Bayesian tool for methylation analysis

It can be applied to large datasets generated using either oligonucleotide arrays (MeDIP-chip) or next-generation sequencing (MeDIP-seq), providing a quantitative estimation of absolute methylation state in a region of interest.

In this way Batman converts the signals from MeDIP experiments to absolute methylation levels.

The core principle of the Batman algorithm is to model the effects of varying density of CpG dinucleotides, and the effect this has on MeDIP enrichment of DNA fragments.

The basic assumptions of Batman: Basic parameters in Batman: Based on these assumptions, the signal from the MeDIP channel of the MeDIP-chip or MeDIP-seq experiment depends on the degree of enrichment of DNA fragments overlapping that probe, which in turn depends on the amount of antibody binding, and thus to the number of methylated CpGs on those fragments.

Standard Bayesian techniques can be used to infer f(m|A), that is, the distribution of likely methylation states given one or more sets of MeDIP-chip/MeDIP-seq outputs.