scib-metrics
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 3.8 or newer installed on your system. If you don't have Python installed, we recommend installing Miniconda.
There are several alternative options to install scib-metrics:
- Install the latest release on PyPI:
pip install scib-metrics
- Install the latest development version:
pip install git+https://github.com/yoseflab/scib-metrics.git@main
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
t.b.a
3 maintainers
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