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. 2022 Aug 26;7:289. doi: 10.1038/s41392-022-01130-8

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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 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. 6 — The trajectory analysis of Mφ in LUAD and LUSC revealed distinct features. a, b Differentiation trajectory of Mφ in all lung samples, with each point colored by pseudotime (a) and Mφ subtype (b) (bottom) which was divided into two branches. c, d Pseudo-heatmap showing the various genes in the differentiation process of Mφ in branch 1, which was clustered into five clusters, and a scatter distribution plot showing the expression variation of some specific genes in each state during the pseudotime. The fit curves representing the gene expression of two states, and color coded for cancer type. e, f Pseudo-heatmap showing the various genes involved in the differentiation process of Mφ in branch 2, which was clustered into five clusters, and the scatter distribution plot showed the expression variation of some specific genes in each state during the pseudotime. The fit curves represent the gene expression of two states, and color coded for cancer types. g, h Ligand–receptor connections network among TFs and their target genes in branch 1 (g) and branch 2 (h)