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. 2023 May 9;10:261. doi: 10.1038/s41597-023-02158-3

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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. 5 — Peptide concordance between SRM and ssTMT datasets. (a) Volcano plot displaying the log2 fold change (FC) (x-axis) against t-test log10 p-value (y-axis) for all peptides (n = 2,340) comparing AD (n = 150) versus Controls (n = 147). Cutoffs were determined by significant differential expression (p < 0.05) between control and AD cases. Peptides with significantly decreased levels in AD are shown in blue while peptides with significantly increased levels in disease were indicated in red. 44 of 62 SRM peptides that overlap with this ssTMT dataset and SRM are highlighted as larger yellow points with black text labels. Red text and traces to red points are labels for peptides not included in the current SRM study that were significantly upregulated in the ssTMT dataset. (b) Correlation between the fold-change (AD vs control) of all selected overlapping peptides (n = 40) across SRM (x-axis) and ssTMT (y-axis) were strongly correlated (cor = 0.91, p = 2.8e−15).