MethCP: Differentially Methylated Region Detection with Change Point Models

  • Boying Gong
  • Elizabeth PurdomEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11467)


Whole-genome bisulfite sequencing (WGBS) provides a precise measure of methylation across the genome, yet presents a challenge in identifying regions that are differentially methylated (DMRs) between different conditions. Many methods have been developed, which focus primarily on the setting of two-group comparison. We develop a DMR detecting method MethCP for WGBS data, which is applicable for a wide range of experimental designs beyond the two-group comparisons, such as time-course data. MethCP identifies DMRs based on change point detection, which naturally segments the genome and provides region-level differential analysis. For simple two-group comparison, we show that our method outperforms developed methods in accurately detecting the complete DM region on a simulated dataset and an Arabidopsis dataset. Moreover, we show that MethCP is capable of detecting wide regions with small effect sizes, which can be common in some settings but existing techniques are poor in detecting such DMRs. We also demonstrate the use of MethCP for time-course data on another dataset following methylation throughout seed germination in Arabidopsis.

Availability: The package MethCP has been submitted to Bioconductor, and is currently available at


Differential methylation Bisulfite sequencing Change point detection 



This work has been supported in part by a DOE BER grant, DE-SC0014081.

Supplementary material


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Division of BiostatisticsUniversity of California, BerkeleyBerkeleyUSA
  2. 2.Department of StatisticsUniversity of California, BerkeleyBerkeleyUSA

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