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Author:
GGE Team
License:
MIT
Summary:
A Standardized Framework for Evaluating Gene Expression Generative Models. Accepted at Gen2 Workshop @ ICLR 2026. Provides explicit computation space options (raw/pca/deg), perturbation-effect correlation, and standardized reporting for reproducible benchmarking.
Latest version:
1.0.1
Required dependencies:
anndata
|
geomloss
|
matplotlib
|
numpy
|
pandas
|
scanpy
|
scikit-learn
|
scipy
|
seaborn
|
torch
Optional dependencies:
plotly
|
pykeops
|
umap-learn
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