Mixed-model association for biobank-scale datasets

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Fig. 1: Power, calibration and speed of BOLT-LMM v2.3 in UK Biobank analyses.

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Acknowledgements

We are grateful to H. Finucane and Y. Reshef for helpful discussions. This research was conducted using the UK Biobank Resource under application 10438 and was supported by US National Institutes of Health grants R01 HG006399, R01 GM105857 and R01 MH107649 (A.L.P.), a Burroughs Wellcome Fund Career Award at the Scientific Interfaces and the Next Generation Fund at the Broad Institute of MIT and Harvard (P.-R.L.), and a Boehringer Ingelheim Fonds fellowship (A.P.S.). Computational analyses were performed on the Orchestra High-Performance Compute Cluster at Harvard Medical School, which is partially supported by grant NCRR 1S10RR028832-01.

Author information

P.-R.L. and A.L.P. designed the study. P.-R.L., G.K., S.G. and A.P.S. performed analyses. All authors wrote the manuscript.

Correspondence to Po-Ru Loh or Alkes L. Price.

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The authors declare no competing interests.

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Supplementary Figures 1 and 2, Supplementary Tables 1–9 and Supplementary Note

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Loh, P., Kichaev, G., Gazal, S. et al. Mixed-model association for biobank-scale datasets. Nat Genet 50, 906–908 (2018). https://doi.org/10.1038/s41588-018-0144-6

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