Nature Reviews Genetics 11, 459-463 (July 2010) | doi:10.1038/nrg2813

Article series: Genome-wide association studies

New approaches to population stratification in genome-wide association studies

Alkes L. Price1,2, Noah A. Zaitlen1,2, David Reich3 & Nick Patterson1  About the authors


Genome-wide association (GWA) studies are an effective approach for identifying genetic variants associated with disease risk. GWA studies can be confounded by population stratification — systematic ancestry differences between cases and controls — which has previously been addressed by methods that infer genetic ancestry. Those methods perform well in data sets in which population structure is the only kind of structure present but are inadequate in data sets that also contain family structure or cryptic relatedness. Here, we review recent progress on methods that correct for stratification while accounting for these additional complexities.

Author affiliations

  1. Alkes L. Price, Noah A. Zaitlen, David Reich and Nick Patterson are at the Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts 02142, USA.
  2. Alkes L. Price and Noah A. Zaitlen are also at the Department of Epidemiology and Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA.
  3. David Reich is also at the Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA.

Correspondence to: Alkes L. Price1,2 Email:

Published online 15 June 2010