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Exploring and visualizing large-scale genetic associations by using PheWeb

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Fig. 1: Interactive views of genetic associations in the UK Biobank instance of PheWeb.

Data availability

PheWeb fully embodies the philosophy of data and results sharing to advance scientific discoveries. PheWeb allows users to download full sets of summary statistics or subsets corresponding to the strongest association results. The summary statistics that populate the UK Biobank instance of PheWeb can be downloaded at ftp://share.sph.umich.edu/UKBB_SAIGE_HRC/.

The following links can be used to reproduce the images from Fig. 1: a, http://pheweb.sph.umich.edu/SAIGE-UKB/pheno/189.2; b, http://pheweb.sph.umich.edu/SAIGE-UKB/region/189.2/8:143552994-143952994; c, http://pheweb.sph.umich.edu/SAIGE-UKB/variant/8:143752994-T-C.

Code availability

PheWeb’s codebase is open source and hosted on GitHub at https://github.com/statgen/pheweb. Our pipeline for computing pairwise genetic correlations by using cross-trait LD Score regression10 or SumHer12 is scalable to large datasets and is available at https://github.com/statgen/pheweb-rg-pipeline. Additional information is provided in the Nature Research Reporting Summary.

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Acknowledgements

The UK Biobank genetic association summary statistics were generated previously by using the UK Biobank Resource through project ID number 24460. This research was supported by US National Institutes of Health grants HG009976 (M.B.) and HG007022 (G.R.A.).

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Author notes

  1. These authors contributed equally: Sarah A. Gagliano Taliun, Peter VandeHaar.

Authors and Affiliations

  1. Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA

    Sarah A. Gagliano Taliun, Peter VandeHaar, Andrew P. Boughton, Ryan P. Welch, Daniel Taliun, Ellen M. Schmidt, Wei Zhou, Cristen J. Willer, Seunggeun Lee, Lars G. Fritsche, Michael Boehnke & Gonçalo R. Abecasis

  2. Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA

    Sarah A. Gagliano Taliun, Peter VandeHaar, Andrew P. Boughton, Ryan P. Welch, Daniel Taliun, Ellen M. Schmidt, Seunggeun Lee, Lars G. Fritsche, Michael Boehnke & Gonçalo R. Abecasis

  3. Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA

    Wei Zhou & Cristen J. Willer

  4. Department of Internal Medicine, Division of Cardiology, University of Michigan Medical School, Ann Arbor, MI, USA

    Jonas B. Nielsen & Cristen J. Willer

  5. Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, NY, USA

    Gonçalo R. Abecasis

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  1. Sarah A. Gagliano Taliun
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  13. Gonçalo R. Abecasis
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Contributions

G.R.A. conceived the project. P.V. implemented the PheWeb software. A.P.B., R.P.W. and D.T. contributed additional key features to the software. S.A.G.T. drafted the initial manuscript and revised it according to coauthor input. S.A.G.T., P.V., A.P.B., R.P.W., D.T., E.M.S., L.G.F., M.B. and G.R.A. contributed to study design and/or direction. W.Z., J.B.N., S.A.G.T., C.J.W. and S.L. generated the UK Biobank association summary statistics. All authors reviewed the manuscript and suggested revisions. All authors approved the final manuscript.

Corresponding author

Correspondence to Gonçalo R. Abecasis.

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Competing interests

G.R.A. is an employee of Regeneron Pharmaceuticals; he owns stock and stock options for Regeneron Pharmaceuticals. The spouse of C.J.W. is employed at Regeneron Pharmaceuticals.

Additional information

Editorial Note: This article has been peer reviewed.

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Supplementary Information

Supplementary Note and Figs. 1–7

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Gagliano Taliun, S.A., VandeHaar, P., Boughton, A.P. et al. Exploring and visualizing large-scale genetic associations by using PheWeb. Nat Genet 52, 550–552 (2020). https://doi.org/10.1038/s41588-020-0622-5

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