over previously used methods, particularly for detecting association in several rare cell-types. I outline current and future work on this problem, which leverages the flexibility of the Bayesian modelling approach by incorporating local methylation correlation and multiple data-types.

This talk is part of the MRC Biostatistics Unit Seminars series.

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