Lisardo Fernández

The study of Deoxyribonucleic Acid (DNA) methylation has allowed important advances in the understanding of genetic diseases related to abnormal cell behavior. DNA methylation analysis tools have become especially relevant in recent years. However, these tools have a high computational cost and some of them require the configuration of specific hardware and software, extending the time for research and diagnosis. In previous works, we proposed some tools for DNA methylation analysis and a new tool, called HPG-DHunter, for the detection and visualization of Differentially Methylated Regions (DMRs). Even though this tool offers a user-friendly interface, its installation and maintenance requires the information technology knowledge specified above. In this paper, we propose our tool as a web-based application, which allows biomedical researchers the use of a powerful tool for methylation analysis, even for those not specialized in the management of Graphics Processing Units (GPUs) and their related software. The performance evaluation results show that this web-based version of HPG-DHunter tool improves the response time offered to the user, also offering an improved interface and higher visualization quality, while showing the same efficiency in DMR identification than the standalone version.

Background: Software tools for analyzing DNA methylation do not provide graphical results which can be easily identified, but huge text files containing the alignment of the samples and their methylation status at a resolution of base pairs. There have been proposed different tools and methods for finding Differentially Methylated Regions (DMRs) among different samples, but the execution time required by these tools is large, and the visualization of their results is far from being interactive. Additionally, these methods show more accurate results when identifying simulated DM regions that are long and have small within-group variation, but they have low concordance when used with real datasets, probably due to the different approaches they use for DMR identification. Thus, a tool which automatically detects DMRs among different samples and interactively visualizes DMRs at different scales (from a bunch to ten of millions of DNA locations) can be the key for shortening the DNA methylation analysis process in many studies. Results: In this paper, we propose a software tool based on the wavelet transform. This mathematical tool allows the fast automatic DMR detection by simple comparison of different signals at different resolution levels. Also, it allows an interactive visualization of the DMRs found at different resolution levels. The tool is publicly available at https://grev-uv.github.io/, and it is part of a complete suite of tools which allow to carry out the complete process of DNA alignment and methylation analysis, creation of methylation maps of the whole genome, and the detection and visualization of DMRs between different samples. Conclusions: The validation of the developed software tool shows similar concordance with other well-known and extended tools when used with real and synthetic data. The batch mode of the tool is capable of automatically detecting the existing DMRs for half (twelve) of the human chromosomes between two sets of six samples (whose.csv files after the alignment and mapping procedures have an aggregated size of 108 Gigabytes) in around three hours and a half. When compared to other well-known tools, HPG-DHunter only requires around 15% of the execution time required by other tools for detecting the DMRs.