Higher order methylation features for clustering and prediction in epigenomic studies

@article{Kapourani2016HigherOM,
  title={Higher order methylation features for clustering and prediction in epigenomic studies},
  author={Chantriolnt-Andreas Kapourani and Guido Sanguinetti},
  journal={Bioinformatics},
  year={2016},
  volume={32 17},
  pages={i405-i412}
}
MOTIVATION DNA methylation is an intensely studied epigenetic mark, yet its functional role is incompletely understood. Attempts to quantitatively associate average DNA methylation to gene expression yield poor correlations outside of the well-understood methylation-switch at CpG islands. RESULTS Here, we use probabilistic machine learning to extract higher order features associated with the methylation profile across a defined region. These features quantitate precisely notions of shape of a… CONTINUE READING
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Higher order methylation features for clustering and prediction in epigenomic studies

  • Chantriolnt-Andreas Kapourani, Guido Sanguinetti
  • 2016

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