@article {1230,
	title = {A new parallel pipeline for DNA methylation analysis of long reads datasets.},
	journal = {BMC bioinformatics},
	volume = {18},
	year = {2017},
	month = {2017 Mar 09},
	pages = {161},
	abstract = {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.},
	keywords = {Methyl-Seq, NGS},
	issn = {1471-2105},
	doi = {10.1186/s12859-017-1574-3},
	url = {http://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1574-3},
	author = {Olanda, Ricardo and P{\'e}rez, Mariano and Ordu{\~n}a, Juan M and T{\'a}rraga, Joaqu{\'\i}n and Joaqu{\'\i}n Dopazo}
}
