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. 2022 Aug 29;12:14683. doi: 10.1038/s41598-022-14395-4

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© The Author(s) 2022

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Evaluating the accuracy of PCA clustering for a heterogeneous test population in a simulation of a GWAS setting. (A) The true distribution of the test Cyan population (n = 1000). (B) PCA of the test population with eight even-sized (n = 250) samples from reference populations. (C) PCA of the test population with Blue from the previous analysis shows a minimal overlap between the cohorts. (D) PCA of the test population with five even-sized (n = 250) samples from reference populations, including Cyan (marked by an arrow). Colors (B) from top to bottom and left to right include: Yellow [1,1,0], light Red [1,0,0.5], Purple [1,0,1], Dark Purple [0.5,0,0.5], Black [0,0,0], dark Green [0,0.5,0], Green [0,1,0], and Blue [1,0,0].