nsforest

Name	nsforest JSON
Version	4.0.0 JSON
	download
home_page	https://github.com/JCVenterInstitute/NSForest
Summary	Discovery of cell type classification marker genes from single cell RNA sequencing data using NS-Forest
upload_time	2024-06-14 20:45:46
maintainer	None
docs_url	None
author	Renee Zhang, Richard Scheuermann, Brian Aevermann, Angela Liu, Beverly Peng, Ajith V. Pankajam
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 decision trees
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

# NS-Forest v4.0

Documentation: https://nsforest.readthedocs.io/en/latest/

BioArchive Link: https://www.biorxiv.org/content/10.1101/2024.04.22.590194v1.full

## Download and installation

In terminal:

git clone https://github.com/JCVenterInstitute/NSForest.git

cd NSForest

conda env create -f nsforest.yml

conda activate nsforest

## Tutorial

Follow the on readthedocs: https://nsforest.readthedocs.io/en/latest/tutorial.html

## Pipeline

Will be uploaded to official PyPI channel soon.

## Prerequisites
* This is a python script written and tested in python 3.11, scanpy 1.9.6.
* Other required libraries: numpy, pandas, sklearn, plotly, time, tqdm.

## Versions and citations

This is version 4.0.0. Earlier versions are managed in [Releases](https://github.com/JCVenterInstitute/NSForest/releases).

Version 2:

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 richard.scheuermann@nih.gov
* Brian Aevermann baevermann@chanzuckerberg.com
* Angela Liu aliu@jcvi.org
* Beverly Peng bpeng@jcvi.org
* Ajith V. Pankajam ajith.viswanathanasaripankajam@nih.gov

## 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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Renee Zhang, Richard Scheuermann, Brian Aevermann, Angela Liu, Beverly Peng, Ajith V. Pankajam