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. 2022 Jul 18;12:12239. doi: 10.1038/s41598-022-16158-7

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© The Author(s) 2022

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/.

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(A) UMAP reduction of the transcriptomic feature vector for each cell. Clusters were identified by the Suerat software. (B) PCA reduction of the transcriptomic features; individual cells are colored according to their cluster number from (A). (C) Labeling each cell by the expression level of four myofibroblast associated genes (TGFB1, COL1A1, POSTN, and TIMP1) shows a consistent spectrum of activation. (D) Using the PCA reduction, another continuous label system was created. The distribution of cells is similar to that seen from the SSM model. (E) Log₂(FC) values of myofibroblast associated genes show that clusters 1, 4, 5, 7, 8, and 10 are highly activated compared to cluster 2.