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README.rst

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SIGnature: Scoring the Importance of Genes
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**SIGnature** is a python package that enables the efficient generation and collection of gene attributions.
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**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.
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Attribution scores can be used for rapid gene signature scoring across database of 22 million single cell transcriptomes.
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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.
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See the notebooks folder for tutorials on querying and generating attributions.
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Documentation
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--------------------------------------------------------------------------------
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Tutorials and API documentation can be found at:
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https://genentech.github.io/signature/index.html
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Download & Install
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The SIGnature API is under activate development. The latest development API can be downloaded and installed as follows::
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git clone https://github.com/genentech/signature.git
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cd signature
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pip install -e .
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Precomputed attribution scores can be downloaded from Zenodo:
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https://zenodo.org/communities/signature/
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To generate attribution scores on new data, the SCimilarity model can be downloaded from Zenodo:
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https://zenodo.org/records/15729925
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Citation
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--------------------------------------------------------------------------------
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To cite SIGnature in publications please use:
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**Foundation Model Attributions Reveal Shared Inflammatory Program Across Diseases**
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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

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docs/about.rst

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To cite SIGnature in publications please use:
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Foundation Model Attributions Reveal Shared Inflammatory Program Across Diseases
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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
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bioRxiv 2025.06.14.659567; doi: https://doi.org/10.1101/2025.06.14.659567
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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

docs/index.rst

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Scoring the Importance of Genes using scRNA-seq Foundation Models
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SIGnature is a python package that enables the efficient generation and
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collection of gene attributions.
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**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.
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Attribution scores can be used for rapid gene signature scoring across database
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of 22 million single cell transcriptomes.
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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.
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.. image:: _static/overview_image.png
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:width: 75%
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Generate attributions
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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:mod:`signature.signature` also provides tools to generate attribution scores on new data that can be integrated with out existing scores.
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:mod:`signature.signature` also provides tools to generate attribution scores on new data that can be integrated with our collection of annotated datasets.
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.. image:: _static/generate_image.png
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:width: 75%

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