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Abundant associations with gene expression complicate GWAS follow-up

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Fig. 1: Distinguishing candidates from false-positive genes by using LocusCompare.

Data availability

A bash script to download all GWAS datasets is available at https://github.com/mikegloudemans/gwas-download. GTEx eQTL data can be accessed via https://gtexportal.org/home/datasets. Data for coronary artery smooth muscle cells are available at https://stanford.app.box.com/s/e6e8hyft5u7wix1nzg5mjfqa084c4tin. Data for retinal pigment epithelium cells are available at https://stanford.box.com/s/asrxy0o66xxe1j7mfj56p3z3d405gijj. Methylation QTL data for brain and blood are available at https://cnsgenomics.com/software/smr/#DataResource.

Code availability

LocusCompare is hosted at http://locuscompare.com and is also available as open source software at https://github.com/boxiangliu/locuscompare. LocusCompareR is open source and is available at https://github.com/boxiangliu/locuscomparer. Our pipeline for running colocalization tests is available at https://bitbucket.org/mgloud/production_coloc_pipeline/. The LocusCompareR package was built with R version 3.2.3.

References

  1. MacArthur, J. et al. Nucleic Acids Res. 45, D896–D901 (2017).

    Article  CAS  Google Scholar 

  2. Farh, K. K.-H. et al. Nature 518, 337–343 (2015).

    Article  CAS  Google Scholar 

  3. Battle, A., Brown, C. D., Engelhardt, B. E. & Montgomery, S. B. Nature 550, 204–213 (2017).

    Article  Google Scholar 

  4. Zhao, W. et al. Nat. Genet. 49, 1450–1457 (2017).

    Article  CAS  Google Scholar 

  5. Nica, A. C. et al. PLoS Genet. 6, e1000895 (2010).

    Article  Google Scholar 

  6. Hormozdiari, F. et al. Am. J. Hum. Genet. 99, 1245–1260 (2016).

    Article  CAS  Google Scholar 

  7. Zhu, Z. et al. Nat. Genet. 48, 481–487 (2016).

    Article  CAS  Google Scholar 

  8. Giambartolomei, C. et al. PLoS Genet. 10, e1004383 (2014).

    Article  Google Scholar 

  9. Liu, B. et al. Am. J. Hum. Genet. 103, 377–388 (2018).

    Article  CAS  Google Scholar 

  10. Liu, B. et al. Preprint at bioRxiv https://doi.org/10.1101/446799 (2018).

  11. Qi, T. et al. Nat. Commun. 9, 2282 (2018).

    Article  Google Scholar 

  12. Hannon, E. et al. Nat. Neurosci. 19, 48–54 (2016).

    Article  CAS  Google Scholar 

  13. McRae, A. F. et al. Sci. Rep. 8, 17605 (2018).

    Article  Google Scholar 

  14. Pruim, R. J. et al. Bioinformatics 26, 2336–2337 (2010).

    Article  CAS  Google Scholar 

  15. Benner, C. et al. Bioinformatics 32, 1493–1501 (2016).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

B.L. is supported by the Stanford Center for Evolution and Human Genomics fellowship and National Key R&D Program of China, 2016YFD0400800 and Baidu Research. M.J.G. is funded by NLM training grant T15 LM 007033 and a Stanford Graduate Fellowship. E.I. is supported by R01DK106236. S.B.M. is supported by R33HL120757 (NHLBI), U01HG009431 (NHGRI; ENCODE4), R01MH101814 (NIH Common Fund; GTEx Program), R01HG008150 (NHGRI; Non-Coding Variants Program), R01HL142015 (NHLBI; TOPMED), U01HG009080 (NHGRI; GSPAC) and the Edward Mallinckrodt Jr. Foundation. We acknowledge A. Shcherbina for support in this project and N. Cyr for support with graphical illustration.

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Authors and Affiliations

Authors

Contributions

B.L. and S.B.M. designed the study. B.L., M.J.G. and A.S.R. performed analyses. E.I. provided study support and feedback. B.L., M.J.G. and S.B.M. wrote the paper. B.L. and M.J.G. contributed equally to this work.

Corresponding authors

Correspondence to Boxiang Liu or Stephen B. Montgomery.

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Competing interests

S.B.M. is on the SAB of Prime Genomics.

Supplementary information

Supplementary Information

Supplementary Methods and Supplementary Figs. 1–6

Reporting Summary

Supplementary Tables 1 and 2

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Liu, B., Gloudemans, M.J., Rao, A.S. et al. Abundant associations with gene expression complicate GWAS follow-up. Nat Genet 51, 768–769 (2019). https://doi.org/10.1038/s41588-019-0404-0

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