Abstract
DNA methylation (mC) and hydroxymethylation (hmC) can have a significant effect on normal human development, health and disease status. Hydroxymethylation studies require specific treatment of DNA, as well as software tools for their analysis. In this paper, we propose a parallel software tool for analyzing the DNA hydroxymethylation data obtained by TAB-seq. The software is based on the use of binary trees for searching the different occurrences of methylation and hydroxymethylation in DNA samples. The binary trees allow to efficiently store and access the information about the methylation of each methylated/hydroxymethylated cytosines in the samples. Evaluation results shows that the performance of the application is only limited by the computer input/output bandwidth, even for the case of very long samples.
This work has been supported by Spanish MINECO and EU FEDER funds under grants TIN2015-66972-C5-5-R, TIN2016-81850-REDC, PI14/00874 and CIBERDEM (Carlos III Health Institute).
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González, C., Pérez, M., Orduña, J.M., Chaves, J., García, AB. (2017). On the Use of Binary Trees for DNA Hydroxymethylation Analysis. In: Ibrahim, S., Choo, KK., Yan, Z., Pedrycz, W. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2017. Lecture Notes in Computer Science(), vol 10393. Springer, Cham. https://doi.org/10.1007/978-3-319-65482-9_37
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DOI: https://doi.org/10.1007/978-3-319-65482-9_37
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