{"id":15118792,"url":"https://github.com/Novartis/scar","last_synced_at":"2025-09-28T01:31:01.170Z","repository":{"id":37503743,"uuid":"470323565","full_name":"Novartis/scar","owner":"Novartis","description":"scAR (single-cell Ambient Remover) is a deep learning model for removal of the ambient signals in droplet-based single cell omics","archived":false,"fork":false,"pushed_at":"2024-05-28T21:20:32.000Z","size":62960,"stargazers_count":44,"open_issues_count":1,"forks_count":4,"subscribers_count":8,"default_branch":"main","last_synced_at":"2024-05-28T21:33:01.358Z","etag":null,"topics":["cite-seq","crispr-screen","denoising-algorithm","generative-model","machine-learning","probabilistic-graphical-models","pytorch","single-cell-rna-seq","variational-autoencoder"],"latest_commit_sha":null,"homepage":"https://scar-tutorials.readthedocs.io/en/main/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Novartis.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":".github/CONTRIBUTING.md","funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2022-03-15T20:35:43.000Z","updated_at":"2024-07-24T09:55:44.468Z","dependencies_parsed_at":"2024-07-24T10:12:31.578Z","dependency_job_id":null,"html_url":"https://github.com/Novartis/scar","commit_stats":null,"previous_names":[],"tags_count":29,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Novartis%2Fscar","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Novartis%2Fscar/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Novartis%2Fscar/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Novartis%2Fscar/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Novartis","download_url":"https://codeload.github.com/Novartis/scar/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":234475315,"owners_count":18839358,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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":["cite-seq","crispr-screen","denoising-algorithm","generative-model","machine-learning","probabilistic-graphical-models","pytorch","single-cell-rna-seq","variational-autoencoder"],"created_at":"2024-09-26T01:53:38.253Z","updated_at":"2025-09-28T01:30:53.608Z","avatar_url":"https://github.com/Novartis.png","language":"Python","readme":"\n\u003cp align=\"left\"\u003e\n  \u003cimg src=\"docs/_static/scAR_logo_white.png\" width=\"250\" title=\"scAR\"\u003e\n\u003c/p\u003e\n\n   \n   \n[![scAR](https://anaconda.org/bioconda/scar/badges/version.svg)](https://anaconda.org/bioconda/scar)\n[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/scar/README.html)\n[![code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)\n[![Documentation Status](https://readthedocs.org/projects/scar-tutorials/badge/?version=latest)](https://scar-tutorials.readthedocs.io/en/latest/?badge=latest)\n[![semantic-release: angular](https://img.shields.io/badge/semantic--release-angular-e10079?logo=semantic-release)](https://github.com/semantic-release/semantic-release)\n[![test](https://github.com/Novartis/scAR/actions/workflows/python-conda-build.yaml/badge.svg)](https://github.com/Novartis/scAR/actions/workflows/python-conda-build.yaml)\n[![Stars](https://img.shields.io/github/stars/Novartis/scar?logo=GitHub\u0026color=red)](https://github.com/Novartis/scAR)\n[![Downloads](https://anaconda.org/bioconda/scar/badges/downloads.svg)](https://anaconda.org/bioconda/scar/files)\n\n**scAR** (\u003cu\u003es\u003c/u\u003eingle-\u003cu\u003ec\u003c/u\u003eell \u003cu\u003eA\u003c/u\u003embient \u003cu\u003eR\u003c/u\u003eemover) is a tool designed for denoising ambient signals in droplet-based single-cell omics data. It can be employed for a wide range of applications, such as, **sgRNA assignment** in scCRISPRseq, **identity barcode assignment** in cell indexing, **protein denoising** in CITE-seq, **mRNA denoising** in scRNAseq, and **ATAC signal denoising** in scATACseq, among others.\n\n# Table of Contents\n\n- [Installation](#Installation)\n- [Dependencies](#Dependencies)\n- [Resources](#Resources)\n- [License](#License)\n- [Reference](#Reference)\n\n## [Installation](https://scar-tutorials.readthedocs.io/en/latest/Installation.html)\n## Dependencies\n\n[![PyTorch 1.8](https://img.shields.io/badge/PyTorch-1.8.0-greeen.svg)](https://pytorch.org/)\n[![Python 3.8.6](https://img.shields.io/badge/python-3.8.6-blue.svg)](https://www.python.org/)\n[![torchvision 0.9.0](https://img.shields.io/badge/torchvision-0.9.0-red.svg)](https://pytorch.org/vision/stable/index.html)\n[![tqdm 4.62.3](https://img.shields.io/badge/tqdm-4.62.3-orange.svg)](https://github.com/tqdm/tqdm)\n[![scikit-learn 1.0.1](https://img.shields.io/badge/scikit_learn-1.0.1-green.svg)](https://scikit-learn.org/)\n\n## Resources\n\n- Installation, Usages and Tutorials can be found in the [documentation](https://scar-tutorials.readthedocs.io/en/latest/).\n- If you'd like to contribute, please read [contributing guidelines](https://github.com/Novartis/scAR/blob/main/.github/CONTRIBUTING.md).\n- Please use the [issues](https://github.com/Novartis/scAR/issues) to submit bug reports.\n\n## License\n\nThis project is licensed under the terms of [License](docs/License.rst).  \nCopyright 2022 Novartis International AG.\n\n## Reference\n\nIf you use scAR in your research, please consider citing our [manuscript](https://doi.org/10.1101/2022.01.14.476312),\n\n```\n@article {Sheng2022.01.14.476312,\n\tauthor = {Sheng, Caibin and Lopes, Rui and Li, Gang and Schuierer, Sven and Waldt, Annick and Cuttat, Rachel and Dimitrieva, Slavica and Kauffmann, Audrey and Durand, Eric and Galli, Giorgio G and Roma, Guglielmo and de Weck, Antoine},\n\ttitle = {Probabilistic modeling of ambient noise in single-cell omics data},\n\telocation-id = {2022.01.14.476312},\n\tyear = {2022},\n\tdoi = {10.1101/2022.01.14.476312},\n\tpublisher = {Cold Spring Harbor Laboratory},\n\tURL = {https://www.biorxiv.org/content/early/2022/01/14/2022.01.14.476312},\n\teprint = {https://www.biorxiv.org/content/early/2022/01/14/2022.01.14.476312.full.pdf},\n\tjournal = {bioRxiv}\n}\n```\n","funding_links":[],"categories":["Ranked by starred repositories"],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FNovartis%2Fscar","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FNovartis%2Fscar","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FNovartis%2Fscar/lists"}