Changepoint detection in base-resolution methylome data reveals a robust signature of methylated domain landscape

Takao Yokoyama, Fumihito Miura, Hiromitsu Araki, Kohji Okamura, Takashi Ito

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Background: Base-resolution methylome data generated by whole-genome bisulfite sequencing (WGBS) is often used to segment the genome into domains with distinct methylation levels. However, most segmentation methods include many parameters to be carefully tuned and/or fail to exploit the unsurpassed resolution of the data. Furthermore, there is no simple method that displays the composition of the domains to grasp global trends in each methylome. Results: We propose to use changepoint detection for domain demarcation based on base-resolution methylome data. While the proposed method segments the methylome in a largely comparable manner to conventional approaches, it has only a single parameter to be tuned. Furthermore, it fully exploits the base-resolution of the data to enable simultaneous detection of methylation changes in even contrasting size ranges, such as focal hypermethylation and global hypomethylation in cancer methylomes. We also propose a simple plot termed methylated domain landscape (MDL) that globally displays the size, the methylation level and the number of the domains thus defined, thereby enabling one to intuitively grasp trends in each methylome. Since the pattern of MDL often reflects cell lineages and is largely unaffected by data size, it can serve as a novel signature of methylome. Conclusions: Changepoint detection in base-resolution methylome data followed by MDL plotting provides a novel method for methylome characterization and will facilitate global comparison among various WGBS data differing in size and even species origin.

Original languageEnglish
Article number594
JournalBMC genomics
Volume16
Issue number1
DOIs
Publication statusPublished - Aug 12 2015

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Genetics

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