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cellvgae

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0.0.1b4 cellvgae-0.0.1b4-py3-none-any.whl

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Project: cellvgae
Version: 0.0.1b4
Filename: cellvgae-0.0.1b4-py3-none-any.whl
Download: [link]
Size: 18835
MD5: 36046fde6f0ce3d19067ab62f072ae01
SHA256: aacbfa6637ad8eef527a9d466aceec4ea0ac59a889b613ad2eca83ecabd17379
Uploaded: 2021-11-11 13:39:10 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt

METADATA

Metadata-Version: 2.1
Name: cellvgae
Version: 0.0.1b4
Summary: CellVGAE uses the connectivity between cells (such as k-nearest neighbour graphs) with gene expression values as node features to learn high-quality cell representations in a lower-dimensional space
Author: David Buterez
Author-Email: david.buterez[at]gmail.com
Home-Page: https://github.com/davidbuterez/CellVGAE
License: MIT
Keywords: scrnaseq,graph,gnn,dimensionality,reduction,neural
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Requires-Dist: torch (>=1.6.0)
Requires-Dist: umap-learn (>=0.5.1)
Requires-Dist: hdbscan (>=0.8.27)
Requires-Dist: seaborn (>=0.11.1)
Requires-Dist: matplotlib (>=3.3.4)
Requires-Dist: scanpy (>=1.7.2)
Requires-Dist: anndata (>=0.7.5)
Requires-Dist: tqdm (>=4.61.2)
Requires-Dist: termcolor (>=1.1.0)
Requires-Dist: numpy (>=1.19.5)
Requires-Dist: pandas (>=1.2.4)
Requires-Dist: torch-geometric (>=1.7.0)
Requires-Dist: scikit-learn (>=0.24.2)
Requires-Dist: torch-sparse (>=0.6.12)
Requires-Dist: torch-scatter (>=2.0.8)
Description-Content-Type: text/markdown
License-File: LICENSE
[Description omitted; length: 6899 characters]

WHEEL

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RECORD

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cellvgae-0.0.1b4.dist-info/LICENSE sha256=snvukZpYkwFmXOz8GkQu4BErwFWQgF_E_IhQKgGcCXM 1091
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cellvgae-0.0.1b4.dist-info/RECORD — —

top_level.txt

cellvgae