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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We performed community detection (Leiden algorithm) with resolution 0.1 and used the same markers as scRNA data to select the fibroblast cluster.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We used marker genes from scRNA-seq data to label fibroblast populations through manual annotation.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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Cell coordinates colored by cell type were visualized using squidpy (sq.pl.spatial_scatter).
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We used the same integration strategy for newly generated atopic dermatitis data and publicly available cutaneous melanoma data.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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Cutaneous melanoma data were downloaded from https://www.10xgenomics.com/datasets/xenium-prime-ffpe-human-skin.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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NicheCompass was run after selecting 1,024 spatially variable genes.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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The number of neighbors selected per cell was 8, and otherwise default settings were used.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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To calculate neighborhood enrichment scores, we first constructed an adjacency matrix for indicating which cells were connected using the spatial_neighbors functions in squidpy.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We determined the neighborhood as a cell as cells within 20 µm of an index cell.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We then applied neighborhood enrichment analysis (nhood_enrichment function in squidpy) to quantify which cell types were more frequently colocalized than expected by chance.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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Heatmaps of enrichment scores were visualized using sq.pl.nhood_enrichment.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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To identify fibroblast clusters in disease, we mapped lesional data to the healthy/nonlesional reference described above.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We used a state-of-the-art deep meta-learning model (scPoli).
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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This approach first trains a model using the healthy/nonlesional (reference) to generate centroids (Fig. 3a).
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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Then, cells in the query that are distinct to centroids generated from the reference are marked as uncertain, which facilitates the discovery of new cell types/states in the query data (Fig. 3a).
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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This permits automated cell annotation while highlighting cells that could not be mapped to the reference through prototypical learning.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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Due to the proposed role of hypoxia in myofibroblast differentiation, we included hypoxic genes for consideration in feature selection.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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To ensure this selection did not bias results, we repeated an scVI integration using the same methodology as for healthy fibroblasts (Supplementary Fig. 4a,b).
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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Our definition of ‘uncertain’ cells was derived from scPoli.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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scPoli utilizes Euclidean distances of query cells from prototypes (or centroids) generated from the reference to yield an uncertainty associated with each cell.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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To manually annotate cells labeled as uncertain, we calculated DEGs for each Leiden cluster and also assessed expression of healthy fibroblast marker genes in each population.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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The top DEGs for each cluster considered as disease-associated or disease-specific are shown in Supplementary Fig. 1c and Supplementary Table 3.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We also considered which populations were enriched in disease.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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To validate our reported fibroblast subtypes, we used two approaches.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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First, we used skin scRNA-seq datasets not used in the original integration.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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Using the scPoli model to generate embeddings and transfer labels to these populations, we identified expected populations from earlier analysis (Supplementary Fig. 4c).
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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Second, we used Xenium data to validate the existence of the same clusters in which cell gene expression profiles are generated in situ, without tissue dissociation.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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For CellDISECT, we used 6,000 HVGs and raw counts as input.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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Model architecture and training schedule is listed in the provided code.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We used the top 500 human genes per pathway and default settings for the multivariate linear model (decoupler.run_mlm).
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We broadly grouped individual diseases into disease categories (inflammatory + low scarring risk, inflammatory + high scarring risk, cancer, established scarring/fibrosis) based on clinical disease features.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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Of note, clear separation of diseases is not possible because of a well-recognized link between inflammation and fibrosis.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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For example, an inflammatory component to systemic sclerosis is well recognized and first-line treatments typically include immunosuppressants, but this disease also features established fibrosis.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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Additionally, we included sarcoidosis and granuloma annulare (both disorders of granulomatous inflammation) in ‘inflammatory high scarring risk’ as fibrosis can occur within granulomas.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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Additionally, pulmonary sarcoidosis is a well-recognized cause of pulmonary fibrosis; however, most cases of cutaneous sarcoidosis and granuloma annulare do not scar.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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Prurigo nodularis was classified as low scarring risk as it is unclear whether scarring arises secondary to scratching.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We considered cancer as moderate scarring risk as fibrosis can occur within lesions (desmoplasia) and self-resolving melanoma can result in scarring.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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For fibroblast proportions by scarring category, we calculated the s.e.m.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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for each category using the mean proportion for each donor.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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The s.e.m.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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for each disease category was derived from the s.d.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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of donor-level proportions divided by the square root of the number of donors in that category.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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All research ethics committees and regulatory approvals were in place for the collection and storage of atopic dermatitis skin samples at the St John’s Institute of Dermatology, Guy’s Hospital, London (REC reference no. EC00/128) and hidradenitis suppurativa skin samples at Newcastle Dermatology Biobank (REC reference no. 19/NE/0004).
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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Fresh-frozen OCT-embedded skin samples were sectioned at 10-µm thickness directly onto superfrost microscope slides and stored at −80 °C.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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Slides were air dried at room temperature for 10 min and then fixed using 4% PFA for 10 min.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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Next, a blocking solution of 5% normal goat serum with 0.01% Triton X-100 was applied to the tissue sections and incubated for 1 h at room temperature.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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Slides were then incubated with primary antibodies overnight at 4 °C.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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The next day, slides were washed with 1× PBS and incubated with secondary antibodies for 1 h at room temperature.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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Then, 4,6-diamidino-2-phenylindole (DAPI) was used to demarcate nuclei and slides were mounted with DAKO mounting medium before applying coverslips and leaving slides to dry overnight.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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Skin sections were imaged using a Leica SP8 confocal microscope.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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To calculate gene scores, we used the score_genes() function in scanpy.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We used arguments of ctrl_size = 1,000 and n_bins = 25.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We used the marker genes reported for each population, rather than more extensive gene lists, based on the rationale that larger gene programs would be more likely to include tissue-specific gene expression and thus underestimate transcriptomic similarity across tissues.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We trained a random forest classifier using fibroblast subtype composition as input to predict scarring risk group.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We evaluated performance in terms of average F1 score, a widely used metric for evaluating classification performance, computed using classification_report from scikit-learn.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We applied fivefold stratified cross-validation to train and evaluate a RandomForestClassifier (100 estimators, random_state = 42).
