Skip to main content

SIGnature is a Python package that empowers researchers to rapidly query gene sets across diverse single-cell RNA sequencing (scRNA-seq) datasets through precomputed gene attribution scores.

Beyond querying capabilities, SIGnature also enables the generation of attribution scores on novel scRNA-seq data, allowing seamless integration with our collection of annotated studies.

Documentation

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

Download & Install

The SIGnature API is under activate development. The latest development API can be downloaded and installed as follows:

git clone https://github.com/genentech/signature.git
cd signature
pip install -e .

SIGnature release versions can be installed via:

pip install sc-signature

Precomputed attribution scores can be downloaded from Zenodo: https://zenodo.org/communities/signature/

To generate attribution scores on new data, helper files can be downloaded from Zenodo: https://zenodo.org/records/17903196

SIGnature currently supports calculating attributions using the following models:

  1. SCimilarity: pretrained weights included in helper files, but can also be downloaded here: https://zenodo.org/records/15729925

  2. scFoundation: pretrained weights can be downloaded here: https://huggingface.co/genbio-ai/scFoundation/tree/main

  3. scVI: pretrained weights for scVI models trained on CZI Census data can be downloaded here: https://cellxgene.cziscience.com/census-models

  4. SSL-scTab: pretrained weights for self-supervised learning models trained on scTab data can be downloaded here: https://huggingface.co/TillR/sc_pretrained/tree/main

Citation

To cite SIGnature in publications please use:

Foundation Model Attributions Reveal Shared Inflammatory Program Across Diseases

Maxwell P. Gold, Miguel Reyes, Nathaniel Diamant, Tony Kuo, Ehsan Hajiramezanali, Jane W. Newburger, Mary Beth F. Son, Pui Y. Lee, Gabriele Scalia, Aicha BenTaieb, Sharookh B. Kapadia, Anupriya Tripathi, Héctor Corrada Bravo, Graham Heimberg*, Tommaso Biancalani* bioRxiv 2025.06.14.659567; doi: https://doi.org/10.1101/2025.06.14.659567

Metadata

Release files for sc-signature 1.0.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for sc-signature 1.0.0
File Size Uploaded
sc_signature-1.0.0.tar.gz 1.2 MB Details

Built distribution (wheel)

Table of built distributions (wheels) for sc-signature 1.0.0
File Interpreter ABI Platform
sc_signature-1.0.0-py3-none-any.whl Python 3 none any Details

Total release size: 1.2 MB

Release files / sc_signature-1.0.0.tar.gz

Download URL sc_signature-1.0.0.tar.gz
Size 1.2 MB
Tags Source
SHA-256 checksum
How to use checksums
0c5a797db6217581975a20de7f5eb91dc89ba8803be068db18b452a26bc9d9fd
BLAKE2b-256 checksum
How to use checksums
77dd8f757621f06beaa7aa16b9ea0ced75e19a6e3106e08ff7c701c698958fdf
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.11

Release files / sc_signature-1.0.0-py3-none-any.whl

Download URL sc_signature-1.0.0-py3-none-any.whl
Size 30.0 kB
Tags Python 3
SHA-256 checksum
How to use checksums
24b0173b06fbb142b72b53a7100eb843d3260d693d40e0509fce20f70ca02f83
BLAKE2b-256 checksum
How to use checksums
c1885470555891538447031f2a66dafccc92a97086a30eb360e0c75743a8d507
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.11

Release history Release notifications | RSS feed

This release

1.0.0 This release

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page