{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T13:20:33Z","timestamp":1740144033819,"version":"3.37.3"},"reference-count":34,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2019,3,13]],"date-time":"2019-03-13T00:00:00Z","timestamp":1552435200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"Federal Ministry of Education and Research Germany","award":["01KT1510"],"award-info":[{"award-number":["01KT1510"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,5,21]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Population stratification is usually corrected relying on principal component analysis (PCA) of genome-wide genotype data, even in populations considered genetically homogeneous, such as Europeans. The need to genotype only a small number of genetic variants that show large differences in allele frequency among subpopulations\u2014so-called ancestry-informative markers (AIMs)\u2014instead of the whole genome for stratification adjustment could represent an advantage for replication studies and candidate gene\/pathway studies. Here we compare the correction performance of classical and robust principal components (PCs) with the use of AIMs selected according to four different methods: the informativeness for assignment measure ($IN$-AIMs), the combination of PCA and F-statistics, PCA-correlated measurement and the PCA weighted loadings for each genetic variant. We used real genotype data from the Population Reference Sample and The Cancer Genome Atlas to simulate European genetic association studies and to quantify type I error rate and statistical power in different case\u2013control settings.<\/jats:p>\n               <jats:p>In studies with the same numbers of cases and controls per country and control-to-case ratios reflecting actual rates of disease prevalence, no adjustment for population stratification was required. The unnecessary inclusion of the country of origin, PCs or AIMs as covariates in the regression models translated into increasing type I error rates. In studies with cases and controls from separate countries, no investigated method was able to adequately correct for population stratification. The first classical and the first two robust PCs achieved the lowest (although inflated) type I error, followed at some distance by the first eight $IN$-AIMs.<\/jats:p>","DOI":"10.1093\/bib\/bbz023","type":"journal-article","created":{"date-parts":[[2019,2,25]],"date-time":"2019-02-25T20:13:15Z","timestamp":1551125595000},"page":"753-761","source":"Crossref","is-referenced-by-count":2,"title":["Optimal selection of genetic variants for adjustment of population stratification in European association studies"],"prefix":"10.1093","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5731-173X","authenticated-orcid":false,"given":"Regina","family":"Brinster","sequence":"first","affiliation":[{"name":"Institute of Medical Biometry and Informatics, University of Heidelberg, Im Neuenheimer Feld 130.3, Heidelberg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dominique","family":"Scherer","sequence":"first","affiliation":[{"name":"Institute of Medical Biometry and Informatics, University of Heidelberg, Im Neuenheimer Feld 130.3, Heidelberg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6568-5333","authenticated-orcid":false,"given":"Justo","family":"Lorenzo Bermejo","sequence":"first","affiliation":[{"name":"Institute of Medical Biometry and Informatics, University of Heidelberg, Im Neuenheimer Feld 130.3, Heidelberg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2019,3,13]]},"reference":[{"key":"2020051819180890700_ref1","doi-asserted-by":"crossref","first-page":"781","DOI":"10.1038\/nrg1916","article-title":"A tutorial on statistical methods for population association studies","volume":"7","author":"Balding","year":"2006","journal-title":"Nat Rev Genet"},{"key":"2020051819180890700_ref2","doi-asserted-by":"crossref","first-page":"868","DOI":"10.1038\/ng1607","article-title":"Demonstrating stratification in 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