A new approach for the visualization of DNA methylation results

Current software tools for analyzing the DNA methylation yield the results as text files whose sizes reach tens or hundreds of gigabytes, and they are not useful by themselves to biomedical researchers, who need to compare methylation information at different scales. Several tools for discovering differentially methylated regions have been proposed, but they are based on statistical techniques, requiring huge computations for finding differences in small DNA segments. In this paper, we propose a different strategy based on treating the DNA methylation as a signal. We propose to translate the DNA methylation results into a methylation signal, and the wavelet transformation of that signal for the displaying of the methylation results at the required scale. The results show that this approach not only yields the same visualization results than other existing tools, but it also yields signals with different resolution levels, which can be used to easily detect differentially methylated regions in much faster way than using statistical techniques.