# MetaTiME: Meta-components in Tumor immune MicroEnvironment
<p align="left"><img src="https://raw.githubusercontent.com/yi-zhang/MetaTiME/main/docs/source/_static/img/logo.png" width="290" height="240"></p>
[](https://metatime.readthedocs.io/en/latest/?badge=latest)
MetaTiME is a framework to generate data-driven, interpretable, and reproducible gene programs by integrating millions of single cells from hundreds of tumor scRNA-seq data. Applied on large-scale tumor scRNA data with 1.7 million Tcells, MetaTiME thus utilize the meta-components to automatically annotate cell states for single-cells from tumor microenvironment.
( * BETA version, Currently under development :)
## Installation
Create a new virtual env and activate (optional)
`python -m venv metatime-env;
source metatime-env/bin/activate`
Use pip to install
`pip install metatime`
Installation shall be in minutes .
## Interactive tutorials
### MetaTiME-Annotator
[Use MetaTiME to automatically annotate cell states and map signatures ](https://colab.research.google.com/github/yi-zhang/MetaTiME/blob/main/docs/notebooks/metatime_annotator.ipynb)
## Method
<p align="left"><img src="https://raw.githubusercontent.com/yi-zhang/MetaTiME/main/docs/source/_static/img/fig1.png" width="700" height="400"></p>
### Usage
- [Use MetaTiME to automatically annotate cell states and map signatures](https://github.com/yi-zhang/MetaTiME/blob/main/docs/notebooks/metatime_annotator.ipynb)
### Dependency
- pandas
- scanpy
- anndata
- matplotlib
- adjustText
- leidenalg
- harmonypy
Dependency version tested:
- pandas==1.1.5
- scanpy==1.8.2
- anndata==0.8.0
- matplotlib==3.5.1
- adjustText==0.7.3
- leidenalg==0.8.3
### Reference
Manuscript In Revision. Repo continously being improved! More details will be updated.
[Paper at bioRxiv](https://www.biorxiv.org/content/10.1101/2022.08.05.502989v1)
[Journal Article doi pending]
### Training Datasets
Tumor scRNAseq Data for MetaTiME @ [Zenodo](https://zenodo.org/record/7410180)
- A large collection of uniformly processed tumor single-cell RNA-seq.
- Includes raw data and MetaTiME score for the TME cells.
### Contact
Yi Zhang, Ph.D.
yiz [AT] ds.dfci.harvard.edu
[Twitter](https://twitter.com/Wings7Spread) | [Website](https://yi-zhang.github.io/)
Research Fellow
Department of Data Science
Dana-Farber Cancer Institute
Harvard University T.H. Chan School of Public Health
Raw data
{
"_id": null,
"home_page": "https://github.com/yi-zhang/MetaTiME.git",
"name": "metatime",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.6",
"maintainer_email": "",
"keywords": "",
"author": "Yi Zhang",
"author_email": "wingsyiz@gmail.com",
"download_url": "https://files.pythonhosted.org/packages/8f/95/91b8db9e3ecd8663e3e36545b2a6bd66346e3ba604b68a21bf3a95c7f29c/metatime-1.2.2.tar.gz",
"platform": null,
"description": "# MetaTiME: Meta-components in Tumor immune MicroEnvironment \n<p align=\"left\"><img src=\"https://raw.githubusercontent.com/yi-zhang/MetaTiME/main/docs/source/_static/img/logo.png\" width=\"290\" height=\"240\"></p>\n\n[](https://metatime.readthedocs.io/en/latest/?badge=latest)\n\nMetaTiME is a framework to generate data-driven, interpretable, and reproducible gene programs by integrating millions of single cells from hundreds of tumor scRNA-seq data. Applied on large-scale tumor scRNA data with 1.7 million Tcells, MetaTiME thus utilize the meta-components to automatically annotate cell states for single-cells from tumor microenvironment. \n( * BETA version, Currently under development :)\n\n## Installation\n\nCreate a new virtual env and activate (optional)\n\n`python -m venv metatime-env; \nsource metatime-env/bin/activate`\n\nUse pip to install\n\n`pip install metatime`\n\nInstallation shall be in minutes .