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Here we describe a simple and novel approach to locate genome-wide CNVs common to a specific population, using human ancestry as the phenotype.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>We utilized our previously published Genome Alteration Detection Analysis (GADA) algorithm to identify common ancestry CNVs (caCNVs) and built a caCNV model to predict population structure. We identified a 73 caCNV signature using a training set of 225 healthy individuals from European, Asian, and African ancestry. The signature was validated on an independent test set of 300 individuals with similar ancestral background. The error rate in predicting ancestry in this test set was 2% using the 73 caCNV signature. Among the caCNVs identified, several were previously confirmed experimentally to vary by ancestry. Our signature also contains a caCNV region with a single microRNA (<jats:italic>MIR270<\/jats:italic>), which represents the first reported variation of microRNA by ancestry.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p>We developed a new methodology to identify common CNVs and demonstrated its performance by building a caCNV signature to predict human ancestry with high accuracy. The utility of our approach could be extended to large case\u2013control studies to identify CNV signatures for other phenotypes such as disease susceptibility and drug response.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1471-2105-13-336","type":"journal-article","created":{"date-parts":[[2012,12,27]],"date-time":"2012-12-27T13:15:06Z","timestamp":1356614106000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Copy number variation signature to predict human ancestry"],"prefix":"10.1186","volume":"13","author":[{"given":"Melissa","family":"Pronold","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marzieh","family":"Vali","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Roger","family":"Pique-Regi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shahab","family":"Asgharzadeh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2012,12,27]]},"reference":[{"issue":"7319","key":"5711_CR1","doi-asserted-by":"publisher","first-page":"1061","DOI":"10.1038\/nature09534","volume":"467","author":"D Altshuler","year":"2010","unstructured":"Altshuler D, Durbin R, Abecasis G, Bentley D, Chakravarti A, Clark A, Collins F, De la Vega F, Donnelly P, Egholm M, et al.: A map of human genome variation from population-scale sequencing. 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