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. 2021 Jan 25;7:23. doi: 10.1038/s41420-020-00383-y

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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 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 Hierarchical clustering of 872 single cells derived from three extinction (KTN126, KTN129, and KTN206) and three persistence (KTN102, KTN132, and KTN615) triple-negative breast cancer (TNBC) prior to neoadjuvant chemotherapy based on lncRNA transcriptome. b Unsupervised single-cell population identification using ICGS algorithm conducted on 577 single cells derived from the extinction (KTN126, KTN129, and KTN206) and 295 cells derived from the persistence (KTN102, KTN132, and KTN615) group prior to neoadjuvant treatment. Data are presented as heat map with the corresponding single-cell cluster on top. Color scale displays differential gene expression (log2). The lower legend indicated the source of each cell. c Uniform manifold approximation and projection (UMAP) dimensionality reduction analysis of 872 single cells from the same cohort prior to neoadjuvant treatment.