\n## Interactive tutorials\n### MetaTiME-Annotator\n[Use MetaTiME to automatically annotate cell states and map signatures ](https://colab.research.google.com/github/yi-zhang/MetaTiME/blob/main/docs/notebooks/metatime_annotator.ipynb)\n\n## Method \n<p align=\"left\"><img src=\"https://raw.githubusercontent.com/yi-zhang/MetaTiME/main/docs/source/_static/img/fig1.png\" width=\"700\" height=\"400\"></p>\n\n\n### Usage\n - [Use MetaTiME to automatically annotate cell states and map signatures](https://github.com/yi-zhang/MetaTiME/blob/main/docs/notebooks/metatime_annotator.ipynb)\n\n### Dependency\n\n- pandas\n- scanpy\n- anndata\n- matplotlib\n- adjustText\n- leidenalg\n- harmonypy\n\nDependency version tested:\n- pandas==1.1.5\n- scanpy==1.8.2\n- anndata==0.8.0\n- matplotlib==3.5.1\n- adjustText==0.7.3\n- leidenalg==0.8.3\n\n\n### Reference\nManuscript In Revision. Repo continously being improved! More details will be updated. \n\n[Paper at bioRxiv](https://www.biorxiv.org/content/10.1101/2022.08.05.502989v1)\n\n[Journal Article doi pending]\n\n### Training Datasets\n\nTumor scRNAseq Data for MetaTiME @ [Zenodo](https://zenodo.org/record/7410180)\n\n- A large collection of uniformly processed tumor single-cell RNA-seq. \n\n- Includes raw data and\u00a0MetaTiME score for the TME cells.\n\n### Contact\n\n\nYi Zhang, Ph.D.\n\nyiz [AT] ds.dfci.harvard.edu\n\n[Twitter](https://twitter.com/Wings7Spread) | [Website](https://yi-zhang.github.io/)\n\nResearch Fellow\n\nDepartment of Data Science\n\nDana-Farber Cancer Institute\n\nHarvard University T.H. Chan School of Public Health\n\n\n\n\n\n",
"bugtrack_url": null,
"license": "",
"summary": "Beta MetaTiME: annotate TME scRNA cell states",
"version": "1.2.2",
"split_keywords": [],
"urls": [
{
"comment_text": "",
"digests": {
"md5": "c95834368b296a8c895790098447b5b8",
"sha256": "8f29cd6c8c6161f584e84728074337b069c4774d960d0b9faaeba5d20b6faf27"
},
"downloads": -1,
"filename": "metatime-1.2.2-py3-none-any.whl",
"has_sig": false,
"md5_digest": "c95834368b296a8c895790098447b5b8",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.6",
"size": 1575971,
"upload_time": "2022-12-19T03:35:38",
"upload_time_iso_8601": "2022-12-19T03:35:38.578461Z",
"url": "https://files.pythonhosted.org/packages/f5/6a/9ac14e8e5fc88a06ffb76a63cdb6118edaef407ecaecf8a11afdcb2d4806/metatime-1.2.2-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"md5": "39d264544ec137231173042370a11143",
"sha256": "1567a841873e8eb55dda0d6779c46448438c852b939e78b2e92b9142cfb54c2b"
},
"downloads": -1,
"filename": "metatime-1.2.2.tar.gz",
"has_sig": false,
"md5_digest": "39d264544ec137231173042370a11143",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.6",
"size": 8093662,
"upload_time": "2022-12-19T03:35:42",
"upload_time_iso_8601": "2022-12-19T03:35:42.288808Z",
"url": "https://files.pythonhosted.org/packages/8f/95/91b8db9e3ecd8663e3e36545b2a6bd66346e3ba604b68a21bf3a95c7f29c/metatime-1.2.2.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2022-12-19 03:35:42",
"github": true,
"gitlab": false,
"bitbucket": false,
"github_user": "yi-zhang",
"github_project": "MetaTiME.git",
"lcname": "metatime"
}
JSON
