Abstract
Motivation Identifying regions of the genome that demonstrate significant differences in DNA methylation between groups of samples is an important problem in computational epigenetics. Available methods assume that methylation occurs in a statistically independent manner at individual cytosine-phosphate-guanine (CpG) sites or perform analysis using empirically estimated joint probability distributions of methylation patterns at no more than 4 contiguous CpG sites. These approaches can lead to poor detection performance and loss of reliability and reproducibility due to reduced specificity and sensitivity in the presence of insufficient data.
Results To accommodate data obtained with different bisulfite sequencing technologies, such as RRBS, ERRBS, and WGBS, and improve statistical power, we developed CpelTdm.jl, a Julia package for targeted differential analysis of DNA methylation stochasticity between groups of unmatched or matched samples. This package performs rigorous statistical analysis of methylation patterns within regions of the genome specified by the user that takes into account correlations in methylation and results in robust detection of genomic regions exhibiting statistically significant differences in methylation stochasticity. CpelTdm.jl does not only detect mean methylation differences, as it is commonly done by previous methods, but also differences in methylation entropy and, more generally, between probability distributions of methylation.
Availability and Implementation This Julia package is supported for Windows, MacOS, and Linux, and can be freely downloaded from GitHub: https://github.com/jordiabante/CpelTdm.jl.
Contacts jabante1{at}jhu.edu or goutsias{at}jhu.edu.
Competing Interest Statement
The authors have declared no competing interest.
