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This web implementation uses **Pyodide** (Python compiled to WebAssembly) to run the complete starCAT algorithm entirely in your browser.\n\n## Key Features\n\n- **Complete Privacy**: All computation happens client-side - your data never leaves your machine\n- **No Installation Required**: Run sophisticated bioinformatics analysis directly in your browser\n- **Multiple Input Formats**: Takes raw count data in both H5AD (AnnData) and MTX (Matrix Market) file formats\n- **Curated Reference Catalogs**: Access to pre-built reference datasets for various tissues and species\n- **Zero Infrastructure**: No backend servers or API limits\n\n## Quick Start\n\n1. **Visit the application** (https://immunogenomics.io/starcat)\n2. **Select a reference catalog** from the dropdown menu\n3. **Choose your file format** (H5AD or MTX)\n4. **Upload your data**:\n   - H5AD: Single `.h5ad` file (up to ~50,000 cells or 700MB)\n   - MTX: Three files (matrix, features, barcodes)\n5. **Click \"Run starCAT\"** and wait for processing\n6. **Download results**: Two TSV files (usage scores and detailed scores) plus interactive visualizations\n\n## Supported File Formats\n\n### H5AD Format\nStandard AnnData format for single-cell data stored in HDF5 files.\n\n### CellRanger H5 Format\nH5 format output by CellRanger (e.g. filtered_feature_bc_matrix.h5) for users who want to avoid H5Ad\n\n## Reference Catalogs\n\nPre-built reference catalogs are available for the following:\n- Human T cells across tissies and diseases (TCAT.V1)\n- Human myeloid cells from gliomas (MYELOID.GLIOMA.V1)\n- Human bone marrow derived CD34+ hematapoetic stem cells (BONEMARROW.CD34POS.HSPC.V1)\n\nView the full catalog at the **References** page.\n\n## Local Development\n\nSince this is a static website, you can run it locally with any web server:\n\n```bash\n# Using Python 3\npython -m http.server 8000\n\n# Using Node.js http-server\nnpx http-server\n\n# Or simply open starcat/index.html in your browser\n```\n\n## Citation\n\nIf you use starCAT in your research, please cite:\n\n```\nKotliar, D.*, Curtis, M.*, Agnew, R. et al. Reproducible single-cell annotation of programs underlying T cell subsets, activation states and functions. Nat Methods 22, 1964–1980 (2025). https://doi.org/10.1038/s41592-025-02793-1\n```\n\n## Related Resources\n\n- **GitHub** for [starCAT algorithm](https://github.com/immunogenomics/starCAT)\n- **Reference Catalogs**: Available on [Zenodo](https://zenodo.org/communities/starcat/records?q=\u0026l=list\u0026p=1\u0026s=10\u0026sort=newest)\n- **Documentation**: See [manuscript](https://www.nature.com/articles/s41592-025-02793-1#citeas) for methodology details\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fimmunogenomics%2Fstarcat_website","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fimmunogenomics%2Fstarcat_website","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fimmunogenomics%2Fstarcat_website/lists"}