Journal home
Advance online publication
Current issue
Archive
Press releases
Free Association (blog)
Supplements
Focuses
Guide to authors
Online submissionOnline submission
For referees
Free online issue
Contact the journal
Subscribe
Advertising
work@npg
Reprints and permissions
About this site
For librarians
 
NPG Resources
Nature
Nature Biotechnology
Nature Cell Biology
Nature Medicine
Nature Methods
Nature Reviews Cancer
Nature Reviews Genetics
Nature Reviews Molecular Cell Biology
news@nature.com
Nature Conferences
RNAi Gateway
NPG Subject areas
Biotechnology
Cancer
Chemistry
Clinical Medicine
Dentistry
Development
Drug Discovery
Earth Sciences
Evolution & Ecology
Genetics
Immunology
Materials Science
Medical Research
Microbiology
Molecular Cell Biology
Neuroscience
Pharmacology
Physics
Browse all publications
Letter
Nature Genetics  36, 512 - 517 (2004)
Published online: 28 March 2004; | doi:10.1038/ng1337

The effects of human population structure on large genetic association studies

Jonathan Marchini1, Lon R Cardon2, Michael S Phillips3 & Peter Donnelly1

1  Department of Statistics, University of Oxford, 1 South Parks Road, Oxford OX1 3TG, UK.

2  Wellcome Trust Center for Human Genetics, University of Oxford, Oxford OX3 7BN, UK.

3  Genome Quebec and McGill University Genome Center, Montreal H3A 1A4, Canada.

Correspondence should be addressed to Peter Donnelly donnelly@stats.ox.ac.uk
Large-scale association studies hold substantial promise for unraveling the genetic basis of common human diseases. A well-known problem with such studies is the presence of undetected population structure, which can lead to both false positive results and failures to detect genuine associations. Here we examine approx15,000 genome-wide single-nucleotide polymorphisms typed in three population groups to assess the consequences of population structure on the coming generation of association studies. The consequences of population structure on association outcomes increase markedly with sample size. For the size of study needed to detect typical genetic effects in common diseases, even the modest levels of population structure within population groups cannot safely be ignored. We also examine one method for correcting for population structure (Genomic Control). Although it often performs well, it may not correct for structure if too few loci are used and may overcorrect in other settings, leading to substantial loss of power. The results of our analysis can guide the design of large-scale association studies.


 Top
Abstract
Previous | Next
Table of contents
Full textFull text
Download PDFDownload PDF
Send to a friendSend to a friend

natureevents

Figures & Tables
Supplementary info
Export citation
natureproducts

Search buyers guide:

 
ADVERTISEMENT
 
Nature Genetics
ISSN: 1061-4036
EISSN: 1546-1718
Journal home | Advance online publication | Current issue | Archive | Press releases | Supplements | Focuses | For authors | Online submission | Permissions | For referees | Free online issue | About the journal | Contact the journal | Subscribe | Advertising | work@npg | naturereprints | About this site | For librarians
Nature Publishing Group, publisher of Nature, and other science journals and reference works©2004 Nature Publishing Group | Privacy policy