@article{
 title = {Use of unlinked genetic markers to detect population stratification in association studies},
 type = {article},
 year = {1999},
 identifiers = {[object Object]},
 keywords = {*Case-Control Studies,*Genetic Markers,*Linkage (Genetics),*Models, Genetic,Alleles,Genotype,Human,Research Design,Support, Non-U.S. Gov't,Support, U.S. Gov't, P.H.S.},
 pages = {220-8.},
 volume = {65},
 id = {b79d206a-a398-3b9a-8ad4-7f1e22c70cda},
 created = {2017-06-19T13:45:20.473Z},
 file_attached = {true},
 profile_id = {de68dde1-2ff3-3a4e-a214-ef424d0c7646},
 group_id = {b2078731-0913-33b9-8902-a53629a24e83},
 last_modified = {2017-06-19T13:45:20.613Z},
 tags = {02/11/15},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 source_type = {Journal Article},
 notes = {<m:note>eng<m:linebreak/>Journal Article</m:note>},
 abstract = {We examine the issue of population stratification in association-mapping studies. In case-control studies of association, population subdivision or recent admixture of populations can lead to spurious associations between a phenotype and unlinked candidate loci. Using a model of sampling from a structured population, we show that if population stratification exists, it can be detected by use of unlinked marker loci. We show that the case-control-study design, using unrelated control individuals, is a valid approach for association mapping, provided that marker loci unlinked to the candidate locus are included in the study, to test for stratification. We suggest guidelines as to the number of unlinked marker loci to use.},
 bibtype = {article},
 author = {Pritchard, J K and Rosenberg, N A},
 journal = {Am J Hum Genet},
 number = {1}
}

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