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. 2024 May 9;29(11):3330–3343. doi: 10.1038/s41380-024-02576-8

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© The Author(s) 2024

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/.

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Fig. 2 — A Workflow of 11-plex TMT-based proteome analysis. A total of 10 samples and 1 internal standard (i.e., 10 pooled samples) were analyzed by LC/LC-MS/MS. MS raw data were analyzed using JUMP software. B Stacked Venn diagram showing the numbers of proteins identified in all 268 samples. C Histogram showing the coverage of quantified proteins across 29 batches of TMT experiments. D Histogram showing the coverage of proteomic data compared to RNA-seq data. The open bar represents the distribution of protein-coding genes detected by RNA-seq, the light blue bar indicates the distribution of protein-coding genes from proteomic data, and the navy bar indicates the distribution of protein-coding genes from no missing value proteomic data. Protein coverage is defined as the determination of whether a transcript is expressed in one or more samples. E Scatter plot showing a comparison of gene expression levels and protein abundance. Expression levels are averaged across all samples. F Distribution of coefficient of variation (CV) for all proteins across all samples.