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. 2024 Jan 24;25:34. doi: 10.1186/s13059-024-03168-z

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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/. 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. 2 — High variabilities in the performance of metabolomics profiling among laboratories. a Numbers of detected metabolites in each metabolomic measurement using different filtering criteria, including no filtering (all detected metabolites in any of the samples), no missing (metabolites detected in all 12 samples); CV (coefficient of variance) < 30%; ICC (intraclass correlation coefficient) > 0.04; CV < 30% and ICC > 0.04. b Reprehensive scatter plots of technical replicates (D5-1 and D5-2). c Reprehensive scatter plots of different samples (D5-1 and D6-1). Number in parentheses represent corresponding Pearson correlation coefficient (PCC). d PCC of pairs of technical replicates and of different Quartet samples in each measurement. e Negative correlation between reproducibility (PCC of technical replicates) and discriminability (1-PCC of different samples). f Differentially abundant metabolites (DAMs) analysis for three sample pairs. Volcano plots were used to display the magnitude of the fold change versus the statistical significance level for each measurement. g Numbers of upregulated or downregulated DAMs identified for three sample pairs in each measurement