Supplementary spatial metadata for integrated OSCC Visium analysis (E-GEAD-511)

<b>How to Cite</b>If you use this dataset in your research, please cite our primary publication in <i>PLOS Genetics</i>:Furudate K, Kasai S, Yoshizawa T, Sasaki Y, Fujikura K, <i>et al</i>. (2025) Spatial colocalization and molecular crosstalk of myofroblastic CAFs and tumor cells shape lymph node metastasis in oral squamous cell carcinoma. <i>PLOS Genetics</i> 21(9): e1011791. https://doi.org/10.1371/journal.pgen.1011791<br><b>Dataset Citation (Optional but Recommended):</b> For data traceability, you may also cite this Figshare dataset directly using the citation generated by the "Cite" button on this page. <b>However, please ensure the primary publication above is also cited.</b><br><b>Dataset Description</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>".Specifically, this deposit contains four (4) pickled Python dictionary objects. Each pickle file (e.g., sampleA_uns_spatial.pickle, sampleB_uns_spatial.pickle, sampleC_uns_spatial.pickle, sampleD_uns_spatial.pickle - stores the AnnData.uns['spatial'] dictionary information derived from one of the four OSCC samples. These uns['spatial'] objects are structured to correspond with the integrated AnnData object (processed.h5ad) that combines all four samples and is available from the Genomic Expression Archive (GEA) under accession number E-GEAD-511 (https://ddbj.nig.ac.jp/public/ddbj_database/gea/experiment/E-GEAD-000/E-GEAD-511/).These pickled dictionaries are intended for use within a Python/Scanpy environment. They can be loaded (e.g., using pickle.load()) and assigned to the .uns['spatial'] attribute of an appropriately subsetted AnnData object derived from the E-GEAD-511 deposit. This allows users to replicate specific spatial visualizations or access pre-calculated spatial parameters (such as image paths, scale factors, and spot coordinates under tissue) as used in our study's analysis of the integrated dataset.For the complete, raw 10x Genomics Space Ranger output files for each of the four individual samples (including filtered_feature_bc_matrix.h5 files and full spatial image folders, as well as patho_annot folders), please refer to our separate Figshare deposit: https://doi.org/10.6084/m9.figshare.29237660.The raw sequencing reads for these samples are available at DDBJ under BioProject accession PRJDB13905 (https://ddbj.nig.ac.jp/search/entry/bioproject/PRJDB13905).All patient-derived image information that might be referenced by this spatial metadata was originally obtained from de-identified images.