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. 2023 Nov 29;625(7995):540–547. doi: 10.1038/s41586-023-06770-6

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© The Author(s) 2023

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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Extended Data Fig. 6 — HH (left column) and LD (right column) estimates were calculated for the unmasked and masked Only-BSP dataset (DB) including only populations with a minimum sample size of 10 individuals and a maximum sample size of 30. HH was estimated on a window size of 50 kb and LD was estimated as r² at 50 kb (Supplementary Information). Figure showing for each population of the unmasked DB: a, HH estimates (based on 67 populations in total); and b, LD estimates (based on 70 populations). Figure showing for each population of the masked DB: c, HH estimates; d, LD estimates; e, decrease of HH estimates with geographical distance from Cameroon; and f, increase of LD estimates with geographical distance from Cameroon (based on 49 populations; populations with LD > 0.27 were excluded from this analysis). In e and f, spatial distances were calculated as the spherical distance from each population and a centroid position located in the centre of Cameroon. The dotted line represents the linear regression between the estimates of each statistic and the geographical distances.