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.

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 [email protected]
• Richard Scheuermann [email protected]
• Brian Aevermann [email protected]
• Angela Liu [email protected]
• Beverly Peng [email protected]
• Ajith V. Pankajam [email protected]

License

This project is licensed under the MIT License.

Acknowledgments

• BICCN
• Allen Institute of Brain Science
• Chan Zuckerberg Initiative
• California Institute for Regenerative Medicine