NS-Forest can be installed using pip:
sudo pip install nsforest
If you are using a machine on which you lack administrative access, NS-Forest can be installed locally using pip:
pip install --user nsforest
NS-Forest can also be installed using conda:
conda install -c ttl074 nsforest
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.
Follow the tutorial to get started.
If you download 'NSForest_v3dot9_2.py' directly, replace the version to the most updated one in the tutorial.
If you download the pip or conda package, use the following in the tutorial.
import nsforest as ns
ns.NSForest()
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
This project is licensed under the MIT License.
- BICCN
- Allen Institute of Brain Science
- Chan Zuckerberg Initiative
- California Institute for Regenerative Medicine