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. 2023 Feb 23;14:1028. doi: 10.1038/s41467-023-36707-6

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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. 1 — a Illustration of the overall workflow. Examples images for SpotClean-adjusted gene expression (OLIG2) and BANKSY-based spatial clustering for DMG1 are shown. b UMAP of all Harmony-integrated spatial transcriptomic spots (n = 26, 460) from all samples (n = 11). Colors represent different samples. Clusters of peritumor spots are highlighted by blue dashed lines. c Overview of the workflow for CNV-based estimation of tumor cell content. GBM4 is shown as an example. Colors indicate the predicted tumor cell content score. d UMAP of all Harmony-integrated spatial transcriptomic spots from all samples (n = 26,460 spots). Colors indicate the predicted tumor cell content score. The same clusters of peritumor spots in b are highlighted by blue dashed lines. e The colocalization of CNV and H3K27M mutation in spots from DMG samples (n = 5). The number of spots from each sample is indicated.