scspecies
scSpecies is a deep‐learning framework for aligning single‐cell RNA-seq datasets across species.
Built on top of scVI and transfer-learning principles, it learns a shared embedding space that directly matches cell populations from different organisms.
Installation
To install the latest stable release of scSpecies run one of the following commands. scSpecies defines two extras required to run the tutorial notebooks, plotting and notebooks.
.. code-block:: bash
pip install scspecies
After installing, confirm that scSpecies loads:
.. code-block:: bash
python -c "import scspecies; print(scspecies.__version__)"
Documentation
Full API docs, tutorials, and examples are available at: scSpecies Documentation (Read the Docs)
Tutorial Notebooks
Start with running the tutorial notebooks. They can be downloaded from the GitHub repository.
1 maintainer
Metadata
1 maintainer
Release files for scspecies 0.1.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| scspecies-0.1.4.tar.gz | 42.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| scspecies-0.1.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 84.1 kB
Release files / scspecies-0.1.4.tar.gz
| Download URL | scspecies-0.1.4.tar.gz |
|---|---|
| Size | 42.2 kB |
| Tags | Source |
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twine/6.1.0 CPython/3.11.8
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Release files / scspecies-0.1.4-py3-none-any.whl
| Download URL | scspecies-0.1.4-py3-none-any.whl |
|---|---|
| Size | 41.9 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.11.8
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