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. 2023 Jul 11;11:113. doi: 10.1186/s40478-023-01610-0

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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/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 1 — Results from EPIC DNA methylation arrays a Heatmap of scaled methylation M-values of 3648 most variable probes, split in rows, according to CpG relation to CGI and clustering of samples. b Beta values of 364,784 probes with standard deviation of β-values above 0.1, split according to CpG relation to CGI and gene. c Quantification of differences in overall methylation levels using a linear model of M-values. d Distribution of differentially methylated probes classified according to their position regarding CGI and genes. e Differentially methylated regions, depicted on Manhattan plots (genomic position on x-axis), gene names for most significant and biologically interesting DMRs are captioned