frmatch: A Python package for the FR-Match method

Preprint: Hu et al. 2025. Benchmarking single cell transcriptome matching methods for incremental growth of reference atlases. https://www.biorxiv.org/content/10.1101/2025.04.10.648034v1.

Download and installation

In terminal:

git clone https://github.com/BeverlyPeng/frmatch.git

cd frmatch

conda env create -f nsforest.yml

conda activate nsforest

pip install .

Tutorial and documentation

Please start from the tutorials folder.

Documentation: tbd

Prerequisites

• This python package is written and tested in python 3.11, scanpy 1.9.6.
• Other required libraries: numpy, pandas, sklearn, plotly, time, tqdm.
• Feature selection: JCVenterInstitute/NSForest

Pipeline

Versions and citations

v2.0 (Python):

Hu et al. 2025. Benchmarking single cell transcriptome matching methods for incremental growth of reference atlases. https://www.biorxiv.org/content/10.1101/2025.04.10.648034v1.

v2.0:

Zhang et al. 2022. Cell type matching in single-cell RNA-sequencing data using FR-Match. Scientific Reports, https://doi.org/10.1038/s41598-022-14192-z.

v1.0:

Zhang et al. 2020. FR-Match: robust matching of cell type clusters from single cell RNA sequencing data using the Friedman–Rafsky non-parametric test. Briefings in Bioinformatics, https://doi.org/10.1093/bib/bbaa339.

Authors

• Beverly Peng (bpeng@jcvi.org)

• Joyce Hu (johu@jcvi.org)

• Richard Scheuermann (richard.scheuermann@nih.gov)

• Yun (Renee) Zhang (yun.zhang@nih.gov)

License

This project is licensed under the MIT License.

Acknowledgments

• Allen Institute for Brain Science
• Chan Zuckerberg Initiative (DAF 2018–182730)
• NIH BRAIN Initiative (1RF1MH123220)
• NIH Common Fund (1R03OD036499, OT2OD033756 and OT2OD026671)
• National Library of Medicine