IDEAS home Printed from https://ideas.repec.org/a/bpj/sagmbi/v17y2018i5p8n1.html
   My bibliography  Save this article

Assessing genome-wide significance for the detection of differentially methylated regions

Author

Listed:
  • Page Christian M.
  • Harbo Hanne F.

    (Department of Neurology, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway)

  • Vos Linda
  • Rounge Trine B.
  • Andreassen Bettina K.

    (Department of Research, Cancer Registry of Norway, Oslo, Norway)

Abstract

DNA methylation plays an important role in human health and disease, and methods for the identification of differently methylated regions are of increasing interest. There is currently a lack of statistical methods which properly address multiple testing, i.e. control genome-wide significance for differentially methylated regions. We introduce a scan statistic (DMRScan), which overcomes these limitations. We benchmark DMRScan against two well established methods (bumphunter, DMRcate), using a simulation study based on real methylation data. An implementation of DMRScan is available from Bioconductor. Our method has higher power than alternative methods across different simulation scenarios, particularly for small effect sizes. DMRScan exhibits greater flexibility in statistical modeling and can be used with more complex designs than current methods. DMRScan is the first dynamic approach which properly addresses the multiple-testing challenges for the identification of differently methylated regions. DMRScan outperformed alternative methods in terms of power, while keeping the false discovery rate controlled.

Suggested Citation

  • Page Christian M. & Harbo Hanne F. & Vos Linda & Rounge Trine B. & Andreassen Bettina K., 2018. "Assessing genome-wide significance for the detection of differentially methylated regions," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 17(5), pages 1-8, October.
    • Handle: RePEc:bpj:sagmbi:v:17:y:2018:i:5:p:8:n:1
    DOI: 10.1515/sagmb-2017-0050
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/sagmb-2017-0050
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.1515/sagmb-2017-0050?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    References listed on IDEAS

    as
    1. D. O. Siegmund & N. R. Zhang & B. Yakir, 2011. "False discovery rate for scanning statistics," Biometrika, Biometrika Trust, vol. 98(4), pages 979-985.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yueying Wang & Guannan Wang & Li Wang & R. Todd Ogden, 2020. "Simultaneous confidence corridors for mean functions in functional data analysis of imaging data," Biometrics, The International Biometric Society, vol. 76(2), pages 427-437, June.
    2. Reiner-Benaim Anat & Davis Ronald W. & Juneau Kara, 2014. "Scan statistics analysis for detection of introns in time-course tiling array data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 13(2), pages 173-190, April.
    3. Anat Reiner-Benaim, 2016. "Scan Statistic Tail Probability Assessment Based on Process Covariance and Window Size," Methodology and Computing in Applied Probability, Springer, vol. 18(3), pages 717-745, September.

    Corrections

    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:bpj:sagmbi:v:17:y:2018:i:5:p:8:n:1. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.