Visualization of DNA methylation results through a GPU-based parallelization of the wavelet transform

Different statistical approaches have been proposed last years for finding differentially methylated DNA regions, starting from the outputs of DNA methylation analysis tools. However, these approaches do not allow an interactive and flexible exploration of these regions. Additionally, they add a hig...

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Bibliographic Details
Published in:The Journal of supercomputing 2019-03, Vol.75 (3), p.1496-1509
Main Authors: Fernández, Lisardo, Pérez, Mariano, Orduña, Juan M.
Format: Article
Language:English
Subjects:
Compilers
Computer Science
Deoxyribonucleic acid
DNA
DNA methylation
Interpreters
Parallel processing
Performance evaluation
Processor Architectures
Programming Languages
Visualization
Wavelet transforms
Workload
Workloads
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Summary:Different statistical approaches have been proposed last years for finding differentially methylated DNA regions, starting from the outputs of DNA methylation analysis tools. However, these approaches do not allow an interactive and flexible exploration of these regions. Additionally, they add a high computation workload when used with large datasets. In this paper, we propose a new approach consisting in the transformation of DNA methylation results into a methylation signal and the Haar wavelet transformation of that signal for the displaying of the methylation results at different scales. Additionally, we propose the parallelization of the Haar wavelet transform on the GPU, as well as the GPU-based visualization of the methylation signal. The performance evaluation results show that this is the first proposal which allows the interactive visualization of different methylation signals with different resolution levels, in such a way that it can be used to visually detect differentially methylated regions accurately, in a user-friendly and flexible way, and with a very low computational workload.
ISSN:0920-8542
1573-0484
DOI:10.1007/s11227-018-2670-5