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. 2024 Sep 3;30(12):3578–3589. doi: 10.1038/s41591-024-03239-5

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© The Author(s) 2024

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, 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 you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. 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-nc-nd/4.0/.

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Extended Data Fig. 3 — For each PC, we show a scatter plot and kernel density estimate (KDE) plot. In the scatter plots, the actual PC values are plotted on the x-axis and the projected PC values are plotted on the y-axis. The Pearson correlation coefficient is shown in the top left corner of each scatter plot. In the KDE plots, the true PC distribution is shown in blue and the projected PC distribution is shown in orange. The p-value of a two-sided Kolmogorov-Smirnov test comparing the two distributions is shown in the top left corner of each KDE plot. No multiple hypothesis correction was needed.