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. 2020 Sep 8;11:4487. doi: 10.1038/s41467-020-18148-7

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© The Author(s) 2020

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. 5 — a Bar plot of the distribution of the most significant results from mixed-effect modeling for each of the clinical variables compared to features from the proteome, transcriptome, metabolome and lipidome. b Visualization of the top two most significant features for each clinical data across omics colored by omics type. Multiple test corrections have been applied for p values using Benjamini and Hochberg method. Number of samples: metabolome (n = 94), lipidome (n = 48), proteome (n = 90), transcriptome (n = 77).