IDEAS home Printed from
   My bibliography  Save this article

Detection of Differentially Methylated Regions Using Bayesian Curve Credible Bands


  • Jincheol Park

    (Keimyung University)

  • Shili Lin

    () (The Ohio State University)


Abstract DNA methylation is one of the most crucial epigenetic modifications involved in regulating gene transcription, cellular differentiation, development, and disease. In recent years, aided by fast parallel sequencing technology, a number of genome-wide bisulfite sequencing platforms have been developed to provide high-throughput DNA methylation data. These are essentially short reads that can be classified as methylated or unmethylated for a particular CpG site. Numerous sophisticated statistical methods have been developed to analyze such a massive amount of correlated data, but they are mainly for detecting differentially methylated loci (DMLs). To detect differentially methylated regions (DMRs), which are often more relevant biologically, a post-processing step from the identified DMLs is needed. In this paper, we address this shortcoming and other issues by proposing a latent variable Bayesian smoothing Curve (BCurve) method for detecting DMRs directly by means of constructing Bayesian credible intervals and bands. In addition to direct detection of DMRs, BCurve differs from existing methods in several other aspects, including its ability to accommodate between-sample variability, taking correlation of methylation levels among nearby loci into account when detecting DMRs, and the construction of credible bands (not just point estimates). We carried out an extensive simulation study to evaluate the performance of BCurve and to compare it with an existing method, BSmooth. The results show that BCurve outperforms BSmooth in all scenarios considered. Finally, we applied BCurve to a dataset to illustrate its utility in real data applications.

Suggested Citation

  • Jincheol Park & Shili Lin, 0. "Detection of Differentially Methylated Regions Using Bayesian Curve Credible Bands," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 0, pages 1-21.
  • Handle: RePEc:spr:stabio:v::y::i::d:10.1007_s12561-016-9171-y
    DOI: 10.1007/s12561-016-9171-y

    Download full text from publisher

    File URL:
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    1. ., 2014. "The Smithian inheritance," Chapters,in: Economists and the State, chapter 1 Edward Elgar Publishing.
    Full references (including those not matched with items on IDEAS)


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:stabio:v::y::i::d:10.1007_s12561-016-9171-y. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla) or (Rebekah McClure). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.