title: De novo identification of differentially methylated regions in the human genome.
abstract: BACKGROUND
  The identification and characterisation of differentially methylated regions (DMRs) between phenotypes in the human genome is of prime interest in epigenetics. We present a novel method, DMRcate, that fits replicated methylation measurements from the Illumina HM450K BeadChip (or 450K array) spatially across the genome using a Gaussian kernel. DMRcate identifies and ranks the most differentially methylated regions across the genome based on tunable kernel smoothing of the differential methylation (DM) signal. The method is agnostic to both genomic annotation and local change in the direction of the DM signal, removes the bias incurred from irregularly spaced methylation sites, and assigns significance to each DMR called via comparison to a null model.
  
  
  RESULTS
  We show that, for both simulated and real data, the predictive performance of DMRcate is superior to those of Bumphunter and Probe Lasso, and commensurate with that of comb-p. For the real data, we validate all array-derived DMRs from the candidate methods on a suite of DMRs derived from whole-genome bisulfite sequencing called from the same DNA samples, using two separate phenotype comparisons.
  
  
  CONCLUSIONS
  The agglomeration of genomically localised individual methylation sites into discrete DMRs is currently best served by a combination of DM-signal smoothing and subsequent threshold specification. The findings also suggest the design of the 450K array shows preference for CpG sites that are more likely to be differentially methylated, but its overall coverage does not adequately reflect the depth and complexity of methylation signatures afforded by sequencing. For the convenience of the research community we have created a user-friendly R software package called DMRcate, downloadable from Bioconductor and compatible with existing preprocessing packages, which allows others to apply the same DMR-finding method on 450K array data.
authors.affiliation: CSIRO Digital Productivity Flagship, Riverside Life Sciences Centre, 11 Julius Avenue, North Ryde, New South Wales, 2113 Australia.
authors.forename: Timothy J
authors.initials: TJ
authors.lastname: Peters
authors.affiliation: CSIRO Digital Productivity Flagship, Riverside Life Sciences Centre, 11 Julius Avenue, North Ryde, New South Wales, 2113 Australia.
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Buckley
authors.affiliation: Epigenetics Program, Garvan Institute of Medical Research, Sydney, Australia.
authors.forename: Aaron L
authors.initials: AL
authors.lastname: Statham
authors.affiliation: Epigenetics Program, Garvan Institute of Medical Research, Sydney, Australia.
authors.forename: Ruth
authors.initials: R
authors.lastname: Pidsley
authors.affiliation: St Vincent's Hospital, Darlinghurst, New South Wales 2010 Australia.
authors.forename: Katherine
authors.initials: K
authors.lastname: Samaras
authors.affiliation: School of Medicine, University of Notre Dame, Darlinghurst, New South Wales 2010 Australia.
authors.forename: Reginald
authors.initials: R
authors.lastname: V Lord
authors.affiliation: Epigenetics Program, Garvan Institute of Medical Research, Sydney, Australia ; St Vincent's Clinical School, Faculty of Medicine, University of New South Wales, Darlinghurst, New South Wales 2010 Australia.
authors.forename: Susan J
authors.initials: SJ
authors.lastname: Clark
authors.affiliation: CSIRO Food and Nutrition Flagship, Riverside Life Sciences Centre, 11 Julius Avenue, Sydney, Australia.
authors.forename: Peter L
authors.initials: PL
authors.lastname: Molloy
keywords: Differential DNA methylation; Illumina; Kernel smoothing