title: D3M: detection of differential distributions of methylation levels.
abstract: DNA methylation is an important epigenetic modification related to a variety of diseases including cancers. We focus on the methylation data from Illumina's Infinium HumanMethylation450 BeadChip. One of the key issues of methylation analysis is to detect the differential methylation sites between case and control groups. Previous approaches describe data with simple summary statistics or kernel function, and then use statistical tests to determine the difference. However, a summary statistics-based approach cannot capture complicated underlying structure, and a kernel function-based approach lacks interpretability of results.
  
  
  
  We propose a novel method D(3)M, for detection of differential distribution of methylation, based on distribution-valued data. Our method can detect the differences in high-order moments, such as shapes of underlying distributions in methylation profiles, based on the Wasserstein metric. We test the significance of the difference between case and control groups and provide an interpretable summary of the results. The simulation results show that the proposed method achieves promising accuracy and shows favorable results compared with previous methods. Glioblastoma multiforme and lower grade glioma data from The Cancer Genome Atlas show that our method supports recent biological advances and suggests new insights.
  
  
  
  R implemented code is freely available from https://github.com/ymatts/D3M/ CONTACT: ymatsui@med.nagoya-u.ac.jp or shimamura@med.nagoya-u.ac.jp
  
  
  
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Nagoya University Graduate School of Medicine, Nagoya 466-8550, Japan.
authors.forename: Yusuke
authors.initials: Y
authors.lastname: Matsui
authors.affiliation: Information Initiative Center, Hokkaido University, Sapporo 060-0811, Japan.
authors.forename: Masahiro
authors.initials: M
authors.lastname: Mizuta
authors.affiliation: Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Japan.
authors.forename: Satoshi
authors.initials: S
authors.lastname: Ito
authors.affiliation: Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Japan.
authors.forename: Satoru
authors.initials: S
authors.lastname: Miyano
authors.affiliation: Nagoya University Graduate School of Medicine, Nagoya 466-8550, Japan.
authors.forename: Teppei
authors.initials: T
authors.lastname: Shimamura
mesh_terms: D000465:Algorithms; D019175:DNA Methylation; D006801:Humans; D009369:Neoplasms