| Name | nsforest JSON |
| Version |
3.9.2.5
JSON |
| download |
| home_page | https://github.com/JCVenterInstitute/NSForest |
| Summary | A machine learning method for the discovery of minimum marker gene combinations for cell type identification from single-cell RNA sequencing |
| upload_time | 2023-03-17 06:29:34 |
| maintainer | |
| docs_url | None |
| author | Renee Zhang, Richard Scheuermann, Brian Aevermann |
| requires_python | >=3.8 |
| license | MIT License Copyright (c) 2022 J. Craig Venter Institute Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
machine learning
scrna
cell type
random forest
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# NS-Forest
<img src="NS-Forest-sticker.png" width="110" height="125">
## Getting Started
Download NSForest_v3dot9_1.py.
### Prerequisites
* This is a python script written and tested in python 3.8, scanpy 1.8.2, anndata 0.8.0.
* Other required libraries: numpy, pandas, sklearn, itertools, time, tqdm.
### Tutorial
Follow the [tutorial](https://jcventerinstitute.github.io/celligrate/tutorials/NS-Forest_tutorial.html) to get started.
## Versioning and citations
This is version 3.9.1. Earlier releases are managed in [Releases](https://github.com/JCVenterInstitute/NSForest/releases).
Version 2 and beyond:
Aevermann BD, Zhang Y, Novotny M, Keshk M, Bakken TE, Miller JA, Hodge RD, Lelieveldt B, Lein ES, Scheuermann RH. A machine learning method for the discovery of minimum marker gene combinations for cell-type identification from single-cell RNA sequencing. Genome Res. 2021 Jun 4:gr.275569.121. doi: 10.1101/gr.275569.121.
Version 1.3/1.0:
Aevermann BD, Novotny M, Bakken T, Miller JA, Diehl AD, Osumi-Sutherland D, Lasken RS, Lein ES, Scheuermann RH. Cell type discovery using single-cell transcriptomics: implications for ontological representation. Hum Mol Genet. 2018 May 1;27(R1):R40-R47. doi: 10.1093/hmg/ddy100.
## Authors
* Yun (Renee) Zhang zhangy@jcvi.org
* Richard Scheuermann RScheuermann@jcvi.org
* Brian Aevermann baevermann@chanzuckerberg.com
## License
This project is licensed under the [MIT License](https://github.com/JCVenterInstitute/NSForest/blob/master/LICENSE).
## Acknowledgments
* BICCN
* Allen Institute of Brain Science
* Chan Zuckerberg Initiative
* California Institute for Regenerative Medicine
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