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. 2022 Jul 14;13:4076. doi: 10.1038/s41467-022-31739-w

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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. 5 — a H&E image and annotation from the original study for the spots of sample G in human breast cancer ST data⁵⁶. b Domain segmentation from SpaceFlow. c Spatial visualization of pseudotime calculated by Monocle. d Spatial visualization of pseudotime calculated by stLearn. e The pSM from SpaceFlow. f The pSM versus UMAP component 1 from low-dimensional embeddings colored by annotations from SpaceFlow. g Dot plot of the gene expression of domain-specific markers. The dot size represents the fraction of cells in a domain expressing the marker and the color intensity represents the average expression of the marker in that domain. h Spatial expression of top domain marker genes with anti-cancer, pro-cancer, or dual function labels. i Gene Ontology (GO) enrichment for the top domain-specific genes (48 genes) in the identified Tumor-Immune-Interface-1 (Tu.Imm.Itfc.1). Enriched GO terms are presented as -log10(p-value) using topGO analysis. P values were obtained using the one-sided Fisher’s exact test without multiple-testing correction. P values < 0.005 were considered significant. Space-constrained CellChat inferred cell-cell communications with cell-cell communications signaling sent from Invasive-1 in Collagen pathway (j) and from In-situ cancer 1 in MK & APP pathways (k).