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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To identify cell types that are most predictive of scarring status, we extracted the final trained model’s feature importances.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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For trajectory inference, we used both velocity-based (RNA velocity (scVelo and CellRank2 Velocity kernel)) and graph-based (PAGA and Monocle 3) approaches.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We used data for which we could calculate RNA velocity using velocyto and scvelo.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We first used PAGA (as implemented in scanpy), plotted using a threshold of 0.1 and applied to the whole dataset.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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In future analyses, we excluded F5: Schwann-like fibroblasts, which seemed to be distinct (Extended Data Fig. 8a) and F_Fascia, which were observed in few diseases (Fig. 4a).
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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As healing and scarring is observed on non-hair-bearing sites, we also did not include F4: hair follicle-associated fibroblasts.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We generated new scVI embeddings for the lesional fibroblasts and re-calculated the k-NN graph using the top 2,000 HVGs, followed by UMAP visualization.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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Velocity pseudotime was calculated using scvelo.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We re-calculated the PAGA plot using only lesional fibroblasts, again using a threshold of 0.1.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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For Monocle 3 (v.1.3.7), the expression count matrix along with the corresponding cell and gene metadata from the processed anndata object in scanpy was used to create Monocle object (cell_data_set object).
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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The cell_data_set object was then pre-processed using default settings and aligned to correct for batch effects based on the ‘dataset_id’.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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Dimensionality reduction was performed using ‘UMAP’ as the reduction method.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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Cells were clustered with a resolution of 1 × 10 − 6 and ‘UMAP’ as the reduction method.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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A trajectory graph was learned by adjusting parameters such as geodesic distance ratio (0.5) and minimal branch length (10) to optimize for large datasets.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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Finally, cells were arranged in pseudotime by manually selecting root nodes from the F2: universal population.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We used F2: universal as the root state in Monocle 3 based on velocity pseudotime results and previous work.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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The ordered and learned graph object was then used to plot the pseudotime trajectory plots.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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The RNA velocity kernel was calculated using CellRank2.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We obtained post-alignment skin wound data from the authors of ref.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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and processed these using CellBender as previously described for skin fibroblast data.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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To annotate skin wound fibroblasts, we integrated the unlabeled skin wound cells with our labeled integrated skin dataset using scanVI.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We used the same model architecture (30 latent dimensions, two layers) and the same number of input HVGs (n = 6,000).
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We selected only fibroblasts for further analysis, using the same downstream strategy as used for skin fibroblasts previously.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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For cross-tissue marker gene comparisons, we selected reported populations from Korsunsky et al., Buecher et al. and Gao et al. As Gao et al. reported six universal and five shared populations, we show matching populations in the main figure and other populations in the extended figure.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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For cross-tissue integration, we concatenated our labeled skin data with other tissues (raw count data).
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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HLCA data, gut atlas data and Human Endometrial Cell Atlas data were available locally.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We downloaded nasal tissue data from https://ngdc.cncb.ac.cn/gsa-human/browse/HRA000772 (ref. ),
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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heart data from https://data.humancellatlas.org/explore/projects/e9f36305-d857-44a3-93f0-df4e6007dc97, rheumatoid arthritis from https://www.immport.org/shared/study/SDY998 (ref. )
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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and additional intestinal data from the Gene Expression Omnibus (GEO) under accession code GSE282122.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We used the same number of input HVGs (n = 6,000).
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We integrated data in a semi-supervised manner using scANVI, where skin cell types were labeled and cells from other tissues were unlabeled.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We used the same scANVI hyperparameters as for wound data but with a smaller number of maximum epochs (n = 10) due to the larger dataset size.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We then calculated k-NN (k = 30) and performed low-resolution Leiden clustering (resolution 0.1).
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We selected a fibroblast cluster based on canonical marker genes, which also contained the labeled skin fibroblasts.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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To annotate clusters, we labeled clusters by the majority skin fibroblast population (Fig. 6c and Extended Data Fig. 8b) (for example if F3: FRC-like was the predominant skin fibroblast subtype, we labeled the cluster as F3: FRC-like).
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We then assessed gene expression markers for each cluster, excluding skin fibroblasts, to ensure that skin fibroblasts did not drive the gene expression signature for that cluster.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We also plotted gene expression for each cluster by tissue using our previously reported marker genes for each cluster.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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To assess F3: FRC-like fibroblasts in HLCA data, we performed the same clustering strategy as previously described for skin fibroblasts and then plotted F3: FRC-like marker genes by cluster.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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Inflammation severity scores were obtained from GEO under accession code GSE282122.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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A linear regression model was fitted using ordinary least squares with the F6 proportion as the dependent variable and inflammation severity score as the independent variable using seaborn’s regplot function.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We used CellPhoneDB v.5 (method 2) for cell–cell communication analysis.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We combined our fibroblast data with skin immune cells from our previously published scRNA-seq data from skin with more granular immune cell annotations (Reynolds et al.).
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We restricted interactions to marker genes for F3: FRC-like fibroblasts and F6: inflammatory myofibroblasts.
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PMC12479362
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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues.
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We visualized the results using ktplotspy.
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