IDEAS home Printed from https://ideas.repec.org/a/plo/pgen00/1006916.html
   My bibliography  Save this article

Statistical correction of the Winner’s Curse explains replication variability in quantitative trait genome-wide association studies

Author

Listed:
  • Cameron Palmer
  • Itsik Pe’er

Abstract

Genome-wide association studies (GWAS) have identified hundreds of SNPs responsible for variation in human quantitative traits. However, genome-wide-significant associations often fail to replicate across independent cohorts, in apparent inconsistency with their apparent strong effects in discovery cohorts. This limited success of replication raises pervasive questions about the utility of the GWAS field. We identify all 332 studies of quantitative traits from the NHGRI-EBI GWAS Database with attempted replication. We find that the majority of studies provide insufficient data to evaluate replication rates. The remaining papers replicate significantly worse than expected (p

Suggested Citation

  • Cameron Palmer & Itsik Pe’er, 2017. "Statistical correction of the Winner’s Curse explains replication variability in quantitative trait genome-wide association studies," PLOS Genetics, Public Library of Science, vol. 13(7), pages 1-18, July.
  • Handle: RePEc:plo:pgen00:1006916
    DOI: 10.1371/journal.pgen.1006916
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1006916
    Download Restriction: no

    File URL: https://journals.plos.org/plosgenetics/article/file?id=10.1371/journal.pgen.1006916&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pgen.1006916?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
    ---><---

    Citations

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


    Cited by:

    1. Zichen Zhang & Ye Eun Bae & Jonathan R. Bradley & Lang Wu & Chong Wu, 2022. "SUMMIT: An integrative approach for better transcriptomic data imputation improves causal gene identification," Nature Communications, Nature, vol. 13(1), pages 1-12, December.

    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:pgen00:1006916. 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: plosgenetics (email available below). General contact details of provider: https://journals.plos.org/plosgenetics/ .

    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.