Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Correspondence
  • Published:

FaST-LMM-Select for addressing confounding from spatial structure and rare variants

Nature Genetics volume 45, pages 470–471 (2013)Cite this article

Subjects

To the Editor:

A recent report by Mathieson and McVean1 showed that confounding in genome-wide association studies (GWAS) resulting from spatially structured populations in conjunction with rare variants could not be corrected by currently available statistical genetics methods. In particular, when simulating that the non-genetic cause of disease arose from a sharply defined spatial region, genomic control2, principal-component analysis (PCA)3 and linear mixed models (LMMs)4,5 all failed to correct for stratification, resulting in systematically inflated test statistics1. Although several research avenues were proposed as possible solutions to the problem1, none has so far been shown to work. Additionally, it was speculated that any method that could correct for such confounding would require fine-grained geographic information1.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Comparison of three methods for genome-wide association analyses in the presence of confounding due to spatial structure and rare variants.

References

  1. Mathieson, I. & McVean, G. Nat. Genet. 44, 243–246 (2012).

    Article  CAS  Google Scholar 

  2. Devlin, B. & Roeder, K. Biometrics 55, 997–1004 (1999).

    Article  CAS  Google Scholar 

  3. Price, A.L. et al. Nat. Genet. 38, 904–909 (2006).

    Article  CAS  Google Scholar 

  4. Kang, H.M. et al. Nat. Genet. 42, 348–354 (2010).

    Article  CAS  Google Scholar 

  5. Lippert, C. et al. Nat. Methods 8, 833–835 (2011).

    Article  CAS  Google Scholar 

  6. Listgarten, J. et al. Nat. Methods 9, 525–526 (2012).

    Article  CAS  Google Scholar 

  7. Lippert, C., Quon, G., Listgarten, J. & Heckerman, D. Sci. Rep. (in the press).

  8. Hayes, B.J., Visscher, P.M. & Goddard, M.E. Genet. Res. 91, 47–60 (2009).

    Article  CAS  Google Scholar 

  9. Yu, J. et al. Nat. Genet. 38, 203–208 (2006).

    Article  CAS  Google Scholar 

  10. Agresti, A. Categorical Data Analysis (Wiley, New York, 2002).

    Book  Google Scholar 

Download references

Author information

Author notes

  1. Jennifer Listgarten, Christoph Lippert and David Heckerman: These authors contributed equally to this work.

Authors and Affiliations

  1. Microsoft Research, Los Angeles, California, USA

    Jennifer Listgarten, Christoph Lippert & David Heckerman

Authors
  1. Jennifer Listgarten
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Christoph Lippert
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. David Heckerman
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Jennifer Listgarten, Christoph Lippert or David Heckerman.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Listgarten, J., Lippert, C. & Heckerman, D. FaST-LMM-Select for addressing confounding from spatial structure and rare variants. Nat Genet 45, 470–471 (2013). https://doi.org/10.1038/ng.2620

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ng.2620

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing