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. 2023 Sep 1;55(9):2005–2024. doi: 10.1038/s12276-023-01074-1

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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 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 — A Venn diagram representing proteins shared between in vivo liver and in vitro organoids. The correlation is also shown with the scatterplot, and the overrepresented GO terms of the shared proteins are shown by a bar graph. B Ranked plot of log2(intensity) of proteomics data in organoid (blue) and liver (red). Proteins are categorized by four intensity ranges (25~, 20–25, 15–20 and 10–15). Representative liver markers in each intensity range are shown in the right panel. C Bar plot showing overrepresented Gene Ontology terms in each intensity range. D Unbiased clustering of proteomic data. Clustering was performed to log2(intensity) value of all expressed genes (log2(intensity)>10). E Differentially expressed proteins and their overrepresented GO terms. All of the above experiments were performed with the hiPSC line AG27.