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unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["cell-atlas","clustering","leidenalg","scrna-seq","scrna-seq-analysis","singlecell"],"created_at":"2026-01-16T20:28:03.989Z","updated_at":"2026-01-16T20:28:04.690Z","avatar_url":"https://github.com/fabilab.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"[![Build Status](https://travis-ci.org/northstaratlas/northstar.svg?branch=master)](https://travis-ci.org/northstaratlas/northstar)\n[![License: MIT](https://img.shields.io/badge/license-MIT-brightgreen.svg)](https://opensource.org/licenses/MIT)\n[![ReleaseVersion](https://img.shields.io/pypi/v/northstar?color=limegreen)](https://pypi.org/project/northstar/)\n[![FOSSA Status](https://app.fossa.io/api/projects/git%2Bgithub.com%2Fiosonofabio%2Fnorthstar.svg?type=shield)](https://app.fossa.io/projects/git%2Bgithub.com%2Fiosonofabio%2Fnorthstar?ref=badge_shield)\n[![Documentation Status](https://readthedocs.org/projects/northstar/badge/?version=latest)](https://northstar.readthedocs.io/en/latest/?badge=latest)\n\n![Logo](https://raw.githubusercontent.com/northstaratlas/northstar/master/docs/_static/logo.png)\n# northstar\nSingle cell type annotation guided by cell atlases, with freedom to be queer.\n\n## Brief description\n`northstar` is a Python package to identify cell types within single cell transcriptomics datasets.\nnorthstar's superpower is that it learns from cell atlases but still allows queer cells to make their own cluster if they want to.\n\nAlso, northstar was heavily developed during [Pride Month](https://en.wikipedia.org/wiki/Gay_pride).\n\n## Atlas resources\n![Atlas averages](https://northstaratlas.github.io/atlas_landmarks/static/logo.png)\n\nCurated averages and subsamples from several atlases: https://northstaratlas.github.io/atlas_landmarks/\n\nIf you want us to add you cell atlas, open an issue on: https://github.com/northstaratlas/atlas_landmarks/issues\n\n## Documentation\nhttps://northstar.readthedocs.io\n\n## Installation\n```bash\npip install northstar\n```\n\nTo automatically download and use our online atlas collection at [https://northstaratlas.github.io/atlas_averages/](https://northstaratlas.github.io/atlas_averages/), you will need to call:\n\n```bash\npip install 'northstar[atlas-fetcher]'\n```\n\n### Dependencies\n- `numpy`\n- `scipy`\n- `pandas`\n- `scikit-learn`\n- `anndata`\n- `python-igraph\u003e=0.8.0`\n- `leidenalg\u003e=0.8.0`\n\nIt is recommended that you install python-igraph and leidenalg using `pip`. However, any installation (e.g. conda) that includes recent enough versions of both packages should work.\n\nOptional deps to use our online atlases:\n\n- `requests`\n- `loompy`\n- `scanpy`\n- `pynndescent` (only useful if you use `scanpy` as well)\n\nIf you have `scanpy` installed, `northstar` will use it to speed up a few operations (PCA, graph construction). You can turn this off in two ways:\n\n1. Uninstall `scanpy` is you don't need it for anything else, or\n2. Set the environment variable `NORTHSTAR_SKIP_SCANPY` to anything except empty string, e.g. in a notebook:\n\n```python\nimport os\nos.environ['NORTHSTAR_SKIP_SCANPY'] = 'yes'\nimport northstar as ns\n\n(rest of the notebook/script)\n```\n\nHot-swapping between the two modes (w or w/o `scanpy`) is not currently supported.\n\n## Usage\nSee the paper below or the documentation for detailed instructions and examples. The simplest way to use `northstar` is to classify a new single cell dataset using one of the available atlases, e.g. `Darmanis_2015` on brain cells:\n\n```python\nimport northstar\n\n# Choose an atlas\natlas_name = 'Darmanis_2015'\n\n# Get a gene expression matrix of the new dataset (here a\n# random matrix for simplicity)\nN = 200\nL = 50\nnew_dataset = pd.DataFrame(\n    data=np.random.rand(L, N).astype(np.float32),\n    index=\u003cgene_list\u003e,\n    columns=['cell_'+str(i+1) for i in range(N)],\n    )\n\n# Initialize northstar classes\nmodel = northstar.Averages(\n        atlas='Darmanis_2015',\n        n_neighbors=5,\n        n_pcs=10,\n        )\n\n# Run the classifier\nmodel.fit(new_dataset)\n\n# Get the cluster memberships for the new cells\nmembership = model.membership\n```\n\n## Citation\nIf you use this software please cite the following paper:\n\nFabio Zanini\\*, Bojk A. Berghuis\\*, Robert C. Jones, Benedetta Nicolis di Robilant, Rachel Yuan Nong, Jeffrey Norton, Michael F. Clarke, Stephen R. Quake. **Northstar enables automatic classification of known and novel cell types from tumor samples.** Scientific Reports 10, Article number: 15251 (2020), DOI: https://doi.org/10.1038/s41598-020-71805-1\n\n## License\n`northstar` is released under the MIT license.\n\nNOTE: The module leidenalg to perform graph-based clstering is released\nunder the GLP3 license. 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