Abstract DNA methylation analysis has become an important topic in the study of human health. In previous work, we developed a suite of tools to perform this analysis. It includes HPG-Dhunter, a web-based tool for automatic detection of differentially methylated regions (DMRs) between different samples. The back-end of that tool receives an undefined number of simultaneous requests to detect DMRs on different datasets. Currently, simultaneous requests are queued and processed one at a time. This paper proposes a parallel architecture where multiple daemons serve requests simultaneously. Daemons can also share the same physical GPUs. A scheduler manages requests and forwards them to daemons. The number of daemons per GPU is configurable, thus adapting the architecture to the available hardware. Results show that the proposed parallel architecture hugely reduces the execution time. Furthermore, the speedup increases proportionally to the number of available GPUs (up to 7.47x in our experimental setup).

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.

BACKGROUND: DNA methylation is an important mechanism of epigenetic regulation in development and disease. New generation sequencers allow genome-wide measurements of the methylation status by reading short stretches of the DNA sequence (Methyl-seq). Several software tools for methylation analysis have been proposed over recent years. However, the current trend is that the new sequencers and the ones expected for an upcoming future yield sequences of increasing length, making these software tools inefficient and obsolete. RESULTS: In this paper, we propose a new software based on a strategy for methylation analysis of Methyl-seq sequencing data that requires much shorter execution times while yielding a better level of sensitivity, particularly for datasets composed of long reads. This strategy can be exported to other methylation, DNA and RNA analysis tools. CONCLUSIONS: The developed software tool achieves execution times one order of magnitude shorter than the existing tools, while yielding equal sensitivity for short reads and even better sensitivity for long reads.

MOTIVATION: DNA methylation analysis suffers from very long processing time, as the advent of Next-Generation Sequencers has shifted the bottleneck of genomic studies from the sequencers that obtain the DNA samples to the software that performs the analysis of these samples. The existing software for methylation analysis does not seem to scale efficiently neither with the size of the dataset nor with the length of the reads to be analyzed. As it is expected that the sequencers will provide longer and longer reads in the near future, efficient and scalable methylation software should be developed. RESULTS: We present a new software tool, called HPG-Methyl, which efficiently maps bisulphite sequencing reads on DNA, analyzing DNA methylation. The strategy used by this software consists of leveraging the speed of the Burrows-Wheeler Transform to map a large number of DNA fragments (reads) rapidly, as well as the accuracy of the Smith-Waterman algorithm, which is exclusively employed to deal with the most ambiguous and shortest reads. Experimental results on platforms with Intel multicore processors show that HPG-Methyl significantly outperforms in both execution time and sensitivity state-of-the-art software such as Bismark, BS-Seeker or BSMAP, particularly for long bisulphite reads. AVAILABILITY AND IMPLEMENTATION: Software in the form of C libraries and functions, together with instructions to compile and execute this software. Available by sftp to [email protected] (password 'anonymous'). CONTACT: [email protected] or [email protected].

Last years have witnessed the widespread use of online terrain visualization applications. However, the significant improvements achieved in sensing technologies have allowed an increasing size of the terrain databases. These increasing sizes represent a serious drawback when terrain data must be transmitted and rendered at interactive rates. In this paper, we propose a novel wavelet-tiled pyramid for compressing terrain data that replaces the traditional multiresolution pyramid usually used in wavelet compression schemes. The new wavelet-tiled pyramid modifies the wavelet analysis and synthesis processes, allowing an efficient transmission and reconstruction of terrain data in those applications based on multiresolution tiled pyramids. A comparative performance evaluation with the currently existing techniques shows that the proposed scheme obtains a better compression ratio of the terrain data, reducing the storage space and transmission bandwidth required, and achieving a better visual quality of the virtual terrain reconstructed after data decompression.

This letter presents a new tiling scheme to achieve multiresolution and subregion image access as well as progressive retrieval, such as drill-down browsing and remote zooming/panning. This new scheme is based on the standard JPEG2000 algorithm. While JPEG2000 only divides the original image into tiles, the presented scheme divides each coarse version of the image into equal-sized tiles and reorders the wavelet coefficients in each of the steps of the analysis process. This new scheme avoids the problems associated with the traditional tiling, as used in JPEG2000, getting better lossy and lossless compression ratios, reducing disk or network latency, and improving the quality of the image.