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. 2019 Oct 25;28(3):349–357. doi: 10.1038/s41431-019-0533-z

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© The Author(s) 2019

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. 3 — Transformation of mLRRY-values linearises LOY estimates from SNP-array data using the equation: LOY (%) = 100 × (1−2^2mLRRY). a displays estimations of the level of LOY from 26 pairwise studied samples using SNP-array and whole genome sequencing (WGS). The Y-axis show the predicted LOY (%) from SNP-array data using the above formula and the X-axis display the measured level of LOY using WGS. A linear regression line with Pearson’s coefficient of determination (R²) is shown. b shows a corresponding comparison between estimations of LOY from 121 pairwise studied samples using SNP-array and droplet digital PCR (ddPCR)