Metadata-Version: 2.4
Name: scimilarity
Version: 0.4.1
Summary: Single cell embedding into latent space that quantifies similarity between expression states.
Home-page: https://github.com/genentech/scimilarity
Author: Graham Heimberg, Tony Kuo, Nathaniel Diamant, Omar Salem, Héctor Corrada Bravo, Jason A. Vander Heiden
Author-email: heimberg@gene.com
Project-URL: Documentation, https://genentech.github.io/scimilarity
Project-URL: Source, https://github.com/genentech/scimilarity
Project-URL: Tracker, https://github.com/genentech/scimilarity/issues
Keywords: single-cell embedding/retrieval
Platform: any
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Requires-Python: >=3.10
Description-Content-Type: text/x-rst
License-File: LICENSE
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Requires-Dist: pytorch-lightning>=2.0.0
Requires-Dist: scanpy>=1.9.2
Requires-Dist: tiledb>=0.18.2
Requires-Dist: tiledb-vector-search>=0.11.0
Requires-Dist: torch>=1.10.1
Requires-Dist: tqdm
Requires-Dist: zarr<3.0.0,>=2.6.1
Requires-Dist: importlib-metadata; python_version < "3.8"
Provides-Extra: testing
Requires-Dist: setuptools; extra == "testing"
Requires-Dist: pytest; extra == "testing"
Requires-Dist: pytest-cov; extra == "testing"
Dynamic: license-file

SCimilarity
================================================================================

**SCimilarity** is a unifying representation of single cell expression profiles
that quantifies similarity between expression states and generalizes to
represent new studies without additional training.

This enables a novel cell search capability, which sifts through millions of
profiles to find cells similar to a query cell state and allows researchers to
quickly and systematically leverage massive public scRNA-seq atlases to learn
about a cell state of interest.

Documentation
--------------------------------------------------------------------------------

Tutorials and API documentation can be found at:
https://genentech.github.io/scimilarity/index.html

Download & Install
--------------------------------------------------------------------------------

The latest API release can be installed from PyPI::

    pip install scimilarity

Pretrained model weights, embeddings, kNN graphs, a single-cell metadata
can be downloaded from:
https://zenodo.org/records/10685499

A docker container with SCimilarity preinstalled can be pulled from:
https://ghcr.io/genentech/scimilarity

Citation
--------------------------------------------------------------------------------

To cite SCimilarity in publications please use:

**A cell atlas foundation model for scalable search of similar human cells.**
*Graham Heimberg\*, Tony Kuo\*, Daryle J. DePianto, Tobias Heigl,
Nathaniel Diamant, Omar Salem, Gabriele Scalia, Tommaso Biancalani,
Jason R. Rock, Shannon J. Turley, Héctor Corrada Bravo, Josh Kaminker\*\*,
Jason A. Vander Heiden\*\*, Aviv Regev\*\*.*
Nature (2024). https://doi.org/10.1038/s41586-024-08411-y
