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. 2023 Nov 16;14:7432. doi: 10.1038/s41467-023-43201-6

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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. 8 — a Illustration of the workflow for integration of metabolic and transcriptional data. b Dotplot for correlation between transcriptionally defined T cell exhaustion/cytotoxic behavior and abundance of metabolites from various pathways. c Illustration of glycolysis (top) and the exhaustion/cytotoxic score (bottom) at clone level. All spots occupied by a clone are summarized for the clonal profile. d Surface plots of an example sample with the abundance of clones (from left to right), the exhaustion/cytotoxic score, and the abundance of glycolysis metabolites on clone- and spot-level (right). Surface plots contain the dimensions of the samples (in mm) on the x and y axes.