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. 2021 Dec 2;11:23285. doi: 10.1038/s41598-021-02683-4

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© The Author(s) 2021

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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Clustering analysis of noncircular spheroids and the presence of distinct clusters with disrupted morphologies. (A) Fifteen morphological features extracted from human VSMC spheroid images from Clusters #2 and #4 were visualized on UMAP plots. The different colored markers are used to represent the various drug treatments. (B) The number of nearest samples between 10 and 100 was evaluated on the training set, and the silhouette values were plotted. A cluster number of 4 was selected. (C) The silhouette values and the number of clusters on the training set were evaluated by varying the number of nearest samples. (D) Four morphological clusters were observed in the testing set based on the noncircular spheroids from Clusters #2 and #4 obtained from Fig. 5. The different colored markers are used to represent the various morphological clusters. (E) Average Proportionality plots of the distribution of VSMC spheroids in each morphological cluster from the repeated random splitting of training and testing sets. Only testing sets were used. *p < 0.05, **p < 0.01, ***p < 0.001, and ns not significant. (F) Summary of the clustering analysis results.