devCellPy is a Python package designed for hierarchical multilayered classification of cells based on single-cell RNA-sequencing (scRNA-seq). It implements the machine learning algorithm Extreme Gradient Boost (XGBoost) (Chen and Guestrin, 2016) to automatically predict cell identities across complex permutations of layers and sublayers of annotation.
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Release files for devCellPy 1.5.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| devCellPy-1.5.0.tar.gz | 17.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| devCellPy-1.5.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 36.4 kB
Release files / devCellPy-1.5.0.tar.gz
| Download URL | devCellPy-1.5.0.tar.gz |
|---|---|
| Size | 17.5 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.12.2
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Release files / devCellPy-1.5.0-py3-none-any.whl
| Download URL | devCellPy-1.5.0-py3-none-any.whl |
|---|---|
| Size | 18.9 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.12.2
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