Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
Contradictory Results

Commentary on “Limitations of GCTA as a solution to the missing heritability problem”

Jian Yang, S. Hong Lee, Naomi R. Wray, Michael E. Goddard, Peter M. Visscher
doi: https://doi.org/10.1101/036574
Jian Yang
1Queensland Brain Institute, The University of Queensland, Brisbane, Queensland 4072, Australia
2The University of Queensland Diamantina Institute, The Translation Research Institute, Brisbane, Queensland 4102, Australia
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
S. Hong Lee
3School of Environmental and Rural Science, University of New England, Armidale, NSW 2351, Australia
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Naomi R. Wray
1Queensland Brain Institute, The University of Queensland, Brisbane, Queensland 4072, Australia
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Michael E. Goddard
4Faculty of Veterinary and Agricultural Science, University of Melbourne, Parkville, Victoria 3010, Australia
5Biosciences Research Division, Department of Economic Development, Jobs, Transport and Resources, Bundoora, Victoria 3083, Australia
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Peter M. Visscher
1Queensland Brain Institute, The University of Queensland, Brisbane, Queensland 4072, Australia
2The University of Queensland Diamantina Institute, The Translation Research Institute, Brisbane, Queensland 4102, Australia
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Abstract

In a recent publication entitled “Limitations of GCTA as a solution to the missing heritability problem” Krishna Kumar et al. (2015 PNAS) claim that “GCTA applied to current SNP data cannot produce reliable or stable estimates of heritability”. Here we show that those claims are false and that results presented by Krishna Kumar et al. are in fact entirely consistent with and can be predicted from the theory underlying GCTA.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted January 20, 2016.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Commentary on “Limitations of GCTA as a solution to the missing heritability problem”
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Commentary on “Limitations of GCTA as a solution to the missing heritability problem”
Jian Yang, S. Hong Lee, Naomi R. Wray, Michael E. Goddard, Peter M. Visscher
bioRxiv 036574; doi: https://doi.org/10.1101/036574
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
Commentary on “Limitations of GCTA as a solution to the missing heritability problem”
Jian Yang, S. Hong Lee, Naomi R. Wray, Michael E. Goddard, Peter M. Visscher
bioRxiv 036574; doi: https://doi.org/10.1101/036574

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Genetics
Subject Areas
All Articles
  • Animal Behavior and Cognition (3479)
  • Biochemistry (7318)
  • Bioengineering (5296)
  • Bioinformatics (20197)
  • Biophysics (9976)
  • Cancer Biology (7703)
  • Cell Biology (11250)
  • Clinical Trials (138)
  • Developmental Biology (6418)
  • Ecology (9916)
  • Epidemiology (2065)
  • Evolutionary Biology (13280)
  • Genetics (9352)
  • Genomics (12554)
  • Immunology (7674)
  • Microbiology (18939)
  • Molecular Biology (7417)
  • Neuroscience (40893)
  • Paleontology (298)
  • Pathology (1226)
  • Pharmacology and Toxicology (2126)
  • Physiology (3140)
  • Plant Biology (6838)
  • Scientific Communication and Education (1270)
  • Synthetic Biology (1891)
  • Systems Biology (5296)
  • Zoology (1085)