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. 2023 Jan 31;14:509. doi: 10.1038/s41467-023-36071-5

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© The Author(s) 2023

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. 2 — Each subplot shows the RRST data on the left side and the standard Visium data on the right side. a H&E images of two representative tissue sections collected from the same tissue block. b Violin/box plots showing the distribution of unique genes and UMI counts for RRST (n = 1) and standard Visium (n = 2) data generated from consecutive tissue sections from the same lung tissue specimen. The y-axis is shown in log10 scale. Box plots are presented as median values where the lower and upper bounds are the 25th and 75th percentiles. The upper and lower limits of the boxplots are defined by the closest value no further than 1.5*IQR (inter-quartile range) from the closest bound. Values outside of the upper and lower limits are highlighted as outliers. c Unique genes per spot mapped on tissue coordinates. d Spatial visualization showing what spots were discarded due to low quality (less than 300 unique genes detected). e UMAP embedding of adult lung data colored by clusters detected by unsupervised graph-based clustering (louvain). f Split view of clusters (same as in e) mapped on tissue coordinates. g Dot plots of the top marker genes for each cluster. Each cluster was annotated based on its spatial localization in the tissue and expression of canonical marker genes.