| Literature DB >> 20548291 |
Alkes L Price1, Noah A Zaitlen, David Reich, Nick Patterson.
Abstract
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.Entities:
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Year: 2010 PMID: 20548291 PMCID: PMC2975875 DOI: 10.1038/nrg2813
Source DB: PubMed Journal: Nat Rev Genet ISSN: 1471-0056 Impact factor: 53.242