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. 2021 Mar 4;29(9):1446–1454. doi: 10.1038/s41431-021-00835-8

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© The Author(s) 2021

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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 2 — In the main approach, we used a region size spanning 2 Mb, and 400 kb regions as a sensitivity analysis. In addition to the main PCOS dataset, we also performed colocalization analysis with a PCOS dataset where the 23andMe cohort had been excluded as a sensitivity analysis. r² is the linkage disequilibrium value between the top SNP in the main PCOS dataset and the top SNP in the tissue expression/protein dataset, using the 2 Mb region size. N tissues are the number of tissues where the colocalization PP > 0.5 in the main analysis. Only the results for the tissue with the highest posterior probability of colocalization in the main analysis are reported here (for full results and power calculations see Supplementary Tables 1–3). Gene-tissue combinations with a posterior probability of colocalization >0.50 were seen as having some evidence in favour of colocalization, whereas the threshold for strong evidence was set at ≥0.75. PCOS polycystic ovary syndrome, PP posterior probability, Without-23 the PCOS dataset where the 23andMe cohort had been excluded.