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. 2021 Dec 6;22:333. doi: 10.1186/s13059-021-02548-z

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© The Author(s) 2021

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. 5 — geneBasis identifies cell state genes relevant for heterogeneity across multiple cell types in the context of cancer. A UMAP representation, colored by malignancy status and annotated cell types. UMAP coordinates themselves were calculated using the whole transcriptome. B Cell type confusion matrix for non-malignant cells. C Ordered barplot for cell type abundance. D Co-expression (within all cells, left panel; within malignant cells, right panel) for selected genes associated with various transcriptional programs identified in the original publication. Colors correspond to detected programs, corresponding legend is on the right