scib-metrics

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Accelerated and Python-only metrics for benchmarking single-cell integration outputs.

This package contains implementations of metrics for evaluating the performance of single-cell omics data integration methods. The implementations of these metrics use JAX when possible for jit-compilation and hardware acceleration. All implementations are in Python.

Currently we are porting metrics used in the scIB manuscript (and code). Deviations from the original implementations are documented. However, metric values from this repository should not be compared to the scIB repository.

Getting started

Please refer to the documentation.

Installation

You need to have Python 3.12 or newer installed on your system. If you don't have Python installed, we recommend installing Miniconda.

There are several options to install scib-metrics:

  1. Install the latest release on PyPI:
pip install scib-metrics
  1. Install the latest development version:
pip install git+https://github.com/yoseflab/scib-metrics.git@main

To leverage hardware acceleration (e.g., GPU) please install the apprpriate version of JAX separately. Often this can be easier by using conda-distributed versions of JAX.

Release notes

See the changelog.

Contact

For questions and help requests, you can reach out in the scverse Discourse. If you found a bug, please use the issue tracker.

Citation

Please cite:

Adam Gayoso, Martin Kim, Ori Kronfeld, Justin Hong, & Yosef, N. (2026).
YosefLab/scib-metrics: scib-metrics 0.5.8 (v0.5.8). Zenodo.
https://doi.org/10.5281/zenodo.18504367

In addition, please cite the original single-cell integration benchmarking work:

@article{luecken2022benchmarking,
  title={Benchmarking atlas-level data integration in single-cell genomics},
  author={Luecken, Malte D and B{\"u}ttner, Maren and Chaichoompu, Kridsadakorn and Danese, Anna and Interlandi, Marta and M{\"u}ller, Michaela F and Strobl, Daniel C and Zappia, Luke and Dugas, Martin and Colom{\'e}-Tatch{\'e}, Maria and others},
  journal={Nature methods},
  volume={19},
  number={1},
  pages={41--50},
  year={2022},
  publisher={Nature Publishing Group}
}

References for individual metrics can be also found in the corresponding documentation.

Project links

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Credits

Author: Adam Gayoso

Maintainer: Adam Gayoso

GitHub Statistics

Data verified by PyPI on Sep 10, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License

BSD 3-Clause License

Requires

Python >=3.12

Provides Extra

parallel tutorial

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