nsforest 3.9.2.5

A machine learning method for the discovery of minimum marker gene combinations for cell type identification from single-cell RNA sequencing

NS-Forest

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 to get started.

Versioning and citations

This is version 3.9.1. Earlier releases 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.

Authors

• Yun (Renee) Zhang [e-mail]
• Richard Scheuermann [e-mail]
• Brian Aevermann [e-mail]

License

This project is licensed under the MIT License.

Acknowledgments

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