<b>Visium spatial transcriptomics data for individual oral squamous cell carcinoma (OSCC) patients</b>

This dataset contains the 10x Genomics Space Ranger output files for four individual human oral squamous cell carcinoma (OSCC) samples, supporting the findings of our study: "<b>Spatial colocalization and molecular crosstalk of myofibroblastic CAFs and tumor cells shape lymph node metastasis in oral squamous cell carcinoma</b>".For each of the four samples (Sample A [HUH001-P, Sample B [HUH001-P2], Sample C [HUH001-met], and Sample D [HUH002-P]), the following files and folders are provided:The filtered feature-barcode matrix in HDF5 format (filtered_feature_bc_matrix.h5).A spatial subfolder containing:High-resolution tissue image (tissue_hires_image.png)Low-resolution tissue image (tissue_lowres_image.png)Fiducial alignment image (aligned_fiducials.jpg)Tissue detection image (detected_tissue_image.jpg)Scale factors JSON file (scalefactors_json.json)Tissue spot coordinates CSV file (tissue_positions_list.csv)A <code>patho_annot</code> subfolder containing annotation files in TXT format for each respective sample. These files link annotations to spot barcodes and provide detailed information for each spot, including columns for:Barcode (the unique spot identifier)patho (primary pathological annotation ID)graph-based cluster (computationally assigned cluster ID based on gene expression)patho_diag (detailed pathological diagnostic information or feature)category (a broader classification category for the spot, e.g., tumor, peritumor, non_tumor)description (additional descriptive text or notes for the spot) These files allow for the direct import, reprocessing, and reanalysis of individual samples using standard spatial transcriptomics software packages such as Seurat (e.g., the Load10X_Spatial function) or Scanpy/Squidpy (e.g., the read_visium function).The raw sequencing reads for these samples are available at DDBJ under BioProject accession PRJDB13905 (https://ddbj.nig.ac.jp/search/entry/bioproject/PRJDB13905). A processed and integrated AnnData object (.h5ad) combining these four samples is available at GEA under accession E-GEAD-511 (https://ddbj.nig.ac.jp/public/ddbj_database/gea/experiment/E-GEAD-000/E-GEAD-511/). Supplementary spatial metadata components (pickled Python objects) for use with the integrated AnnData object are available at Figshare (https://doi.org/10.6084/m9.figshare.20408067).All patient-derived images included in this dataset were de-identified prior to deposition.