Skip to main content
SpringerLink
Log in

Comments on: Hierarchical inference for genome-wide association studies by Jelle J. Goeman and Stefan Böhringer

  • Discussion
  • Published:
Computational Statistics Aims and scope Submit manuscript

A Rejoinder to this article was published on 08 January 2020

The Original Article was published on 06 January 2020

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

References

  • Benner A, Zucknick M, Hielscher T, Ittrich C, Mansmann U (2010) High-dimensional cox models: the choice of penalty as part of the model building process. Biom J 52(1):50–69

    Article  MathSciNet  Google Scholar 

  • Boyle EA, Li YI, Pritchard JK (2017) An expanded view of complex traits: from polygenic to omnigenic. Cell 169(7):1177–1186

    Article  Google Scholar 

  • Meinshausen N (2008) Hierarchical testing of variable importance. Biometrika 95(2):265–278

    Article  MathSciNet  Google Scholar 

  • Park JH, Wacholder S, Gail MH, Peters U, Jacobs KB, Chanock SJ, Chatterjee N (2010) Estimation of effect size distribution from genome-wide association studies and implications for future discoveries. Nat Genet 42(7):570

    Article  Google Scholar 

  • Sullivan PF, Daly MJ, O’Donovan M (2012) Genetic architectures of psychiatric disorders: the emerging picture and its implications. Nat Rev Genet 13(8):537–551. https://doi.org/10.1038/nrg3240

    Article  Google Scholar 

  • Vukcevic D, Hechter E, Spencer C, Donnelly P (2011) Disease model distortion in association studies. Genet Epidemiol 35(4):278–290

    Google Scholar 

  • Wu MC, Lee S, Cai T, Li Y, Boehnke M, Lin X (2011) Rare-variant association testing for sequencing data with the sequence kernel association test. Am J Hum Genet 89(1):82–93

    Article  Google Scholar 

  • Yang J, Benyamin B, McEvoy BP, Gordon S, Henders AK, Nyholt DR, Madden PA, Heath AC, Martin NG, Montgomery GW (2010) Common SNPs explain a large proportion of the heritability for human height. Nat Genet 42(7):565

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Biomedical Data Sciences, Leiden University Medical Center, Postzone S5-P, Postbus 9600, 2300 RC, Leiden, The Netherlands

    Jelle J. Goeman & Stefan Böhringer

Authors
  1. Jelle J. Goeman
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Stefan Böhringer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jelle J. Goeman.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

JJG was supported by NWO VIDI Grant 639.072.412.

This comment refers to the invited paper available at: https://doi.org/10.1007/s00180-019-00939-2.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Goeman, J.J., Böhringer, S. Comments on: Hierarchical inference for genome-wide association studies by Jelle J. Goeman and Stefan Böhringer. Comput Stat 35, 41–45 (2020). https://doi.org/10.1007/s00180-019-00943-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00180-019-00943-6

Search

Navigation