Approximate Bayesian bisulphite sequencing analysis

We present a Bayesian smoothing approach to detect differentially methylated regions from whole-genome bisulfite sequencing (WGBS) data. The method exploits the Integrated Nested Laplace Approximation for fast and accurate model fitting, an alternative to computationally expensive sampling-based methods. We demonstrate the approach by extensive simulation studies and WGBS of macrophages in experimental glomerulonephritis, revealing differential Ifitm3 promoter methylation in glomerulonephritis, supported by differential transcription factor binding and Ifitm3 gene expression.