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Improved linear mixed models for genome-wide association studies

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Acknowledgements

We thank J. Carlson for help with tools to manage and analyze the data and P. Palamara for cataloging the positions and genetic distances of SNPs in the data for Crohn's disease. This study makes use of data generated by the Wellcome Trust Case Control Consortium. A full list of the investigators who contributed to the generation of the data is available from http://www.wtccc.org.uk/. Funding for the project was provided by the Wellcome Trust under award 076113 and 085475. E.E. is supported by US National Science Foundation grants 0916676 and 1065276 and by US National Institutes of Health grants K25-HL080079, U01-DA024417, P01-HL30568 and PO1-HL28481.

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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

  2. Max Planck Institutes Tübingen, Tübingen, Germany

    Christoph Lippert

  3. Microsoft Research, Redmond, Washington, USA

    Carl M Kadie & Robert I Davidson

  4. University of California Los Angeles, Los Angeles, California, USA

    Eleazar Eskin

Authors
  1. Jennifer Listgarten
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  2. Christoph Lippert
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  3. Carl M Kadie
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  4. Robert I Davidson
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  5. Eleazar Eskin
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  6. David Heckerman
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Corresponding authors

Correspondence to Jennifer Listgarten, Christoph Lippert or David Heckerman.

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Competing interests

J.L., C.L., C.M.K., R.I.D. and D.H. performed research related to this manuscript while employed by Microsoft.

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Supplementary Figure 1, Supplementary Table 1, Supplementary Methods and Supplementary Notes 1-3 (PDF 1202 kb)

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Listgarten, J., Lippert, C., Kadie, C. et al. Improved linear mixed models for genome-wide association studies. Nat Methods 9, 525–526 (2012). https://doi.org/10.1038/nmeth.2037

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