Documentation: https://nsforest.readthedocs.io/en/latest/
BioArchive Link: https://www.biorxiv.org/content/10.1101/2024.04.22.590194v1.full
In terminal:
git clone https://github.com/JCVenterInstitute/NSForest.git
cd NSForest
conda env create -f nsforest.yml
conda activate nsforest
cd tutorials
Follow the on readthedocs: https://nsforest.readthedocs.io/en/latest/tutorial.html
Will be uploaded to official conda channel soon.
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.
Earlier versions are managed in 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.
- Yun (Renee) Zhang zhangy@jcvi.org
- Richard Scheuermann RScheuermann@jcvi.org
- Brian Aevermann baevermann@chanzuckerberg.com
- Angela Liu aliu@jcvi.org
- Beverly Peng bpeng@jcvi.org
This project is licensed under the MIT License.
- BICCN
- Allen Institute of Brain Science
- Chan Zuckerberg Initiative
- California Institute for Regenerative Medicine