IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0042367.html
   My bibliography  Save this article

Improved Minimum Cost and Maximum Power Two Stage Genome-Wide Association Study Designs

Author

Listed:
  • Stephen A Stanhope
  • Andrew D Skol

Abstract

In a two stage genome-wide association study (2S-GWAS), a sample of cases and controls is allocated into two groups, and genetic markers are analyzed sequentially with respect to these groups. For such studies, experimental design considerations have primarily focused on minimizing study cost as a function of the allocation of cases and controls to stages, subject to a constraint on the power to detect an associated marker. However, most treatments of this problem implicitly restrict the set of feasible designs to only those that allocate the same proportions of cases and controls to each stage. In this paper, we demonstrate that removing this restriction can improve the cost advantages demonstrated by previous 2S-GWAS designs by up to 40%. Additionally, we consider designs that maximize study power with respect to a cost constraint, and show that recalculated power maximizing designs can recover a substantial amount of the planned study power that might otherwise be lost if study funding is reduced. We provide open source software for calculating cost minimizing or power maximizing 2S-GWAS designs.

Suggested Citation

  • Stephen A Stanhope & Andrew D Skol, 2012. "Improved Minimum Cost and Maximum Power Two Stage Genome-Wide Association Study Designs," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-10, September.
    • Handle: RePEc:plo:pone00:0042367
    DOI: 10.1371/journal.pone.0042367
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0042367
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0042367&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0042367?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
    ---><---

    References listed on IDEAS

    as
    1. Wang, Hansong & Stram, Daniel O., 2006. "Optimal two-stage genome-wide association designs based on false discovery rate," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 457-465, November.
    2. André Scherag & Johannes Hebebrand & Helmut Schäfer & Hans-Helge Müller, 2009. "Flexible Designs for Genomewide Association Studies," Biometrics, The International Biometric Society, vol. 65(3), pages 815-821, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yi-Hui Zhou & Paul Brooks & Xiaoshan Wang, 2018. "A Two-Stage Hidden Markov Model Design for Biomarker Detection, with Application to Microbiome Research," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 10(1), pages 41-58, April.

    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. Steibel, Juan P. & Rosa, Guilherme J.M. & Tempelman, Robert J., 2009. "Optimizing design of two-stage experiments for transcriptional profiling," Computational Statistics & Data Analysis, Elsevier, vol. 53(5), pages 1639-1649, March.

    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:plo:pone00:0042367. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.