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. 2022 Oct 29;20:494. doi: 10.1186/s12967-022-03713-z

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© The Author(s) 2022

Open AccessThis 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 — The NAS is positively correlated with glioma aggressiveness. A–C Distribution of NAS in samples grouped by Verhaak classification in TCGA, CGGA325, CGGA693, respectively. D, E Distribution of clusters and NAS in GSE84465 and CGGA dataset, respectively. The cells are displayed by tSNE reduction. F The NAS of cluster1 and cluster2 in GSE84465 and CGGA dataset, respectively. G The NAS of four cell types, low neoplastic, high neoplastic, inflammation-related glioma cells and OPC in GSE84465 and CGGA scSeq datasets, respectively. H–J The RNA velocity of GSE84465 displayed by clusters, subtypes and NAS, respectively