IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v40y2013i2p347-357.html
   My bibliography  Save this article

Empirical null distribution-based modeling of multi-class differential gene expression detection

Author

Listed:
  • Xiting Cao
  • Baolin Wu
  • Marshall I. Hertz

Abstract

In this paper, we study the multi-class differential gene expression detection for microarray data. We propose a likelihood-based approach to estimating an empirical null distribution to incorporate gene interactions and provide a more accurate false-positive control than the commonly used permutation or theoretical null distribution-based approach. We propose to rank important genes by p -values or local false discovery rate based on the estimated empirical null distribution. Through simulations and application to lung transplant microarray data, we illustrate the competitive performance of the proposed method.

Suggested Citation

  • Xiting Cao & Baolin Wu & Marshall I. Hertz, 2013. "Empirical null distribution-based modeling of multi-class differential gene expression detection," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(2), pages 347-357, February.
    • Handle: RePEc:taf:japsta:v:40:y:2013:i:2:p:347-357
    DOI: 10.1080/02664763.2012.743976
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02664763.2012.743976
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/02664763.2012.743976?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.

    More about this item

    Statistics

    Access and download statistics

    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:taf:japsta:v:40:y:2013:i:2:p:347-357. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    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.